From c8cebce6788a13a31bfb89f3eb7e22698cd7dba8 Mon Sep 17 00:00:00 2001
From: VahdPourAmin <v.pouramin@gmail.com>
Date: Thu, 26 Aug 2021 09:35:15 +0200
Subject: [PATCH] add freak kernel init

---
 CPU_version/Forster2014ICRA.pdf               |  Bin 1469859 -> 0 bytes
 CPU_version/LICENCE                           |  675 -------
 CPU_version/README.md                         |   64 -
 CPU_version/__init__.py                       |    0
 CPU_version/svo/.idea/.gitignore              |    8 -
 CPU_version/svo/.idea/misc.xml                |    4 -
 CPU_version/svo/.idea/modules.xml             |    8 -
 CPU_version/svo/.idea/svo.iml                 |    2 -
 CPU_version/svo/.idea/vcs.xml                 |    6 -
 CPU_version/svo/CMakeLists.txt                |  156 --
 CPU_version/svo/CMakeModules/FindEigen.cmake  |   81 -
 CPU_version/svo/CMakeModules/FindG2O.cmake    |  113 --
 CPU_version/svo/Doxyfile                      | 1782 -----------------
 CPU_version/svo/doc/.gitignore                |    2 -
 CPU_version/svo/doc/notation.ipe              |  312 ---
 CPU_version/svo/doc/notation.pdf              |  Bin 50379 -> 0 bytes
 CPU_version/svo/doc/notation.png              |  Bin 27376 -> 0 bytes
 .../svo/include/svo/bundle_adjustment.h       |  109 -
 CPU_version/svo/include/svo/config.h          |  177 --
 CPU_version/svo/include/svo/depth_filter.h    |  171 --
 CPU_version/svo/include/svo/feature.h         |   75 -
 .../svo/include/svo/feature_alignment.h       |   63 -
 .../svo/include/svo/feature_detection.h       |  107 -
 CPU_version/svo/include/svo/frame.h           |  154 --
 .../svo/include/svo/frame_handler_base.h      |  123 --
 .../svo/include/svo/frame_handler_mono.h      |  104 -
 CPU_version/svo/include/svo/global.h          |  101 -
 CPU_version/svo/include/svo/imu_integration.h |  121 --
 CPU_version/svo/include/svo/initialization.h  |   83 -
 CPU_version/svo/include/svo/map.h             |  136 --
 CPU_version/svo/include/svo/matcher.h         |  130 --
 CPU_version/svo/include/svo/point.h           |  108 -
 CPU_version/svo/include/svo/pose_optimizer.h  |   50 -
 CPU_version/svo/include/svo/reprojector.h     |  101 -
 .../svo/include/svo/sparse_img_align.h        |   83 -
 CPU_version/svo/include/svo/svoVisionFactor.h |   70 -
 CPU_version/svo/package.xml                   |   27 -
 CPU_version/svo/src/bundle_adjustment.cpp     |  435 ----
 CPU_version/svo/src/config.cpp                |  102 -
 CPU_version/svo/src/depth_filter.cpp          |  352 ----
 CPU_version/svo/src/feature_alignment.cpp     |  601 ------
 CPU_version/svo/src/feature_detection.cpp     |  118 --
 CPU_version/svo/src/frame.cpp                 |  190 --
 CPU_version/svo/src/frame_handler_base.cpp    |  199 --
 CPU_version/svo/src/frame_handler_mono.cpp    |  307 ---
 CPU_version/svo/src/imu_integration.cpp       |  153 --
 CPU_version/svo/src/initialization.cpp        |  199 --
 CPU_version/svo/src/map.cpp                   |  368 ----
 CPU_version/svo/src/matcher.cpp               |  323 ---
 CPU_version/svo/src/point.cpp                 |  179 --
 CPU_version/svo/src/pose_optimizer.cpp        |  165 --
 CPU_version/svo/src/reprojector.cpp           |  219 --
 CPU_version/svo/src/sparse_img_align.cpp      |  274 ---
 CPU_version/svo/test/README.md                |   24 -
 CPU_version/svo/test/benchmark.csv            |  307 ---
 CPU_version/svo/test/data/.gitignore          |    2 -
 CPU_version/svo/test/results/.gitignore       |    2 -
 CPU_version/svo/test/test_depth_filter.cpp    |  206 --
 .../svo/test/test_feature_alignment.cpp       |  124 --
 .../svo/test/test_feature_detection.cpp       |   74 -
 CPU_version/svo/test/test_matcher.cpp         |  200 --
 CPU_version/svo/test/test_pipeline.cpp        |   98 -
 CPU_version/svo/test/test_pose_optimizer.cpp  |  110 -
 .../svo/test/test_sparse_img_align.cpp        |  163 --
 CPU_version/svo/test/test_utils.h             |   57 -
 CPU_version/svo_analysis/.gitignore           |    1 -
 CPU_version/svo_analysis/CMakeLists.txt       |    8 -
 CPU_version/svo_analysis/README.md            |   27 -
 CPU_version/svo_analysis/__init__.py          |    0
 .../svo_analysis/comparisons/speed.yaml       |   14 -
 .../svo_analysis/comparisons/textures.yaml    |   22 -
 .../svo_analysis/experiments/.gitignore       |    2 -
 CPU_version/svo_analysis/package.xml          |   19 -
 CPU_version/svo_analysis/results/.gitignore   |    2 -
 CPU_version/svo_analysis/scripts/__init__.py  |    0
 CPU_version/svo_analysis/scripts/benchmark.py |  111 -
 .../svo_analysis/scripts/compare_results.py   |  150 --
 .../svo_analysis/scripts/comparison.py        |  159 --
 CPU_version/svo_analysis/scripts/evaluate.py  |   58 -
 CPU_version/svo_analysis/setup.py             |   12 -
 CPU_version/svo_analysis/src/__init__.py      |    0
 .../svo_analysis/src/svo_analysis/__init__.py |    0
 .../src/svo_analysis/analyse_dataset.py       |   41 -
 .../src/svo_analysis/analyse_depth.py         |   66 -
 .../src/svo_analysis/analyse_logs.py          |   74 -
 .../src/svo_analysis/analyse_timing.py        |   68 -
 .../src/svo_analysis/analyse_trajectory.py    |  185 --
 .../svo_analysis/filter_groundtruth_smooth.py |   60 -
 .../src/svo_analysis/hand_eye_calib.py        |  227 ---
 .../tum_benchmark_tools/__init__.py           |    2 -
 .../tum_benchmark_tools/associate.py          |  130 --
 .../tum_benchmark_tools/evaluate_ate.py       |  194 --
 .../tum_benchmark_tools/evaluate_rpe.py       |  382 ----
 CPU_version/svo_msgs/.idea/.gitignore         |    8 -
 CPU_version/svo_msgs/.idea/misc.xml           |    4 -
 CPU_version/svo_msgs/.idea/modules.xml        |    8 -
 CPU_version/svo_msgs/.idea/svo_msgs.iml       |    2 -
 CPU_version/svo_msgs/.idea/vcs.xml            |    6 -
 CPU_version/svo_msgs/CMakeLists.txt           |   33 -
 CPU_version/svo_msgs/msg/DenseInput.msg       |    6 -
 CPU_version/svo_msgs/msg/Feature.msg          |    5 -
 CPU_version/svo_msgs/msg/Info.msg             |    6 -
 CPU_version/svo_msgs/msg/NbvTrajectory.msg    |    2 -
 CPU_version/svo_msgs/package.xml              |   19 -
 CPU_version/vio_svo/.idea/.gitignore          |    8 -
 CPU_version/vio_svo/.idea/misc.xml            |    4 -
 CPU_version/vio_svo/.idea/modules.xml         |    8 -
 CPU_version/vio_svo/.idea/svo_ros.iml         |    2 -
 CPU_version/vio_svo/.idea/vcs.xml             |    6 -
 CPU_version/vio_svo/CMakeLists.txt            |   90 -
 .../vio_svo/include/vio_svo/visualizer.h      |   73 -
 CPU_version/vio_svo/launch/Px30.launch        |   22 -
 CPU_version/vio_svo/launch/live.launch        |   16 -
 CPU_version/vio_svo/launch/test.launch        |   22 -
 CPU_version/vio_svo/launch/unity.launch       |   22 -
 CPU_version/vio_svo/msg/Info.msg              |    6 -
 CPU_version/vio_svo/package.xml               |   43 -
 CPU_version/vio_svo/param/camera_atan.yaml    |    8 -
 CPU_version/vio_svo/param/camera_pinhole.yaml |   11 -
 CPU_version/vio_svo/param/px30.yaml           |    8 -
 CPU_version/vio_svo/param/unity.yaml          |    8 -
 CPU_version/vio_svo/param/vo_accurate.yaml    |    4 -
 CPU_version/vio_svo/param/vo_fast.yaml        |   13 -
 CPU_version/vio_svo/rqt.perspective           |  293 ---
 CPU_version/vio_svo/rviz_config.rviz          |  153 --
 CPU_version/vio_svo/src/visualizer.cpp        |  127 --
 CPU_version/vio_svo/src/vo_node.cpp           |  148 --
 GPU_version/vio/include/vio/reprojector.h     |   10 +-
 GPU_version/vio/kernel/freak.cl               |  129 ++
 GPU_version/vio/kernel/integral_image.cl      |   14 +
 GPU_version/vio/src/cl_class.cpp              |    4 +-
 GPU_version/vio/src/frame_handler_mono.cpp    |    1 +
 GPU_version/vio/src/reprojector.cpp           |  234 ++-
 133 files changed, 378 insertions(+), 14079 deletions(-)
 delete mode 100755 CPU_version/Forster2014ICRA.pdf
 delete mode 100755 CPU_version/LICENCE
 delete mode 100755 CPU_version/README.md
 delete mode 100644 CPU_version/__init__.py
 delete mode 100644 CPU_version/svo/.idea/.gitignore
 delete mode 100644 CPU_version/svo/.idea/misc.xml
 delete mode 100644 CPU_version/svo/.idea/modules.xml
 delete mode 100644 CPU_version/svo/.idea/svo.iml
 delete mode 100644 CPU_version/svo/.idea/vcs.xml
 delete mode 100644 CPU_version/svo/CMakeLists.txt
 delete mode 100644 CPU_version/svo/CMakeModules/FindEigen.cmake
 delete mode 100644 CPU_version/svo/CMakeModules/FindG2O.cmake
 delete mode 100644 CPU_version/svo/Doxyfile
 delete mode 100644 CPU_version/svo/doc/.gitignore
 delete mode 100644 CPU_version/svo/doc/notation.ipe
 delete mode 100644 CPU_version/svo/doc/notation.pdf
 delete mode 100644 CPU_version/svo/doc/notation.png
 delete mode 100644 CPU_version/svo/include/svo/bundle_adjustment.h
 delete mode 100644 CPU_version/svo/include/svo/config.h
 delete mode 100644 CPU_version/svo/include/svo/depth_filter.h
 delete mode 100644 CPU_version/svo/include/svo/feature.h
 delete mode 100644 CPU_version/svo/include/svo/feature_alignment.h
 delete mode 100644 CPU_version/svo/include/svo/feature_detection.h
 delete mode 100644 CPU_version/svo/include/svo/frame.h
 delete mode 100644 CPU_version/svo/include/svo/frame_handler_base.h
 delete mode 100644 CPU_version/svo/include/svo/frame_handler_mono.h
 delete mode 100644 CPU_version/svo/include/svo/global.h
 delete mode 100644 CPU_version/svo/include/svo/imu_integration.h
 delete mode 100644 CPU_version/svo/include/svo/initialization.h
 delete mode 100644 CPU_version/svo/include/svo/map.h
 delete mode 100644 CPU_version/svo/include/svo/matcher.h
 delete mode 100644 CPU_version/svo/include/svo/point.h
 delete mode 100644 CPU_version/svo/include/svo/pose_optimizer.h
 delete mode 100644 CPU_version/svo/include/svo/reprojector.h
 delete mode 100644 CPU_version/svo/include/svo/sparse_img_align.h
 delete mode 100644 CPU_version/svo/include/svo/svoVisionFactor.h
 delete mode 100644 CPU_version/svo/package.xml
 delete mode 100644 CPU_version/svo/src/bundle_adjustment.cpp
 delete mode 100644 CPU_version/svo/src/config.cpp
 delete mode 100644 CPU_version/svo/src/depth_filter.cpp
 delete mode 100644 CPU_version/svo/src/feature_alignment.cpp
 delete mode 100644 CPU_version/svo/src/feature_detection.cpp
 delete mode 100644 CPU_version/svo/src/frame.cpp
 delete mode 100644 CPU_version/svo/src/frame_handler_base.cpp
 delete mode 100644 CPU_version/svo/src/frame_handler_mono.cpp
 delete mode 100644 CPU_version/svo/src/imu_integration.cpp
 delete mode 100644 CPU_version/svo/src/initialization.cpp
 delete mode 100644 CPU_version/svo/src/map.cpp
 delete mode 100644 CPU_version/svo/src/matcher.cpp
 delete mode 100644 CPU_version/svo/src/point.cpp
 delete mode 100644 CPU_version/svo/src/pose_optimizer.cpp
 delete mode 100644 CPU_version/svo/src/reprojector.cpp
 delete mode 100644 CPU_version/svo/src/sparse_img_align.cpp
 delete mode 100644 CPU_version/svo/test/README.md
 delete mode 100644 CPU_version/svo/test/benchmark.csv
 delete mode 100644 CPU_version/svo/test/data/.gitignore
 delete mode 100644 CPU_version/svo/test/results/.gitignore
 delete mode 100644 CPU_version/svo/test/test_depth_filter.cpp
 delete mode 100644 CPU_version/svo/test/test_feature_alignment.cpp
 delete mode 100644 CPU_version/svo/test/test_feature_detection.cpp
 delete mode 100644 CPU_version/svo/test/test_matcher.cpp
 delete mode 100644 CPU_version/svo/test/test_pipeline.cpp
 delete mode 100644 CPU_version/svo/test/test_pose_optimizer.cpp
 delete mode 100644 CPU_version/svo/test/test_sparse_img_align.cpp
 delete mode 100644 CPU_version/svo/test/test_utils.h
 delete mode 100644 CPU_version/svo_analysis/.gitignore
 delete mode 100644 CPU_version/svo_analysis/CMakeLists.txt
 delete mode 100644 CPU_version/svo_analysis/README.md
 delete mode 100644 CPU_version/svo_analysis/__init__.py
 delete mode 100644 CPU_version/svo_analysis/comparisons/speed.yaml
 delete mode 100644 CPU_version/svo_analysis/comparisons/textures.yaml
 delete mode 100644 CPU_version/svo_analysis/experiments/.gitignore
 delete mode 100644 CPU_version/svo_analysis/package.xml
 delete mode 100644 CPU_version/svo_analysis/results/.gitignore
 delete mode 100644 CPU_version/svo_analysis/scripts/__init__.py
 delete mode 100755 CPU_version/svo_analysis/scripts/benchmark.py
 delete mode 100755 CPU_version/svo_analysis/scripts/compare_results.py
 delete mode 100755 CPU_version/svo_analysis/scripts/comparison.py
 delete mode 100755 CPU_version/svo_analysis/scripts/evaluate.py
 delete mode 100644 CPU_version/svo_analysis/setup.py
 delete mode 100644 CPU_version/svo_analysis/src/__init__.py
 delete mode 100644 CPU_version/svo_analysis/src/svo_analysis/__init__.py
 delete mode 100644 CPU_version/svo_analysis/src/svo_analysis/analyse_dataset.py
 delete mode 100755 CPU_version/svo_analysis/src/svo_analysis/analyse_depth.py
 delete mode 100755 CPU_version/svo_analysis/src/svo_analysis/analyse_logs.py
 delete mode 100755 CPU_version/svo_analysis/src/svo_analysis/analyse_timing.py
 delete mode 100755 CPU_version/svo_analysis/src/svo_analysis/analyse_trajectory.py
 delete mode 100644 CPU_version/svo_analysis/src/svo_analysis/filter_groundtruth_smooth.py
 delete mode 100644 CPU_version/svo_analysis/src/svo_analysis/hand_eye_calib.py
 delete mode 100644 CPU_version/svo_analysis/src/svo_analysis/tum_benchmark_tools/__init__.py
 delete mode 100755 CPU_version/svo_analysis/src/svo_analysis/tum_benchmark_tools/associate.py
 delete mode 100755 CPU_version/svo_analysis/src/svo_analysis/tum_benchmark_tools/evaluate_ate.py
 delete mode 100755 CPU_version/svo_analysis/src/svo_analysis/tum_benchmark_tools/evaluate_rpe.py
 delete mode 100644 CPU_version/svo_msgs/.idea/.gitignore
 delete mode 100644 CPU_version/svo_msgs/.idea/misc.xml
 delete mode 100644 CPU_version/svo_msgs/.idea/modules.xml
 delete mode 100644 CPU_version/svo_msgs/.idea/svo_msgs.iml
 delete mode 100644 CPU_version/svo_msgs/.idea/vcs.xml
 delete mode 100644 CPU_version/svo_msgs/CMakeLists.txt
 delete mode 100644 CPU_version/svo_msgs/msg/DenseInput.msg
 delete mode 100644 CPU_version/svo_msgs/msg/Feature.msg
 delete mode 100644 CPU_version/svo_msgs/msg/Info.msg
 delete mode 100644 CPU_version/svo_msgs/msg/NbvTrajectory.msg
 delete mode 100644 CPU_version/svo_msgs/package.xml
 delete mode 100644 CPU_version/vio_svo/.idea/.gitignore
 delete mode 100644 CPU_version/vio_svo/.idea/misc.xml
 delete mode 100644 CPU_version/vio_svo/.idea/modules.xml
 delete mode 100644 CPU_version/vio_svo/.idea/svo_ros.iml
 delete mode 100644 CPU_version/vio_svo/.idea/vcs.xml
 delete mode 100644 CPU_version/vio_svo/CMakeLists.txt
 delete mode 100644 CPU_version/vio_svo/include/vio_svo/visualizer.h
 delete mode 100644 CPU_version/vio_svo/launch/Px30.launch
 delete mode 100644 CPU_version/vio_svo/launch/live.launch
 delete mode 100644 CPU_version/vio_svo/launch/test.launch
 delete mode 100644 CPU_version/vio_svo/launch/unity.launch
 delete mode 100644 CPU_version/vio_svo/msg/Info.msg
 delete mode 100644 CPU_version/vio_svo/package.xml
 delete mode 100644 CPU_version/vio_svo/param/camera_atan.yaml
 delete mode 100644 CPU_version/vio_svo/param/camera_pinhole.yaml
 delete mode 100644 CPU_version/vio_svo/param/px30.yaml
 delete mode 100644 CPU_version/vio_svo/param/unity.yaml
 delete mode 100644 CPU_version/vio_svo/param/vo_accurate.yaml
 delete mode 100644 CPU_version/vio_svo/param/vo_fast.yaml
 delete mode 100644 CPU_version/vio_svo/rqt.perspective
 delete mode 100644 CPU_version/vio_svo/rviz_config.rviz
 delete mode 100644 CPU_version/vio_svo/src/visualizer.cpp
 delete mode 100644 CPU_version/vio_svo/src/vo_node.cpp
 create mode 100644 GPU_version/vio/kernel/freak.cl
 create mode 100644 GPU_version/vio/kernel/integral_image.cl

diff --git a/CPU_version/Forster2014ICRA.pdf b/CPU_version/Forster2014ICRA.pdf
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diff --git a/CPU_version/LICENCE b/CPU_version/LICENCE
deleted file mode 100755
index 70fc6da..0000000
--- a/CPU_version/LICENCE
+++ /dev/null
@@ -1,675 +0,0 @@
-GNU GENERAL PUBLIC LICENSE
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- Copyright (C) 2007 Free Software Foundation, Inc. {http://fsf.org/}
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-  15. Disclaimer of Warranty.
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-  THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
-APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
-HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY
-OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO,
-THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
-PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM
-IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF
-ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
-
-  16. Limitation of Liability.
-
-  IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
-WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS
-THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
-GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE
-USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF
-DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD
-PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
-EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
-SUCH DAMAGES.
-
-  17. Interpretation of Sections 15 and 16.
-
-  If the disclaimer of warranty and limitation of liability provided
-above cannot be given local legal effect according to their terms,
-reviewing courts shall apply local law that most closely approximates
-an absolute waiver of all civil liability in connection with the
-Program, unless a warranty or assumption of liability accompanies a
-copy of the Program in return for a fee.
-
-                     END OF TERMS AND CONDITIONS
-
-            How to Apply These Terms to Your New Programs
-
-  If you develop a new program, and you want it to be of the greatest
-possible use to the public, the best way to achieve this is to make it
-free software which everyone can redistribute and change under these terms.
-
-  To do so, attach the following notices to the program. It is safest
-to attach them to the start of each source file to most effectively
-state the exclusion of warranty; and each file should have at least
-the "copyright" line and a pointer to where the full notice is found.
-
-    {one line to give the program's name and a brief idea of what it does.}
-    Copyright (C) {year} {name of author}
-
-    This program is free software: you can redistribute it and/or modify
-    it under the terms of the GNU General Public License as published by
-    the Free Software Foundation, either version 3 of the License, or
-    (at your option) any later version.
-
-    This program is distributed in the hope that it will be useful,
-    but WITHOUT ANY WARRANTY; without even the implied warranty of
-    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
-    GNU General Public License for more details.
-
-    You should have received a copy of the GNU General Public License
-    along with this program. If not, see {http://www.gnu.org/licenses/}.
-
-Also add information on how to contact you by electronic and paper mail.
-
-  If the program does terminal interaction, make it output a short
-notice like this when it starts in an interactive mode:
-
-    PTAM-GPL Copyright (C) 2013 Oxford-PTAM
-    This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
-    This is free software, and you are welcome to redistribute it
-    under certain conditions; type `show c' for details.
-
-The hypothetical commands `show w' and `show c' should show the appropriate
-parts of the General Public License. Of course, your program's commands
-might be different; for a GUI interface, you would use an "about box".
-
-  You should also get your employer (if you work as a programmer) or school,
-if any, to sign a "copyright disclaimer" for the program, if necessary.
-For more information on this, and how to apply and follow the GNU GPL, see
-{http://www.gnu.org/licenses/}.
-
-  The GNU General Public License does not permit incorporating your program
-into proprietary programs. If your program is a subroutine library, you
-may consider it more useful to permit linking proprietary applications with
-the library. If this is what you want to do, use the GNU Lesser General
-Public License instead of this License. But first, please read
-{http://www.gnu.org/philosophy/why-not-lgpl.html}.
-
diff --git a/CPU_version/README.md b/CPU_version/README.md
deleted file mode 100755
index 8387b0e..0000000
--- a/CPU_version/README.md
+++ /dev/null
@@ -1,64 +0,0 @@
-SVO
-===
-
-This code implements a semi-direct monocular visual odometry pipeline which has been integrated with GTSAM to infused IMU as well. 
-
-
-Paper svo: http://rpg.ifi.uzh.ch/docs/ICRA14_Forster.pdf
-Paper Svo+GTSAM: https://arxiv.org/abs/1512.02363
-
-
-#### Disclaimer
-
-SVO has been tested under ROS Groovy, Hydro and Indigo with Ubuntu 12.04, 13.04 and 14.04. This is research code, any fitness for a particular purpose is disclaimed.
-
-
-#### Licence
-
-The source code is released under a GPLv3 licence. A closed-source professional edition is available for commercial purposes. In this case, please contact the authors for further info.
-
-
-#### Citing
-
-If you use SVO in an academic context, please cite the following publication:
-
-    @inproceedings{Forster2014ICRA,
-      author = {Forster, Christian and Pizzoli, Matia and Scaramuzza, Davide},
-      title = {{SVO}: Fast Semi-Direct Monocular Visual Odometry},
-      booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
-      year = {2014}
-    }
-    
-    
-#### Documentation
-
-The API is documented here: http://uzh-rpg.github.io/rpg_svo/doc/
-The GTSAM documentation  https://gtsam.org/tutorials/
-
-#### Instructions
-
-First install gtsam library => https://github.com/borglab/gtsam
-
-Then follow the SVO instalation
-
-See the Wiki for more instructions. https://github.com/uzh-rpg/rpg_svo/wiki and https://gtsam.org/get_started/
-
-#### Contributing
-
-You are very welcome to contribute to SVO by opening a pull request via Github.
-I try to follow the ROS C++ style guide http://wiki.ros.org/CppStyleGuide
-
-## Setting
-
-You can edit the camera position in the launch file as (The IMU frame will rotate to align with camera frame based on the follwoing Eular angles):
-CPU_version/vio_svo/launch/Px30.launch
-
-    <!-- IMU 2 Camera Frame -->
-    <param name="init_rx" value="1.88496" /><!--  90 + 18 -->
-    <param name="init_ry" value="0.0" /> <!--  0 -->
-    <param name="init_rz" value="0.0" /> <!-- 0  -->
-    
-You can also edit the algorithm parameters in the follwoing file, please look at the config file to underestand the meaning of the parameters (CPU_version/svo/include/svo/config.h)
-
-CPU_version/vio_svo/param/vo_fast.yaml
-    
diff --git a/CPU_version/__init__.py b/CPU_version/__init__.py
deleted file mode 100644
index e69de29..0000000
diff --git a/CPU_version/svo/.idea/.gitignore b/CPU_version/svo/.idea/.gitignore
deleted file mode 100644
index 73f69e0..0000000
--- a/CPU_version/svo/.idea/.gitignore
+++ /dev/null
@@ -1,8 +0,0 @@
-# Default ignored files
-/shelf/
-/workspace.xml
-# Datasource local storage ignored files
-/dataSources/
-/dataSources.local.xml
-# Editor-based HTTP Client requests
-/httpRequests/
diff --git a/CPU_version/svo/.idea/misc.xml b/CPU_version/svo/.idea/misc.xml
deleted file mode 100644
index 79b3c94..0000000
--- a/CPU_version/svo/.idea/misc.xml
+++ /dev/null
@@ -1,4 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="CMakeWorkspace" PROJECT_DIR="$PROJECT_DIR$" />
-</project>
\ No newline at end of file
diff --git a/CPU_version/svo/.idea/modules.xml b/CPU_version/svo/.idea/modules.xml
deleted file mode 100644
index 4c8cf2b..0000000
--- a/CPU_version/svo/.idea/modules.xml
+++ /dev/null
@@ -1,8 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="ProjectModuleManager">
-    <modules>
-      <module fileurl="file://$PROJECT_DIR$/.idea/svo.iml" filepath="$PROJECT_DIR$/.idea/svo.iml" />
-    </modules>
-  </component>
-</project>
\ No newline at end of file
diff --git a/CPU_version/svo/.idea/svo.iml b/CPU_version/svo/.idea/svo.iml
deleted file mode 100644
index f08604b..0000000
--- a/CPU_version/svo/.idea/svo.iml
+++ /dev/null
@@ -1,2 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<module classpath="CMake" type="CPP_MODULE" version="4" />
\ No newline at end of file
diff --git a/CPU_version/svo/.idea/vcs.xml b/CPU_version/svo/.idea/vcs.xml
deleted file mode 100644
index 6c0b863..0000000
--- a/CPU_version/svo/.idea/vcs.xml
+++ /dev/null
@@ -1,6 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="VcsDirectoryMappings">
-    <mapping directory="$PROJECT_DIR$/.." vcs="Git" />
-  </component>
-</project>
\ No newline at end of file
diff --git a/CPU_version/svo/CMakeLists.txt b/CPU_version/svo/CMakeLists.txt
deleted file mode 100644
index c3ace90..0000000
--- a/CPU_version/svo/CMakeLists.txt
+++ /dev/null
@@ -1,156 +0,0 @@
-################################################################################
-# user build settings
-
-SET(TRACE TRUE)
-SET(HAVE_G2O FALSE) 
-SET(USE_ROS TRUE) # Set FALSE if you want to build this package without Catkin
-SET(DEBUG_OUTPUT FALSE) # Only relevant if build without ROS
-
-################################################################################
-
-SET(PROJECT_NAME svo)
-PROJECT(${PROJECT_NAME})
-CMAKE_MINIMUM_REQUIRED (VERSION 2.8.3)
-SET(CMAKE_BUILD_TYPE Release) # Release, RelWithDebInfo
-SET(CMAKE_VERBOSE_MAKEFILE OFF)
-SET(CMAKE_MODULE_PATH ${CMAKE_MODULE_PATH} "${PROJECT_SOURCE_DIR}/CMakeModules/")
-set(CMAKE_C_STANDARD 14)
-set(CMAKE_CXX_STANDARD 14)
-
-# Set definitions
-IF(TRACE)
-  ADD_DEFINITIONS(-DSVO_TRACE)
-ENDIF()
-IF(HAVE_G2O)
-  ADD_DEFINITIONS(-DUSE_BUNDLE_ADJUSTMENT)
-ENDIF()
-IF(USE_ROS)
-  ADD_DEFINITIONS(-DSVO_USE_ROS)
-ENDIF()
-IF(DEBUG_OUTPUT)
-  ADD_DEFINITIONS(-DSVO_DEBUG_OUTPUT)
-ENDIF()
-
-# Set build flags, set ARM_ARCHITECTURE environment variable on Odroid
-# Set build flags. Set IS_ARM on odroid board as environment variable
-SET(CMAKE_CXX_FLAGS "-Wall -D_LINUX -D_REENTRANT -march=native -Wno-unused-variable -Wno-unused-but-set-variable -Wno-unknown-pragmas")
-IF(DEFINED ENV{ARM_ARCHITECTURE})
-  SET(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ")
-ELSE()
-  SET(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mmmx -msse -msse -msse2 -msse3 -mssse3")
-ENDIF()
-IF(CMAKE_COMPILER_IS_GNUCC)
-  SET(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++0x")
-ELSE()
-  SET(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11")
-ENDIF()
-SET(CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS} -O3 -fsee -fomit-frame-pointer -fno-signed-zeros -fno-math-errno -funroll-loops")
-
-# Add plain cmake packages 
-FIND_PACKAGE(OpenCV 3 REQUIRED)
-FIND_PACKAGE(Eigen REQUIRED)
-FIND_PACKAGE(Sophus REQUIRED)
-FIND_PACKAGE(fast REQUIRED)
-FIND_PACKAGE(Boost REQUIRED COMPONENTS thread system)
-FIND_PACKAGE(GTSAM REQUIRED)
-
-set(GTSAM_INCLUDE_DIRS "${GTSAM_INCLUDE_DIR}")
-IF(USE_ROS)
-  FIND_PACKAGE(catkin REQUIRED COMPONENTS roscpp roslib cmake_modules vikit_common vikit_ros)
-  catkin_package(
-      DEPENDS Eigen OpenCV Sophus Boost fast GTSAM
-      CATKIN_DEPENDS roscpp roslib vikit_common vikit_ros
-      INCLUDE_DIRS include
-      LIBRARIES svo
-  )
-ELSE()
-  FIND_PACKAGE(vikit_common REQUIRED)
-  SET(EXECUTABLE_OUTPUT_PATH ${PROJECT_SOURCE_DIR}/bin)
-  SET(LIBRARY_OUTPUT_PATH ${PROJECT_SOURCE_DIR}/lib)
-ENDIF()
-
-# Include dirs
-INCLUDE_DIRECTORIES(
-        include
-  ${Eigen_INCLUDE_DIRS}
-  ${OpenCV_INCLUDE_DIRS}
-  ${Sophus_INCLUDE_DIRS}
-  ${Boost_INCLUDE_DIRS}
-  ${fast_INCLUDE_DIRS} ${GTSAM_INCLUDE_DIR}
-)
-
-# Set link libraries
-LIST(APPEND LINK_LIBS 
-  ${OpenCV_LIBS}
-  ${Sophus_LIBRARIES}
-  ${Boost_LIBRARIES}
-  ${fast_LIBRARIES}
-)
-IF(USE_ROS)
-  INCLUDE_DIRECTORIES(${catkin_INCLUDE_DIRS})
-  LIST(APPEND LINK_LIBS ${catkin_LIBRARIES})
-ELSE()
-  INCLUDE_DIRECTORIES(${vikit_common_INCLUDE_DIRS})
-  LIST(APPEND LINK_LIBS ${vikit_common_LIBRARIES})
-ENDIF()
-
-# Set sourcefiles
-LIST(APPEND SOURCEFILES
-        src/frame_handler_mono.cpp
-        src/frame_handler_base.cpp
-        src/frame.cpp
-        src/point.cpp
-        src/map.cpp
-        src/pose_optimizer.cpp
-        src/initialization.cpp
-        src/matcher.cpp
-        src/reprojector.cpp
-        src/feature_alignment.cpp
-        src/feature_detection.cpp
-        src/depth_filter.cpp
-        src/config.cpp
-        src/sparse_img_align.cpp src/imu_integration.cpp)
-
-# Add g2o if available
-IF(HAVE_G2O)
-  FIND_PACKAGE(G2O REQUIRED)
-  INCLUDE_DIRECTORIES(
-    ${G2O_INCLUDE_DIR}
-    /usr/include/suitesparse # for cholmod
-  )
-  LIST(APPEND LINK_LIBS
-    ${G2O_CORE_LIBRARY} ${G2O_STUFF_LIBRARY} ${G2O_SOLVER_CHOLMOD} ${G2O_SOLVER_CSPARSE} ${G2O_SOLVER_DENSE}
-    ${G2O_SOLVER_PCG} ${G2O_TYPES_SBA} cholmod cxsparse
-  )
-  LIST(APPEND SOURCEFILES src/bundle_adjustment.cpp)
-ENDIF(HAVE_G2O)
-
-# Create svo library
-ADD_LIBRARY(svo SHARED ${SOURCEFILES})
-TARGET_LINK_LIBRARIES(svo ${LINK_LIBS} gtsam)
-set_property(TARGET ${PROJECT_NAME} PROPERTY CXX_STANDARD 14)
-set_property(TARGET ${PROJECT_NAME} PROPERTY CXX_STANDARD_REQUIRED ON)
-
-################################################################################
-# TESTS
-
-#ADD_EXECUTABLE(test_feature_align test/test_feature_alignment.cpp)
-#TARGET_LINK_LIBRARIES(test_feature_align svo)
-
-#ADD_EXECUTABLE(test_pipeline test/test_pipeline.cpp)
-#TARGET_LINK_LIBRARIES(test_pipeline svo)
-
-#ADD_EXECUTABLE(test_matcher test/test_matcher.cpp)
-#TARGET_LINK_LIBRARIES(test_matcher svo)
-
-#ADD_EXECUTABLE(test_feature_detection test/test_feature_detection.cpp)
-#TARGET_LINK_LIBRARIES(test_feature_detection svo)
-
-#ADD_EXECUTABLE(test_depth_filter test/test_depth_filter.cpp)
-#TARGET_LINK_LIBRARIES(test_depth_filter svo)
-
-#ADD_EXECUTABLE(test_sparse_img_align test/test_sparse_img_align.cpp)
-#TARGET_LINK_LIBRARIES(test_sparse_img_align svo)
-
-#ADD_EXECUTABLE(test_pose_optimizer test/test_pose_optimizer.cpp)
-#TARGET_LINK_LIBRARIES(test_pose_optimizer svo)
diff --git a/CPU_version/svo/CMakeModules/FindEigen.cmake b/CPU_version/svo/CMakeModules/FindEigen.cmake
deleted file mode 100644
index 8587367..0000000
--- a/CPU_version/svo/CMakeModules/FindEigen.cmake
+++ /dev/null
@@ -1,81 +0,0 @@
-###############################################################################
-# 
-# CMake script for finding the Eigen library.
-# 
-# http://eigen.tuxfamily.org/index.php?title=Main_Page
-# 
-# Copyright (c) 2006, 2007 Montel Laurent, <montel@kde.org>
-# Copyright (c) 2008, 2009 Gael Guennebaud, <g.gael@free.fr>
-# Copyright (c) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
-# Redistribution and use is allowed according to the terms of the 2-clause BSD
-# license.
-# 
-# 
-# Input variables:
-# 
-# - Eigen_ROOT_DIR (optional): When specified, header files and libraries
-#   will be searched for in `${Eigen_ROOT_DIR}/include` and
-#   `${Eigen_ROOT_DIR}/libs` respectively, and the default CMake search order
-#   will be ignored. When unspecified, the default CMake search order is used.
-#   This variable can be specified either as a CMake or environment variable.
-#   If both are set, preference is given to the CMake variable.
-#   Use this variable for finding packages installed in a nonstandard location,
-#   or for enforcing that one of multiple package installations is picked up.
-# 
-# Cache variables (not intended to be used in CMakeLists.txt files)
-# 
-# - Eigen_INCLUDE_DIR: Absolute path to package headers.
-# 
-# 
-# Output variables:
-# 
-# - Eigen_FOUND: Boolean that indicates if the package was found
-# - Eigen_INCLUDE_DIRS: Paths to the necessary header files
-# - Eigen_VERSION: Version of Eigen library found
-# - Eigen_DEFINITIONS: Definitions to be passed on behalf of eigen
-# 
-# 
-# Example usage:
-# 
-#   # Passing the version means Eigen_FOUND will only be TRUE if a
-#   # version >= the provided version is found.
-#   find_package(Eigen 3.1.2)
-#   if(NOT Eigen_FOUND)
-#     # Error handling
-#   endif()
-#   ...
-#   add_definitions(${Eigen_DEFINITIONS})
-#   ...
-#   include_directories(${Eigen_INCLUDE_DIRS} ...)
-# 
-###############################################################################
-
-find_package(PkgConfig)
-pkg_check_modules(PC_EIGEN eigen3)
-set(EIGEN_DEFINITIONS ${PC_EIGEN_CFLAGS_OTHER})
-
-
-find_path(EIGEN_INCLUDE_DIR Eigen/Core
-    HINTS ${PC_EIGEN_INCLUDEDIR} ${PC_EIGEN_INCLUDE_DIRS}
-          "${Eigen_ROOT_DIR}" "$ENV{EIGEN_ROOT_DIR}"
-          "${EIGEN_ROOT}" "$ENV{EIGEN_ROOT}"  # Backwards Compatibility
-    PATHS "$ENV{PROGRAMFILES}/Eigen" "$ENV{PROGRAMW6432}/Eigen"
-          "$ENV{PROGRAMFILES}/Eigen 3.0.0" "$ENV{PROGRAMW6432}/Eigen 3.0.0"
-    PATH_SUFFIXES eigen3 include/eigen3 include)
-
-set(EIGEN_INCLUDE_DIRS ${EIGEN_INCLUDE_DIR})
-
-include(FindPackageHandleStandardArgs)
-find_package_handle_standard_args(Eigen DEFAULT_MSG EIGEN_INCLUDE_DIR)
-
-mark_as_advanced(EIGEN_INCLUDE_DIR)
-
-if(EIGEN_FOUND)
-  message(STATUS "Eigen found (include: ${EIGEN_INCLUDE_DIRS})")
-endif(EIGEN_FOUND)
-
-
-set(Eigen_INCLUDE_DIRS ${EIGEN_INCLUDE_DIRS})
-set(Eigen_FOUND ${EIGEN_FOUND})
-set(Eigen_VERSION ${EIGEN_VERSION})
-set(Eigen_DEFINITIONS ${EIGEN_DEFINITIONS})
diff --git a/CPU_version/svo/CMakeModules/FindG2O.cmake b/CPU_version/svo/CMakeModules/FindG2O.cmake
deleted file mode 100644
index 655600f..0000000
--- a/CPU_version/svo/CMakeModules/FindG2O.cmake
+++ /dev/null
@@ -1,113 +0,0 @@
-# Find the header files
-
-FIND_PATH(G2O_INCLUDE_DIR g2o/core/base_vertex.h
-  ${G2O_ROOT}/include
-  $ENV{G2O_ROOT}/include
-  $ENV{G2O_ROOT}
-  /usr/local/include
-  /usr/include
-  /opt/local/include
-  /sw/local/include
-  /sw/include
-  NO_DEFAULT_PATH
-  )
-
-# Macro to unify finding both the debug and release versions of the
-# libraries; this is adapted from the OpenSceneGraph FIND_LIBRARY
-# macro.
-
-MACRO(FIND_G2O_LIBRARY MYLIBRARY MYLIBRARYNAME)
-
-  FIND_LIBRARY("${MYLIBRARY}_DEBUG"
-    NAMES "g2o_${MYLIBRARYNAME}_d"
-    PATHS
-    ${G2O_ROOT}/lib/Debug
-    ${G2O_ROOT}/lib
-    $ENV{G2O_ROOT}/lib/Debug
-    $ENV{G2O_ROOT}/lib
-    NO_DEFAULT_PATH
-    )
-
-  FIND_LIBRARY("${MYLIBRARY}_DEBUG"
-    NAMES "g2o_${MYLIBRARYNAME}_d"
-    PATHS
-    ~/Library/Frameworks
-    /Library/Frameworks
-    /usr/local/lib
-    /usr/local/lib64
-    /usr/lib
-    /usr/lib64
-    /opt/local/lib
-    /sw/local/lib
-    /sw/lib
-    )
-  
-  FIND_LIBRARY(${MYLIBRARY}
-    NAMES "g2o_${MYLIBRARYNAME}"
-    PATHS
-    ${G2O_ROOT}/lib/Release
-    ${G2O_ROOT}/lib
-    $ENV{G2O_ROOT}/lib/Release
-    $ENV{G2O_ROOT}/lib
-    NO_DEFAULT_PATH
-    )
-
-  FIND_LIBRARY(${MYLIBRARY}
-    NAMES "g2o_${MYLIBRARYNAME}"
-    PATHS
-    ~/Library/Frameworks
-    /Library/Frameworks
-    /usr/local/lib
-    /usr/local/lib64
-    /usr/lib
-    /usr/lib64
-    /opt/local/lib
-    /sw/local/lib
-    /sw/lib
-    )
-  
-  IF(NOT ${MYLIBRARY}_DEBUG)
-    IF(MYLIBRARY)
-      SET(${MYLIBRARY}_DEBUG ${MYLIBRARY})
-    ENDIF(MYLIBRARY)
-  ENDIF( NOT ${MYLIBRARY}_DEBUG)
-  
-ENDMACRO(FIND_G2O_LIBRARY LIBRARY LIBRARYNAME)
-
-# Find the core elements
-FIND_G2O_LIBRARY(G2O_STUFF_LIBRARY stuff)
-FIND_G2O_LIBRARY(G2O_CORE_LIBRARY core)
-
-# Find the CLI library
-FIND_G2O_LIBRARY(G2O_CLI_LIBRARY cli)
-
-# Find the pluggable solvers
-FIND_G2O_LIBRARY(G2O_SOLVER_CHOLMOD solver_cholmod)
-FIND_G2O_LIBRARY(G2O_SOLVER_CSPARSE solver_csparse)
-FIND_G2O_LIBRARY(G2O_SOLVER_CSPARSE_EXTENSION csparse_extension)
-FIND_G2O_LIBRARY(G2O_SOLVER_DENSE solver_dense)
-FIND_G2O_LIBRARY(G2O_SOLVER_PCG solver_pcg)
-FIND_G2O_LIBRARY(G2O_SOLVER_SLAM2D_LINEAR solver_slam2d_linear)
-FIND_G2O_LIBRARY(G2O_SOLVER_STRUCTURE_ONLY solver_structure_only)
-FIND_G2O_LIBRARY(G2O_SOLVER_EIGEN solver_eigen)
-
-# Find the predefined types
-FIND_G2O_LIBRARY(G2O_TYPES_DATA types_data)
-FIND_G2O_LIBRARY(G2O_TYPES_ICP types_icp)
-FIND_G2O_LIBRARY(G2O_TYPES_SBA types_sba)
-FIND_G2O_LIBRARY(G2O_TYPES_SCLAM2D types_sclam2d)
-FIND_G2O_LIBRARY(G2O_TYPES_SIM3 types_sim3)
-FIND_G2O_LIBRARY(G2O_TYPES_SLAM2D types_slam2d)
-FIND_G2O_LIBRARY(G2O_TYPES_SLAM3D types_slam3d)
-
-# G2O solvers declared found if we found at least one solver
-SET(G2O_SOLVERS_FOUND "NO")
-IF(G2O_SOLVER_CHOLMOD OR G2O_SOLVER_CSPARSE OR G2O_SOLVER_DENSE OR G2O_SOLVER_PCG OR G2O_SOLVER_SLAM2D_LINEAR OR G2O_SOLVER_STRUCTURE_ONLY OR G2O_SOLVER_EIGEN)
-  SET(G2O_SOLVERS_FOUND "YES")
-ENDIF(G2O_SOLVER_CHOLMOD OR G2O_SOLVER_CSPARSE OR G2O_SOLVER_DENSE OR G2O_SOLVER_PCG OR G2O_SOLVER_SLAM2D_LINEAR OR G2O_SOLVER_STRUCTURE_ONLY OR G2O_SOLVER_EIGEN)
-
-# G2O itself declared found if we found the core libraries and at least one solver
-SET(G2O_FOUND "NO")
-IF(G2O_STUFF_LIBRARY AND G2O_CORE_LIBRARY AND G2O_INCLUDE_DIR AND G2O_SOLVERS_FOUND)
-  SET(G2O_FOUND "YES")
-ENDIF(G2O_STUFF_LIBRARY AND G2O_CORE_LIBRARY AND G2O_INCLUDE_DIR AND G2O_SOLVERS_FOUND)
diff --git a/CPU_version/svo/Doxyfile b/CPU_version/svo/Doxyfile
deleted file mode 100644
index b1b4256..0000000
--- a/CPU_version/svo/Doxyfile
+++ /dev/null
@@ -1,1782 +0,0 @@
-# Doxyfile 1.7.6.1
-
-# This file describes the settings to be used by the documentation system
-# doxygen (www.doxygen.org) for a project.
-#
-# All text after a hash (#) is considered a comment and will be ignored.
-# The format is:
-#       TAG = value [value, ...]
-# For lists items can also be appended using:
-#       TAG += value [value, ...]
-# Values that contain spaces should be placed between quotes (" ").
-
-#---------------------------------------------------------------------------
-# Project related configuration options
-#---------------------------------------------------------------------------
-
-# This tag specifies the encoding used for all characters in the config file
-# that follow. The default is UTF-8 which is also the encoding used for all
-# text before the first occurrence of this tag. Doxygen uses libiconv (or the
-# iconv built into libc) for the transcoding. See
-# http://www.gnu.org/software/libiconv for the list of possible encodings.
-
-DOXYFILE_ENCODING      = UTF-8
-
-# The PROJECT_NAME tag is a single word (or sequence of words) that should
-# identify the project. Note that if you do not use Doxywizard you need
-# to put quotes around the project name if it contains spaces.
-
-PROJECT_NAME           = "svo"
-
-# The PROJECT_NUMBER tag can be used to enter a project or revision number.
-# This could be handy for archiving the generated documentation or
-# if some version control system is used.
-
-PROJECT_NUMBER         =
-
-# Using the PROJECT_BRIEF tag one can provide an optional one line description
-# for a project that appears at the top of each page and should give viewer
-# a quick idea about the purpose of the project. Keep the description short.
-
-PROJECT_BRIEF          = "Semi-Direct Visual Odometry"
-
-# With the PROJECT_LOGO tag one can specify an logo or icon that is
-# included in the documentation. The maximum height of the logo should not
-# exceed 55 pixels and the maximum width should not exceed 200 pixels.
-# Doxygen will copy the logo to the output directory.
-
-PROJECT_LOGO           =
-
-# The OUTPUT_DIRECTORY tag is used to specify the (relative or absolute)
-# base path where the generated documentation will be put.
-# If a relative path is entered, it will be relative to the location
-# where doxygen was started. If left blank the current directory will be used.
-
-OUTPUT_DIRECTORY       = "doc"
-
-# If the CREATE_SUBDIRS tag is set to YES, then doxygen will create
-# 4096 sub-directories (in 2 levels) under the output directory of each output
-# format and will distribute the generated files over these directories.
-# Enabling this option can be useful when feeding doxygen a huge amount of
-# source files, where putting all generated files in the same directory would
-# otherwise cause performance problems for the file system.
-
-CREATE_SUBDIRS         = NO
-
-# The OUTPUT_LANGUAGE tag is used to specify the language in which all
-# documentation generated by doxygen is written. Doxygen will use this
-# information to generate all constant output in the proper language.
-# The default language is English, other supported languages are:
-# Afrikaans, Arabic, Brazilian, Catalan, Chinese, Chinese-Traditional,
-# Croatian, Czech, Danish, Dutch, Esperanto, Farsi, Finnish, French, German,
-# Greek, Hungarian, Italian, Japanese, Japanese-en (Japanese with English
-# messages), Korean, Korean-en, Lithuanian, Norwegian, Macedonian, Persian,
-# Polish, Portuguese, Romanian, Russian, Serbian, Serbian-Cyrillic, Slovak,
-# Slovene, Spanish, Swedish, Ukrainian, and Vietnamese.
-
-OUTPUT_LANGUAGE        = English
-
-# If the BRIEF_MEMBER_DESC tag is set to YES (the default) Doxygen will
-# include brief member descriptions after the members that are listed in
-# the file and class documentation (similar to JavaDoc).
-# Set to NO to disable this.
-
-BRIEF_MEMBER_DESC      = YES
-
-# If the REPEAT_BRIEF tag is set to YES (the default) Doxygen will prepend
-# the brief description of a member or function before the detailed description.
-# Note: if both HIDE_UNDOC_MEMBERS and BRIEF_MEMBER_DESC are set to NO, the
-# brief descriptions will be completely suppressed.
-
-REPEAT_BRIEF           = YES
-
-# This tag implements a quasi-intelligent brief description abbreviator
-# that is used to form the text in various listings. Each string
-# in this list, if found as the leading text of the brief description, will be
-# stripped from the text and the result after processing the whole list, is
-# used as the annotated text. Otherwise, the brief description is used as-is.
-# If left blank, the following values are used ("$name" is automatically
-# replaced with the name of the entity): "The $name class" "The $name widget"
-# "The $name file" "is" "provides" "specifies" "contains"
-# "represents" "a" "an" "the"
-
-ABBREVIATE_BRIEF       =
-
-# If the ALWAYS_DETAILED_SEC and REPEAT_BRIEF tags are both set to YES then
-# Doxygen will generate a detailed section even if there is only a brief
-# description.
-
-ALWAYS_DETAILED_SEC    = NO
-
-# If the INLINE_INHERITED_MEMB tag is set to YES, doxygen will show all
-# inherited members of a class in the documentation of that class as if those
-# members were ordinary class members. Constructors, destructors and assignment
-# operators of the base classes will not be shown.
-
-INLINE_INHERITED_MEMB  = NO
-
-# If the FULL_PATH_NAMES tag is set to YES then Doxygen will prepend the full
-# path before files name in the file list and in the header files. If set
-# to NO the shortest path that makes the file name unique will be used.
-
-FULL_PATH_NAMES        = YES
-
-# If the FULL_PATH_NAMES tag is set to YES then the STRIP_FROM_PATH tag
-# can be used to strip a user-defined part of the path. Stripping is
-# only done if one of the specified strings matches the left-hand part of
-# the path. The tag can be used to show relative paths in the file list.
-# If left blank the directory from which doxygen is run is used as the
-# path to strip.
-
-STRIP_FROM_PATH        =
-
-# The STRIP_FROM_INC_PATH tag can be used to strip a user-defined part of
-# the path mentioned in the documentation of a class, which tells
-# the reader which header file to include in order to use a class.
-# If left blank only the name of the header file containing the class
-# definition is used. Otherwise one should specify the include paths that
-# are normally passed to the compiler using the -I flag.
-
-STRIP_FROM_INC_PATH    =
-
-# If the SHORT_NAMES tag is set to YES, doxygen will generate much shorter
-# (but less readable) file names. This can be useful if your file system
-# doesn't support long names like on DOS, Mac, or CD-ROM.
-
-SHORT_NAMES            = NO
-
-# If the JAVADOC_AUTOBRIEF tag is set to YES then Doxygen
-# will interpret the first line (until the first dot) of a JavaDoc-style
-# comment as the brief description. If set to NO, the JavaDoc
-# comments will behave just like regular Qt-style comments
-# (thus requiring an explicit @brief command for a brief description.)
-
-JAVADOC_AUTOBRIEF      = YES
-
-# If the QT_AUTOBRIEF tag is set to YES then Doxygen will
-# interpret the first line (until the first dot) of a Qt-style
-# comment as the brief description. If set to NO, the comments
-# will behave just like regular Qt-style comments (thus requiring
-# an explicit \brief command for a brief description.)
-
-QT_AUTOBRIEF           = NO
-
-# The MULTILINE_CPP_IS_BRIEF tag can be set to YES to make Doxygen
-# treat a multi-line C++ special comment block (i.e. a block of //! or ///
-# comments) as a brief description. This used to be the default behaviour.
-# The new default is to treat a multi-line C++ comment block as a detailed
-# description. Set this tag to YES if you prefer the old behaviour instead.
-
-MULTILINE_CPP_IS_BRIEF = NO
-
-# If the INHERIT_DOCS tag is set to YES (the default) then an undocumented
-# member inherits the documentation from any documented member that it
-# re-implements.
-
-INHERIT_DOCS           = YES
-
-# If the SEPARATE_MEMBER_PAGES tag is set to YES, then doxygen will produce
-# a new page for each member. If set to NO, the documentation of a member will
-# be part of the file/class/namespace that contains it.
-
-SEPARATE_MEMBER_PAGES  = NO
-
-# The TAB_SIZE tag can be used to set the number of spaces in a tab.
-# Doxygen uses this value to replace tabs by spaces in code fragments.
-
-TAB_SIZE               = 8
-
-# This tag can be used to specify a number of aliases that acts
-# as commands in the documentation. An alias has the form "name=value".
-# For example adding "sideeffect=\par Side Effects:\n" will allow you to
-# put the command \sideeffect (or @sideeffect) in the documentation, which
-# will result in a user-defined paragraph with heading "Side Effects:".
-# You can put \n's in the value part of an alias to insert newlines.
-
-ALIASES                =
-
-# This tag can be used to specify a number of word-keyword mappings (TCL only).
-# A mapping has the form "name=value". For example adding
-# "class=itcl::class" will allow you to use the command class in the
-# itcl::class meaning.
-
-TCL_SUBST              =
-
-# Set the OPTIMIZE_OUTPUT_FOR_C tag to YES if your project consists of C
-# sources only. Doxygen will then generate output that is more tailored for C.
-# For instance, some of the names that are used will be different. The list
-# of all members will be omitted, etc.
-
-OPTIMIZE_OUTPUT_FOR_C  = NO
-
-# Set the OPTIMIZE_OUTPUT_JAVA tag to YES if your project consists of Java
-# sources only. Doxygen will then generate output that is more tailored for
-# Java. For instance, namespaces will be presented as packages, qualified
-# scopes will look different, etc.
-
-OPTIMIZE_OUTPUT_JAVA   = NO
-
-# Set the OPTIMIZE_FOR_FORTRAN tag to YES if your project consists of Fortran
-# sources only. Doxygen will then generate output that is more tailored for
-# Fortran.
-
-OPTIMIZE_FOR_FORTRAN   = NO
-
-# Set the OPTIMIZE_OUTPUT_VHDL tag to YES if your project consists of VHDL
-# sources. Doxygen will then generate output that is tailored for
-# VHDL.
-
-OPTIMIZE_OUTPUT_VHDL   = NO
-
-# Doxygen selects the parser to use depending on the extension of the files it
-# parses. With this tag you can assign which parser to use for a given extension.
-# Doxygen has a built-in mapping, but you can override or extend it using this
-# tag. The format is ext=language, where ext is a file extension, and language
-# is one of the parsers supported by doxygen: IDL, Java, Javascript, CSharp, C,
-# C++, D, PHP, Objective-C, Python, Fortran, VHDL, C, C++. For instance to make
-# doxygen treat .inc files as Fortran files (default is PHP), and .f files as C
-# (default is Fortran), use: inc=Fortran f=C. Note that for custom extensions
-# you also need to set FILE_PATTERNS otherwise the files are not read by doxygen.
-
-EXTENSION_MAPPING      =
-
-# If you use STL classes (i.e. std::string, std::vector, etc.) but do not want
-# to include (a tag file for) the STL sources as input, then you should
-# set this tag to YES in order to let doxygen match functions declarations and
-# definitions whose arguments contain STL classes (e.g. func(std::string); v.s.
-# func(std::string) {}). This also makes the inheritance and collaboration
-# diagrams that involve STL classes more complete and accurate.
-
-BUILTIN_STL_SUPPORT    = NO
-
-# If you use Microsoft's C++/CLI language, you should set this option to YES to
-# enable parsing support.
-
-CPP_CLI_SUPPORT        = NO
-
-# Set the SIP_SUPPORT tag to YES if your project consists of sip sources only.
-# Doxygen will parse them like normal C++ but will assume all classes use public
-# instead of private inheritance when no explicit protection keyword is present.
-
-SIP_SUPPORT            = NO
-
-# For Microsoft's IDL there are propget and propput attributes to indicate getter
-# and setter methods for a property. Setting this option to YES (the default)
-# will make doxygen replace the get and set methods by a property in the
-# documentation. This will only work if the methods are indeed getting or
-# setting a simple type. If this is not the case, or you want to show the
-# methods anyway, you should set this option to NO.
-
-IDL_PROPERTY_SUPPORT   = YES
-
-# If member grouping is used in the documentation and the DISTRIBUTE_GROUP_DOC
-# tag is set to YES, then doxygen will reuse the documentation of the first
-# member in the group (if any) for the other members of the group. By default
-# all members of a group must be documented explicitly.
-
-DISTRIBUTE_GROUP_DOC   = NO
-
-# Set the SUBGROUPING tag to YES (the default) to allow class member groups of
-# the same type (for instance a group of public functions) to be put as a
-# subgroup of that type (e.g. under the Public Functions section). Set it to
-# NO to prevent subgrouping. Alternatively, this can be done per class using
-# the \nosubgrouping command.
-
-SUBGROUPING            = YES
-
-# When the INLINE_GROUPED_CLASSES tag is set to YES, classes, structs and
-# unions are shown inside the group in which they are included (e.g. using
-# @ingroup) instead of on a separate page (for HTML and Man pages) or
-# section (for LaTeX and RTF).
-
-INLINE_GROUPED_CLASSES = NO
-
-# When the INLINE_SIMPLE_STRUCTS tag is set to YES, structs, classes, and
-# unions with only public data fields will be shown inline in the documentation
-# of the scope in which they are defined (i.e. file, namespace, or group
-# documentation), provided this scope is documented. If set to NO (the default),
-# structs, classes, and unions are shown on a separate page (for HTML and Man
-# pages) or section (for LaTeX and RTF).
-
-INLINE_SIMPLE_STRUCTS  = NO
-
-# When TYPEDEF_HIDES_STRUCT is enabled, a typedef of a struct, union, or enum
-# is documented as struct, union, or enum with the name of the typedef. So
-# typedef struct TypeS {} TypeT, will appear in the documentation as a struct
-# with name TypeT. When disabled the typedef will appear as a member of a file,
-# namespace, or class. And the struct will be named TypeS. This can typically
-# be useful for C code in case the coding convention dictates that all compound
-# types are typedef'ed and only the typedef is referenced, never the tag name.
-
-TYPEDEF_HIDES_STRUCT   = NO
-
-# The SYMBOL_CACHE_SIZE determines the size of the internal cache use to
-# determine which symbols to keep in memory and which to flush to disk.
-# When the cache is full, less often used symbols will be written to disk.
-# For small to medium size projects (<1000 input files) the default value is
-# probably good enough. For larger projects a too small cache size can cause
-# doxygen to be busy swapping symbols to and from disk most of the time
-# causing a significant performance penalty.
-# If the system has enough physical memory increasing the cache will improve the
-# performance by keeping more symbols in memory. Note that the value works on
-# a logarithmic scale so increasing the size by one will roughly double the
-# memory usage. The cache size is given by this formula:
-# 2^(16+SYMBOL_CACHE_SIZE). The valid range is 0..9, the default is 0,
-# corresponding to a cache size of 2^16 = 65536 symbols.
-
-SYMBOL_CACHE_SIZE      = 0
-
-# Similar to the SYMBOL_CACHE_SIZE the size of the symbol lookup cache can be
-# set using LOOKUP_CACHE_SIZE. This cache is used to resolve symbols given
-# their name and scope. Since this can be an expensive process and often the
-# same symbol appear multiple times in the code, doxygen keeps a cache of
-# pre-resolved symbols. If the cache is too small doxygen will become slower.
-# If the cache is too large, memory is wasted. The cache size is given by this
-# formula: 2^(16+LOOKUP_CACHE_SIZE). The valid range is 0..9, the default is 0,
-# corresponding to a cache size of 2^16 = 65536 symbols.
-
-LOOKUP_CACHE_SIZE      = 0
-
-#---------------------------------------------------------------------------
-# Build related configuration options
-#---------------------------------------------------------------------------
-
-# If the EXTRACT_ALL tag is set to YES doxygen will assume all entities in
-# documentation are documented, even if no documentation was available.
-# Private class members and static file members will be hidden unless
-# the EXTRACT_PRIVATE and EXTRACT_STATIC tags are set to YES
-
-EXTRACT_ALL            = YES
-
-# If the EXTRACT_PRIVATE tag is set to YES all private members of a class
-# will be included in the documentation.
-
-EXTRACT_PRIVATE        = YES
-
-# If the EXTRACT_STATIC tag is set to YES all static members of a file
-# will be included in the documentation.
-
-EXTRACT_STATIC         = YES
-
-# If the EXTRACT_LOCAL_CLASSES tag is set to YES classes (and structs)
-# defined locally in source files will be included in the documentation.
-# If set to NO only classes defined in header files are included.
-
-EXTRACT_LOCAL_CLASSES  = YES
-
-# This flag is only useful for Objective-C code. When set to YES local
-# methods, which are defined in the implementation section but not in
-# the interface are included in the documentation.
-# If set to NO (the default) only methods in the interface are included.
-
-EXTRACT_LOCAL_METHODS  = NO
-
-# If this flag is set to YES, the members of anonymous namespaces will be
-# extracted and appear in the documentation as a namespace called
-# 'anonymous_namespace{file}', where file will be replaced with the base
-# name of the file that contains the anonymous namespace. By default
-# anonymous namespaces are hidden.
-
-EXTRACT_ANON_NSPACES   = NO
-
-# If the HIDE_UNDOC_MEMBERS tag is set to YES, Doxygen will hide all
-# undocumented members of documented classes, files or namespaces.
-# If set to NO (the default) these members will be included in the
-# various overviews, but no documentation section is generated.
-# This option has no effect if EXTRACT_ALL is enabled.
-
-HIDE_UNDOC_MEMBERS     = NO
-
-# If the HIDE_UNDOC_CLASSES tag is set to YES, Doxygen will hide all
-# undocumented classes that are normally visible in the class hierarchy.
-# If set to NO (the default) these classes will be included in the various
-# overviews. This option has no effect if EXTRACT_ALL is enabled.
-
-HIDE_UNDOC_CLASSES     = NO
-
-# If the HIDE_FRIEND_COMPOUNDS tag is set to YES, Doxygen will hide all
-# friend (class|struct|union) declarations.
-# If set to NO (the default) these declarations will be included in the
-# documentation.
-
-HIDE_FRIEND_COMPOUNDS  = NO
-
-# If the HIDE_IN_BODY_DOCS tag is set to YES, Doxygen will hide any
-# documentation blocks found inside the body of a function.
-# If set to NO (the default) these blocks will be appended to the
-# function's detailed documentation block.
-
-HIDE_IN_BODY_DOCS      = NO
-
-# The INTERNAL_DOCS tag determines if documentation
-# that is typed after a \internal command is included. If the tag is set
-# to NO (the default) then the documentation will be excluded.
-# Set it to YES to include the internal documentation.
-
-INTERNAL_DOCS          = NO
-
-# If the CASE_SENSE_NAMES tag is set to NO then Doxygen will only generate
-# file names in lower-case letters. If set to YES upper-case letters are also
-# allowed. This is useful if you have classes or files whose names only differ
-# in case and if your file system supports case sensitive file names. Windows
-# and Mac users are advised to set this option to NO.
-
-CASE_SENSE_NAMES       = YES
-
-# If the HIDE_SCOPE_NAMES tag is set to NO (the default) then Doxygen
-# will show members with their full class and namespace scopes in the
-# documentation. If set to YES the scope will be hidden.
-
-HIDE_SCOPE_NAMES       = NO
-
-# If the SHOW_INCLUDE_FILES tag is set to YES (the default) then Doxygen
-# will put a list of the files that are included by a file in the documentation
-# of that file.
-
-SHOW_INCLUDE_FILES     = YES
-
-# If the FORCE_LOCAL_INCLUDES tag is set to YES then Doxygen
-# will list include files with double quotes in the documentation
-# rather than with sharp brackets.
-
-FORCE_LOCAL_INCLUDES   = NO
-
-# If the INLINE_INFO tag is set to YES (the default) then a tag [inline]
-# is inserted in the documentation for inline members.
-
-INLINE_INFO            = YES
-
-# If the SORT_MEMBER_DOCS tag is set to YES (the default) then doxygen
-# will sort the (detailed) documentation of file and class members
-# alphabetically by member name. If set to NO the members will appear in
-# declaration order.
-
-SORT_MEMBER_DOCS       = YES
-
-# If the SORT_BRIEF_DOCS tag is set to YES then doxygen will sort the
-# brief documentation of file, namespace and class members alphabetically
-# by member name. If set to NO (the default) the members will appear in
-# declaration order.
-
-SORT_BRIEF_DOCS        = NO
-
-# If the SORT_MEMBERS_CTORS_1ST tag is set to YES then doxygen
-# will sort the (brief and detailed) documentation of class members so that
-# constructors and destructors are listed first. If set to NO (the default)
-# the constructors will appear in the respective orders defined by
-# SORT_MEMBER_DOCS and SORT_BRIEF_DOCS.
-# This tag will be ignored for brief docs if SORT_BRIEF_DOCS is set to NO
-# and ignored for detailed docs if SORT_MEMBER_DOCS is set to NO.
-
-SORT_MEMBERS_CTORS_1ST = NO
-
-# If the SORT_GROUP_NAMES tag is set to YES then doxygen will sort the
-# hierarchy of group names into alphabetical order. If set to NO (the default)
-# the group names will appear in their defined order.
-
-SORT_GROUP_NAMES       = NO
-
-# If the SORT_BY_SCOPE_NAME tag is set to YES, the class list will be
-# sorted by fully-qualified names, including namespaces. If set to
-# NO (the default), the class list will be sorted only by class name,
-# not including the namespace part.
-# Note: This option is not very useful if HIDE_SCOPE_NAMES is set to YES.
-# Note: This option applies only to the class list, not to the
-# alphabetical list.
-
-SORT_BY_SCOPE_NAME     = NO
-
-# If the STRICT_PROTO_MATCHING option is enabled and doxygen fails to
-# do proper type resolution of all parameters of a function it will reject a
-# match between the prototype and the implementation of a member function even
-# if there is only one candidate or it is obvious which candidate to choose
-# by doing a simple string match. By disabling STRICT_PROTO_MATCHING doxygen
-# will still accept a match between prototype and implementation in such cases.
-
-STRICT_PROTO_MATCHING  = NO
-
-# The GENERATE_TODOLIST tag can be used to enable (YES) or
-# disable (NO) the todo list. This list is created by putting \todo
-# commands in the documentation.
-
-GENERATE_TODOLIST      = YES
-
-# The GENERATE_TESTLIST tag can be used to enable (YES) or
-# disable (NO) the test list. This list is created by putting \test
-# commands in the documentation.
-
-GENERATE_TESTLIST      = YES
-
-# The GENERATE_BUGLIST tag can be used to enable (YES) or
-# disable (NO) the bug list. This list is created by putting \bug
-# commands in the documentation.
-
-GENERATE_BUGLIST       = YES
-
-# The GENERATE_DEPRECATEDLIST tag can be used to enable (YES) or
-# disable (NO) the deprecated list. This list is created by putting
-# \deprecated commands in the documentation.
-
-GENERATE_DEPRECATEDLIST= YES
-
-# The ENABLED_SECTIONS tag can be used to enable conditional
-# documentation sections, marked by \if sectionname ... \endif.
-
-ENABLED_SECTIONS       =
-
-# The MAX_INITIALIZER_LINES tag determines the maximum number of lines
-# the initial value of a variable or macro consists of for it to appear in
-# the documentation. If the initializer consists of more lines than specified
-# here it will be hidden. Use a value of 0 to hide initializers completely.
-# The appearance of the initializer of individual variables and macros in the
-# documentation can be controlled using \showinitializer or \hideinitializer
-# command in the documentation regardless of this setting.
-
-MAX_INITIALIZER_LINES  = 30
-
-# Set the SHOW_USED_FILES tag to NO to disable the list of files generated
-# at the bottom of the documentation of classes and structs. If set to YES the
-# list will mention the files that were used to generate the documentation.
-
-SHOW_USED_FILES        = YES
-
-# If the sources in your project are distributed over multiple directories
-# then setting the SHOW_DIRECTORIES tag to YES will show the directory hierarchy
-# in the documentation. The default is NO.
-
-SHOW_DIRECTORIES       = NO
-
-# Set the SHOW_FILES tag to NO to disable the generation of the Files page.
-# This will remove the Files entry from the Quick Index and from the
-# Folder Tree View (if specified). The default is YES.
-
-SHOW_FILES             = YES
-
-# Set the SHOW_NAMESPACES tag to NO to disable the generation of the
-# Namespaces page.
-# This will remove the Namespaces entry from the Quick Index
-# and from the Folder Tree View (if specified). The default is YES.
-
-SHOW_NAMESPACES        = YES
-
-# The FILE_VERSION_FILTER tag can be used to specify a program or script that
-# doxygen should invoke to get the current version for each file (typically from
-# the version control system). Doxygen will invoke the program by executing (via
-# popen()) the command <command> <input-file>, where <command> is the value of
-# the FILE_VERSION_FILTER tag, and <input-file> is the name of an input file
-# provided by doxygen. Whatever the program writes to standard output
-# is used as the file version. See the manual for examples.
-
-FILE_VERSION_FILTER    =
-
-# The LAYOUT_FILE tag can be used to specify a layout file which will be parsed
-# by doxygen. The layout file controls the global structure of the generated
-# output files in an output format independent way. The create the layout file
-# that represents doxygen's defaults, run doxygen with the -l option.
-# You can optionally specify a file name after the option, if omitted
-# DoxygenLayout.xml will be used as the name of the layout file.
-
-LAYOUT_FILE            =
-
-# The CITE_BIB_FILES tag can be used to specify one or more bib files
-# containing the references data. This must be a list of .bib files. The
-# .bib extension is automatically appended if omitted. Using this command
-# requires the bibtex tool to be installed. See also
-# http://en.wikipedia.org/wiki/BibTeX for more info. For LaTeX the style
-# of the bibliography can be controlled using LATEX_BIB_STYLE. To use this
-# feature you need bibtex and perl available in the search path.
-
-CITE_BIB_FILES         =
-
-#---------------------------------------------------------------------------
-# configuration options related to warning and progress messages
-#---------------------------------------------------------------------------
-
-# The QUIET tag can be used to turn on/off the messages that are generated
-# by doxygen. Possible values are YES and NO. If left blank NO is used.
-
-QUIET                  = NO
-
-# The WARNINGS tag can be used to turn on/off the warning messages that are
-# generated by doxygen. Possible values are YES and NO. If left blank
-# NO is used.
-
-WARNINGS               = YES
-
-# If WARN_IF_UNDOCUMENTED is set to YES, then doxygen will generate warnings
-# for undocumented members. If EXTRACT_ALL is set to YES then this flag will
-# automatically be disabled.
-
-WARN_IF_UNDOCUMENTED   = YES
-
-# If WARN_IF_DOC_ERROR is set to YES, doxygen will generate warnings for
-# potential errors in the documentation, such as not documenting some
-# parameters in a documented function, or documenting parameters that
-# don't exist or using markup commands wrongly.
-
-WARN_IF_DOC_ERROR      = YES
-
-# The WARN_NO_PARAMDOC option can be enabled to get warnings for
-# functions that are documented, but have no documentation for their parameters
-# or return value. If set to NO (the default) doxygen will only warn about
-# wrong or incomplete parameter documentation, but not about the absence of
-# documentation.
-
-WARN_NO_PARAMDOC       = NO
-
-# The WARN_FORMAT tag determines the format of the warning messages that
-# doxygen can produce. The string should contain the $file, $line, and $text
-# tags, which will be replaced by the file and line number from which the
-# warning originated and the warning text. Optionally the format may contain
-# $version, which will be replaced by the version of the file (if it could
-# be obtained via FILE_VERSION_FILTER)
-
-WARN_FORMAT            = "$file:$line: $text"
-
-# The WARN_LOGFILE tag can be used to specify a file to which warning
-# and error messages should be written. If left blank the output is written
-# to stderr.
-
-WARN_LOGFILE           =
-
-#---------------------------------------------------------------------------
-# configuration options related to the input files
-#---------------------------------------------------------------------------
-
-# The INPUT tag can be used to specify the files and/or directories that contain
-# documented source files. You may enter file names like "myfile.cpp" or
-# directories like "/usr/src/myproject". Separate the files or directories
-# with spaces.
-
-INPUT                  = "src", "include/svo"
-
-# This tag can be used to specify the character encoding of the source files
-# that doxygen parses. Internally doxygen uses the UTF-8 encoding, which is
-# also the default input encoding. Doxygen uses libiconv (or the iconv built
-# into libc) for the transcoding. See http://www.gnu.org/software/libiconv for
-# the list of possible encodings.
-
-INPUT_ENCODING         = UTF-8
-
-# If the value of the INPUT tag contains directories, you can use the
-# FILE_PATTERNS tag to specify one or more wildcard pattern (like *.cpp
-# and *.h) to filter out the source-files in the directories. If left
-# blank the following patterns are tested:
-# *.c *.cc *.cxx *.cpp *.c++ *.d *.java *.ii *.ixx *.ipp *.i++ *.inl *.h *.hh
-# *.hxx *.hpp *.h++ *.idl *.odl *.cs *.php *.php3 *.inc *.m *.mm *.dox *.py
-# *.f90 *.f *.for *.vhd *.vhdl
-
-FILE_PATTERNS          =
-
-# The RECURSIVE tag can be used to turn specify whether or not subdirectories
-# should be searched for input files as well. Possible values are YES and NO.
-# If left blank NO is used.
-
-RECURSIVE              = NO
-
-# The EXCLUDE tag can be used to specify files and/or directories that should be
-# excluded from the INPUT source files. This way you can easily exclude a
-# subdirectory from a directory tree whose root is specified with the INPUT tag.
-# Note that relative paths are relative to the directory from which doxygen is
-# run.
-
-EXCLUDE                =
-
-# The EXCLUDE_SYMLINKS tag can be used to select whether or not files or
-# directories that are symbolic links (a Unix file system feature) are excluded
-# from the input.
-
-EXCLUDE_SYMLINKS       = NO
-
-# If the value of the INPUT tag contains directories, you can use the
-# EXCLUDE_PATTERNS tag to specify one or more wildcard patterns to exclude
-# certain files from those directories. Note that the wildcards are matched
-# against the file with absolute path, so to exclude all test directories
-# for example use the pattern */test/*
-
-EXCLUDE_PATTERNS       =
-
-# The EXCLUDE_SYMBOLS tag can be used to specify one or more symbol names
-# (namespaces, classes, functions, etc.) that should be excluded from the
-# output. The symbol name can be a fully qualified name, a word, or if the
-# wildcard * is used, a substring. Examples: ANamespace, AClass,
-# AClass::ANamespace, ANamespace::*Test
-
-EXCLUDE_SYMBOLS        = g2o
-EXCLUDE_SYMBOLS        += vk
-
-# The EXAMPLE_PATH tag can be used to specify one or more files or
-# directories that contain example code fragments that are included (see
-# the \include command).
-
-EXAMPLE_PATH           =
-
-# If the value of the EXAMPLE_PATH tag contains directories, you can use the
-# EXAMPLE_PATTERNS tag to specify one or more wildcard pattern (like *.cpp
-# and *.h) to filter out the source-files in the directories. If left
-# blank all files are included.
-
-EXAMPLE_PATTERNS       =
-
-# If the EXAMPLE_RECURSIVE tag is set to YES then subdirectories will be
-# searched for input files to be used with the \include or \dontinclude
-# commands irrespective of the value of the RECURSIVE tag.
-# Possible values are YES and NO. If left blank NO is used.
-
-EXAMPLE_RECURSIVE      = NO
-
-# The IMAGE_PATH tag can be used to specify one or more files or
-# directories that contain image that are included in the documentation (see
-# the \image command).
-
-IMAGE_PATH             =
-
-# The INPUT_FILTER tag can be used to specify a program that doxygen should
-# invoke to filter for each input file. Doxygen will invoke the filter program
-# by executing (via popen()) the command <filter> <input-file>, where <filter>
-# is the value of the INPUT_FILTER tag, and <input-file> is the name of an
-# input file. Doxygen will then use the output that the filter program writes
-# to standard output.
-# If FILTER_PATTERNS is specified, this tag will be
-# ignored.
-
-INPUT_FILTER           =
-
-# The FILTER_PATTERNS tag can be used to specify filters on a per file pattern
-# basis.
-# Doxygen will compare the file name with each pattern and apply the
-# filter if there is a match.
-# The filters are a list of the form:
-# pattern=filter (like *.cpp=my_cpp_filter). See INPUT_FILTER for further
-# info on how filters are used. If FILTER_PATTERNS is empty or if
-# non of the patterns match the file name, INPUT_FILTER is applied.
-
-FILTER_PATTERNS        =
-
-# If the FILTER_SOURCE_FILES tag is set to YES, the input filter (if set using
-# INPUT_FILTER) will be used to filter the input files when producing source
-# files to browse (i.e. when SOURCE_BROWSER is set to YES).
-
-FILTER_SOURCE_FILES    = NO
-
-# The FILTER_SOURCE_PATTERNS tag can be used to specify source filters per file
-# pattern. A pattern will override the setting for FILTER_PATTERN (if any)
-# and it is also possible to disable source filtering for a specific pattern
-# using *.ext= (so without naming a filter). This option only has effect when
-# FILTER_SOURCE_FILES is enabled.
-
-FILTER_SOURCE_PATTERNS =
-
-#---------------------------------------------------------------------------
-# configuration options related to source browsing
-#---------------------------------------------------------------------------
-
-# If the SOURCE_BROWSER tag is set to YES then a list of source files will
-# be generated. Documented entities will be cross-referenced with these sources.
-# Note: To get rid of all source code in the generated output, make sure also
-# VERBATIM_HEADERS is set to NO.
-
-SOURCE_BROWSER         = NO
-
-# Setting the INLINE_SOURCES tag to YES will include the body
-# of functions and classes directly in the documentation.
-
-INLINE_SOURCES         = NO
-
-# Setting the STRIP_CODE_COMMENTS tag to YES (the default) will instruct
-# doxygen to hide any special comment blocks from generated source code
-# fragments. Normal C and C++ comments will always remain visible.
-
-STRIP_CODE_COMMENTS    = YES
-
-# If the REFERENCED_BY_RELATION tag is set to YES
-# then for each documented function all documented
-# functions referencing it will be listed.
-
-REFERENCED_BY_RELATION = NO
-
-# If the REFERENCES_RELATION tag is set to YES
-# then for each documented function all documented entities
-# called/used by that function will be listed.
-
-REFERENCES_RELATION    = NO
-
-# If the REFERENCES_LINK_SOURCE tag is set to YES (the default)
-# and SOURCE_BROWSER tag is set to YES, then the hyperlinks from
-# functions in REFERENCES_RELATION and REFERENCED_BY_RELATION lists will
-# link to the source code.
-# Otherwise they will link to the documentation.
-
-REFERENCES_LINK_SOURCE = YES
-
-# If the USE_HTAGS tag is set to YES then the references to source code
-# will point to the HTML generated by the htags(1) tool instead of doxygen
-# built-in source browser. The htags tool is part of GNU's global source
-# tagging system (see http://www.gnu.org/software/global/global.html). You
-# will need version 4.8.6 or higher.
-
-USE_HTAGS              = NO
-
-# If the VERBATIM_HEADERS tag is set to YES (the default) then Doxygen
-# will generate a verbatim copy of the header file for each class for
-# which an include is specified. Set to NO to disable this.
-
-VERBATIM_HEADERS       = YES
-
-#---------------------------------------------------------------------------
-# configuration options related to the alphabetical class index
-#---------------------------------------------------------------------------
-
-# If the ALPHABETICAL_INDEX tag is set to YES, an alphabetical index
-# of all compounds will be generated. Enable this if the project
-# contains a lot of classes, structs, unions or interfaces.
-
-ALPHABETICAL_INDEX     = YES
-
-# If the alphabetical index is enabled (see ALPHABETICAL_INDEX) then
-# the COLS_IN_ALPHA_INDEX tag can be used to specify the number of columns
-# in which this list will be split (can be a number in the range [1..20])
-
-COLS_IN_ALPHA_INDEX    = 5
-
-# In case all classes in a project start with a common prefix, all
-# classes will be put under the same header in the alphabetical index.
-# The IGNORE_PREFIX tag can be used to specify one or more prefixes that
-# should be ignored while generating the index headers.
-
-IGNORE_PREFIX          =
-
-#---------------------------------------------------------------------------
-# configuration options related to the HTML output
-#---------------------------------------------------------------------------
-
-# If the GENERATE_HTML tag is set to YES (the default) Doxygen will
-# generate HTML output.
-
-GENERATE_HTML          = YES
-
-# The HTML_OUTPUT tag is used to specify where the HTML docs will be put.
-# If a relative path is entered the value of OUTPUT_DIRECTORY will be
-# put in front of it. If left blank `html' will be used as the default path.
-
-HTML_OUTPUT            = html
-
-# The HTML_FILE_EXTENSION tag can be used to specify the file extension for
-# each generated HTML page (for example: .htm,.php,.asp). If it is left blank
-# doxygen will generate files with .html extension.
-
-HTML_FILE_EXTENSION    = .html
-
-# The HTML_HEADER tag can be used to specify a personal HTML header for
-# each generated HTML page. If it is left blank doxygen will generate a
-# standard header. Note that when using a custom header you are responsible
-#  for the proper inclusion of any scripts and style sheets that doxygen
-# needs, which is dependent on the configuration options used.
-# It is advised to generate a default header using "doxygen -w html
-# header.html footer.html stylesheet.css YourConfigFile" and then modify
-# that header. Note that the header is subject to change so you typically
-# have to redo this when upgrading to a newer version of doxygen or when
-# changing the value of configuration settings such as GENERATE_TREEVIEW!
-
-HTML_HEADER            =
-
-# The HTML_FOOTER tag can be used to specify a personal HTML footer for
-# each generated HTML page. If it is left blank doxygen will generate a
-# standard footer.
-
-HTML_FOOTER            =
-
-# The HTML_STYLESHEET tag can be used to specify a user-defined cascading
-# style sheet that is used by each HTML page. It can be used to
-# fine-tune the look of the HTML output. If the tag is left blank doxygen
-# will generate a default style sheet. Note that doxygen will try to copy
-# the style sheet file to the HTML output directory, so don't put your own
-# style sheet in the HTML output directory as well, or it will be erased!
-
-HTML_STYLESHEET        =
-
-# The HTML_EXTRA_FILES tag can be used to specify one or more extra images or
-# other source files which should be copied to the HTML output directory. Note
-# that these files will be copied to the base HTML output directory. Use the
-# $relpath$ marker in the HTML_HEADER and/or HTML_FOOTER files to load these
-# files. In the HTML_STYLESHEET file, use the file name only. Also note that
-# the files will be copied as-is; there are no commands or markers available.
-
-HTML_EXTRA_FILES       =
-
-# The HTML_COLORSTYLE_HUE tag controls the color of the HTML output.
-# Doxygen will adjust the colors in the style sheet and background images
-# according to this color. Hue is specified as an angle on a colorwheel,
-# see http://en.wikipedia.org/wiki/Hue for more information.
-# For instance the value 0 represents red, 60 is yellow, 120 is green,
-# 180 is cyan, 240 is blue, 300 purple, and 360 is red again.
-# The allowed range is 0 to 359.
-
-HTML_COLORSTYLE_HUE    = 220
-
-# The HTML_COLORSTYLE_SAT tag controls the purity (or saturation) of
-# the colors in the HTML output. For a value of 0 the output will use
-# grayscales only. A value of 255 will produce the most vivid colors.
-
-HTML_COLORSTYLE_SAT    = 100
-
-# The HTML_COLORSTYLE_GAMMA tag controls the gamma correction applied to
-# the luminance component of the colors in the HTML output. Values below
-# 100 gradually make the output lighter, whereas values above 100 make
-# the output darker. The value divided by 100 is the actual gamma applied,
-# so 80 represents a gamma of 0.8, The value 220 represents a gamma of 2.2,
-# and 100 does not change the gamma.
-
-HTML_COLORSTYLE_GAMMA  = 80
-
-# If the HTML_TIMESTAMP tag is set to YES then the footer of each generated HTML
-# page will contain the date and time when the page was generated. Setting
-# this to NO can help when comparing the output of multiple runs.
-
-HTML_TIMESTAMP         = YES
-
-# If the HTML_ALIGN_MEMBERS tag is set to YES, the members of classes,
-# files or namespaces will be aligned in HTML using tables. If set to
-# NO a bullet list will be used.
-
-HTML_ALIGN_MEMBERS     = YES
-
-# If the HTML_DYNAMIC_SECTIONS tag is set to YES then the generated HTML
-# documentation will contain sections that can be hidden and shown after the
-# page has loaded. For this to work a browser that supports
-# JavaScript and DHTML is required (for instance Mozilla 1.0+, Firefox
-# Netscape 6.0+, Internet explorer 5.0+, Konqueror, or Safari).
-
-HTML_DYNAMIC_SECTIONS  = NO
-
-# If the GENERATE_DOCSET tag is set to YES, additional index files
-# will be generated that can be used as input for Apple's Xcode 3
-# integrated development environment, introduced with OSX 10.5 (Leopard).
-# To create a documentation set, doxygen will generate a Makefile in the
-# HTML output directory. Running make will produce the docset in that
-# directory and running "make install" will install the docset in
-# ~/Library/Developer/Shared/Documentation/DocSets so that Xcode will find
-# it at startup.
-# See http://developer.apple.com/tools/creatingdocsetswithdoxygen.html
-# for more information.
-
-GENERATE_DOCSET        = NO
-
-# When GENERATE_DOCSET tag is set to YES, this tag determines the name of the
-# feed. A documentation feed provides an umbrella under which multiple
-# documentation sets from a single provider (such as a company or product suite)
-# can be grouped.
-
-DOCSET_FEEDNAME        = "Doxygen generated docs"
-
-# When GENERATE_DOCSET tag is set to YES, this tag specifies a string that
-# should uniquely identify the documentation set bundle. This should be a
-# reverse domain-name style string, e.g. com.mycompany.MyDocSet. Doxygen
-# will append .docset to the name.
-
-DOCSET_BUNDLE_ID       = org.doxygen.Project
-
-# When GENERATE_PUBLISHER_ID tag specifies a string that should uniquely identify
-# the documentation publisher. This should be a reverse domain-name style
-# string, e.g. com.mycompany.MyDocSet.documentation.
-
-DOCSET_PUBLISHER_ID    = org.doxygen.Publisher
-
-# The GENERATE_PUBLISHER_NAME tag identifies the documentation publisher.
-
-DOCSET_PUBLISHER_NAME  = Publisher
-
-# If the GENERATE_HTMLHELP tag is set to YES, additional index files
-# will be generated that can be used as input for tools like the
-# Microsoft HTML help workshop to generate a compiled HTML help file (.chm)
-# of the generated HTML documentation.
-
-GENERATE_HTMLHELP      = NO
-
-# If the GENERATE_HTMLHELP tag is set to YES, the CHM_FILE tag can
-# be used to specify the file name of the resulting .chm file. You
-# can add a path in front of the file if the result should not be
-# written to the html output directory.
-
-CHM_FILE               =
-
-# If the GENERATE_HTMLHELP tag is set to YES, the HHC_LOCATION tag can
-# be used to specify the location (absolute path including file name) of
-# the HTML help compiler (hhc.exe). If non-empty doxygen will try to run
-# the HTML help compiler on the generated index.hhp.
-
-HHC_LOCATION           =
-
-# If the GENERATE_HTMLHELP tag is set to YES, the GENERATE_CHI flag
-# controls if a separate .chi index file is generated (YES) or that
-# it should be included in the master .chm file (NO).
-
-GENERATE_CHI           = NO
-
-# If the GENERATE_HTMLHELP tag is set to YES, the CHM_INDEX_ENCODING
-# is used to encode HtmlHelp index (hhk), content (hhc) and project file
-# content.
-
-CHM_INDEX_ENCODING     =
-
-# If the GENERATE_HTMLHELP tag is set to YES, the BINARY_TOC flag
-# controls whether a binary table of contents is generated (YES) or a
-# normal table of contents (NO) in the .chm file.
-
-BINARY_TOC             = NO
-
-# The TOC_EXPAND flag can be set to YES to add extra items for group members
-# to the contents of the HTML help documentation and to the tree view.
-
-TOC_EXPAND             = NO
-
-# If the GENERATE_QHP tag is set to YES and both QHP_NAMESPACE and
-# QHP_VIRTUAL_FOLDER are set, an additional index file will be generated
-# that can be used as input for Qt's qhelpgenerator to generate a
-# Qt Compressed Help (.qch) of the generated HTML documentation.
-
-GENERATE_QHP           = NO
-
-# If the QHG_LOCATION tag is specified, the QCH_FILE tag can
-# be used to specify the file name of the resulting .qch file.
-# The path specified is relative to the HTML output folder.
-
-QCH_FILE               =
-
-# The QHP_NAMESPACE tag specifies the namespace to use when generating
-# Qt Help Project output. For more information please see
-# http://doc.trolltech.com/qthelpproject.html#namespace
-
-QHP_NAMESPACE          = org.doxygen.Project
-
-# The QHP_VIRTUAL_FOLDER tag specifies the namespace to use when generating
-# Qt Help Project output. For more information please see
-# http://doc.trolltech.com/qthelpproject.html#virtual-folders
-
-QHP_VIRTUAL_FOLDER     = doc
-
-# If QHP_CUST_FILTER_NAME is set, it specifies the name of a custom filter to
-# add. For more information please see
-# http://doc.trolltech.com/qthelpproject.html#custom-filters
-
-QHP_CUST_FILTER_NAME   =
-
-# The QHP_CUST_FILT_ATTRS tag specifies the list of the attributes of the
-# custom filter to add. For more information please see
-# <a href="http://doc.trolltech.com/qthelpproject.html#custom-filters">
-# Qt Help Project / Custom Filters</a>.
-
-QHP_CUST_FILTER_ATTRS  =
-
-# The QHP_SECT_FILTER_ATTRS tag specifies the list of the attributes this
-# project's
-# filter section matches.
-# <a href="http://doc.trolltech.com/qthelpproject.html#filter-attributes">
-# Qt Help Project / Filter Attributes</a>.
-
-QHP_SECT_FILTER_ATTRS  =
-
-# If the GENERATE_QHP tag is set to YES, the QHG_LOCATION tag can
-# be used to specify the location of Qt's qhelpgenerator.
-# If non-empty doxygen will try to run qhelpgenerator on the generated
-# .qhp file.
-
-QHG_LOCATION           =
-
-# If the GENERATE_ECLIPSEHELP tag is set to YES, additional index files
-#  will be generated, which together with the HTML files, form an Eclipse help
-# plugin. To install this plugin and make it available under the help contents
-# menu in Eclipse, the contents of the directory containing the HTML and XML
-# files needs to be copied into the plugins directory of eclipse. The name of
-# the directory within the plugins directory should be the same as
-# the ECLIPSE_DOC_ID value. After copying Eclipse needs to be restarted before
-# the help appears.
-
-GENERATE_ECLIPSEHELP   = NO
-
-# A unique identifier for the eclipse help plugin. When installing the plugin
-# the directory name containing the HTML and XML files should also have
-# this name.
-
-ECLIPSE_DOC_ID         = org.doxygen.Project
-
-# The DISABLE_INDEX tag can be used to turn on/off the condensed index (tabs)
-# at top of each HTML page. The value NO (the default) enables the index and
-# the value YES disables it. Since the tabs have the same information as the
-# navigation tree you can set this option to NO if you already set
-# GENERATE_TREEVIEW to YES.
-
-DISABLE_INDEX          = NO
-
-# The GENERATE_TREEVIEW tag is used to specify whether a tree-like index
-# structure should be generated to display hierarchical information.
-# If the tag value is set to YES, a side panel will be generated
-# containing a tree-like index structure (just like the one that
-# is generated for HTML Help). For this to work a browser that supports
-# JavaScript, DHTML, CSS and frames is required (i.e. any modern browser).
-# Windows users are probably better off using the HTML help feature.
-# Since the tree basically has the same information as the tab index you
-# could consider to set DISABLE_INDEX to NO when enabling this option.
-
-GENERATE_TREEVIEW      = NO
-
-# The ENUM_VALUES_PER_LINE tag can be used to set the number of enum values
-# (range [0,1..20]) that doxygen will group on one line in the generated HTML
-# documentation. Note that a value of 0 will completely suppress the enum
-# values from appearing in the overview section.
-
-ENUM_VALUES_PER_LINE   = 4
-
-# By enabling USE_INLINE_TREES, doxygen will generate the Groups, Directories,
-# and Class Hierarchy pages using a tree view instead of an ordered list.
-
-USE_INLINE_TREES       = NO
-
-# If the treeview is enabled (see GENERATE_TREEVIEW) then this tag can be
-# used to set the initial width (in pixels) of the frame in which the tree
-# is shown.
-
-TREEVIEW_WIDTH         = 250
-
-# When the EXT_LINKS_IN_WINDOW option is set to YES doxygen will open
-# links to external symbols imported via tag files in a separate window.
-
-EXT_LINKS_IN_WINDOW    = NO
-
-# Use this tag to change the font size of Latex formulas included
-# as images in the HTML documentation. The default is 10. Note that
-# when you change the font size after a successful doxygen run you need
-# to manually remove any form_*.png images from the HTML output directory
-# to force them to be regenerated.
-
-FORMULA_FONTSIZE       = 10
-
-# Use the FORMULA_TRANPARENT tag to determine whether or not the images
-# generated for formulas are transparent PNGs. Transparent PNGs are
-# not supported properly for IE 6.0, but are supported on all modern browsers.
-# Note that when changing this option you need to delete any form_*.png files
-# in the HTML output before the changes have effect.
-
-FORMULA_TRANSPARENT    = YES
-
-# Enable the USE_MATHJAX option to render LaTeX formulas using MathJax
-# (see http://www.mathjax.org) which uses client side Javascript for the
-# rendering instead of using prerendered bitmaps. Use this if you do not
-# have LaTeX installed or if you want to formulas look prettier in the HTML
-# output. When enabled you also need to install MathJax separately and
-# configure the path to it using the MATHJAX_RELPATH option.
-
-USE_MATHJAX            = NO
-
-# When MathJax is enabled you need to specify the location relative to the
-# HTML output directory using the MATHJAX_RELPATH option. The destination
-# directory should contain the MathJax.js script. For instance, if the mathjax
-# directory is located at the same level as the HTML output directory, then
-# MATHJAX_RELPATH should be ../mathjax. The default value points to the
-# mathjax.org site, so you can quickly see the result without installing
-# MathJax, but it is strongly recommended to install a local copy of MathJax
-# before deployment.
-
-MATHJAX_RELPATH        = http://www.mathjax.org/mathjax
-
-# The MATHJAX_EXTENSIONS tag can be used to specify one or MathJax extension
-# names that should be enabled during MathJax rendering.
-
-MATHJAX_EXTENSIONS     =
-
-# When the SEARCHENGINE tag is enabled doxygen will generate a search box
-# for the HTML output. The underlying search engine uses javascript
-# and DHTML and should work on any modern browser. Note that when using
-# HTML help (GENERATE_HTMLHELP), Qt help (GENERATE_QHP), or docsets
-# (GENERATE_DOCSET) there is already a search function so this one should
-# typically be disabled. For large projects the javascript based search engine
-# can be slow, then enabling SERVER_BASED_SEARCH may provide a better solution.
-
-SEARCHENGINE           = YES
-
-# When the SERVER_BASED_SEARCH tag is enabled the search engine will be
-# implemented using a PHP enabled web server instead of at the web client
-# using Javascript. Doxygen will generate the search PHP script and index
-# file to put on the web server. The advantage of the server
-# based approach is that it scales better to large projects and allows
-# full text search. The disadvantages are that it is more difficult to setup
-# and does not have live searching capabilities.
-
-SERVER_BASED_SEARCH    = NO
-
-#---------------------------------------------------------------------------
-# configuration options related to the LaTeX output
-#---------------------------------------------------------------------------
-
-# If the GENERATE_LATEX tag is set to YES (the default) Doxygen will
-# generate Latex output.
-
-GENERATE_LATEX         = YES
-
-# The LATEX_OUTPUT tag is used to specify where the LaTeX docs will be put.
-# If a relative path is entered the value of OUTPUT_DIRECTORY will be
-# put in front of it. If left blank `latex' will be used as the default path.
-
-LATEX_OUTPUT           = latex
-
-# The LATEX_CMD_NAME tag can be used to specify the LaTeX command name to be
-# invoked. If left blank `latex' will be used as the default command name.
-# Note that when enabling USE_PDFLATEX this option is only used for
-# generating bitmaps for formulas in the HTML output, but not in the
-# Makefile that is written to the output directory.
-
-LATEX_CMD_NAME         = latex
-
-# The MAKEINDEX_CMD_NAME tag can be used to specify the command name to
-# generate index for LaTeX. If left blank `makeindex' will be used as the
-# default command name.
-
-MAKEINDEX_CMD_NAME     = makeindex
-
-# If the COMPACT_LATEX tag is set to YES Doxygen generates more compact
-# LaTeX documents. This may be useful for small projects and may help to
-# save some trees in general.
-
-COMPACT_LATEX          = NO
-
-# The PAPER_TYPE tag can be used to set the paper type that is used
-# by the printer. Possible values are: a4, letter, legal and
-# executive. If left blank a4wide will be used.
-
-PAPER_TYPE             = a4
-
-# The EXTRA_PACKAGES tag can be to specify one or more names of LaTeX
-# packages that should be included in the LaTeX output.
-
-EXTRA_PACKAGES         =
-
-# The LATEX_HEADER tag can be used to specify a personal LaTeX header for
-# the generated latex document. The header should contain everything until
-# the first chapter. If it is left blank doxygen will generate a
-# standard header. Notice: only use this tag if you know what you are doing!
-
-LATEX_HEADER           =
-
-# The LATEX_FOOTER tag can be used to specify a personal LaTeX footer for
-# the generated latex document. The footer should contain everything after
-# the last chapter. If it is left blank doxygen will generate a
-# standard footer. Notice: only use this tag if you know what you are doing!
-
-LATEX_FOOTER           =
-
-# If the PDF_HYPERLINKS tag is set to YES, the LaTeX that is generated
-# is prepared for conversion to pdf (using ps2pdf). The pdf file will
-# contain links (just like the HTML output) instead of page references
-# This makes the output suitable for online browsing using a pdf viewer.
-
-PDF_HYPERLINKS         = YES
-
-# If the USE_PDFLATEX tag is set to YES, pdflatex will be used instead of
-# plain latex in the generated Makefile. Set this option to YES to get a
-# higher quality PDF documentation.
-
-USE_PDFLATEX           = YES
-
-# If the LATEX_BATCHMODE tag is set to YES, doxygen will add the \\batchmode.
-# command to the generated LaTeX files. This will instruct LaTeX to keep
-# running if errors occur, instead of asking the user for help.
-# This option is also used when generating formulas in HTML.
-
-LATEX_BATCHMODE        = NO
-
-# If LATEX_HIDE_INDICES is set to YES then doxygen will not
-# include the index chapters (such as File Index, Compound Index, etc.)
-# in the output.
-
-LATEX_HIDE_INDICES     = NO
-
-# If LATEX_SOURCE_CODE is set to YES then doxygen will include
-# source code with syntax highlighting in the LaTeX output.
-# Note that which sources are shown also depends on other settings
-# such as SOURCE_BROWSER.
-
-LATEX_SOURCE_CODE      = NO
-
-# The LATEX_BIB_STYLE tag can be used to specify the style to use for the
-# bibliography, e.g. plainnat, or ieeetr. The default style is "plain". See
-# http://en.wikipedia.org/wiki/BibTeX for more info.
-
-LATEX_BIB_STYLE        = plain
-
-#---------------------------------------------------------------------------
-# configuration options related to the RTF output
-#---------------------------------------------------------------------------
-
-# If the GENERATE_RTF tag is set to YES Doxygen will generate RTF output
-# The RTF output is optimized for Word 97 and may not look very pretty with
-# other RTF readers or editors.
-
-GENERATE_RTF           = NO
-
-# The RTF_OUTPUT tag is used to specify where the RTF docs will be put.
-# If a relative path is entered the value of OUTPUT_DIRECTORY will be
-# put in front of it. If left blank `rtf' will be used as the default path.
-
-RTF_OUTPUT             = rtf
-
-# If the COMPACT_RTF tag is set to YES Doxygen generates more compact
-# RTF documents. This may be useful for small projects and may help to
-# save some trees in general.
-
-COMPACT_RTF            = NO
-
-# If the RTF_HYPERLINKS tag is set to YES, the RTF that is generated
-# will contain hyperlink fields. The RTF file will
-# contain links (just like the HTML output) instead of page references.
-# This makes the output suitable for online browsing using WORD or other
-# programs which support those fields.
-# Note: wordpad (write) and others do not support links.
-
-RTF_HYPERLINKS         = NO
-
-# Load style sheet definitions from file. Syntax is similar to doxygen's
-# config file, i.e. a series of assignments. You only have to provide
-# replacements, missing definitions are set to their default value.
-
-RTF_STYLESHEET_FILE    =
-
-# Set optional variables used in the generation of an rtf document.
-# Syntax is similar to doxygen's config file.
-
-RTF_EXTENSIONS_FILE    =
-
-#---------------------------------------------------------------------------
-# configuration options related to the man page output
-#---------------------------------------------------------------------------
-
-# If the GENERATE_MAN tag is set to YES (the default) Doxygen will
-# generate man pages
-
-GENERATE_MAN           = NO
-
-# The MAN_OUTPUT tag is used to specify where the man pages will be put.
-# If a relative path is entered the value of OUTPUT_DIRECTORY will be
-# put in front of it. If left blank `man' will be used as the default path.
-
-MAN_OUTPUT             = man
-
-# The MAN_EXTENSION tag determines the extension that is added to
-# the generated man pages (default is the subroutine's section .3)
-
-MAN_EXTENSION          = .3
-
-# If the MAN_LINKS tag is set to YES and Doxygen generates man output,
-# then it will generate one additional man file for each entity
-# documented in the real man page(s). These additional files
-# only source the real man page, but without them the man command
-# would be unable to find the correct page. The default is NO.
-
-MAN_LINKS              = NO
-
-#---------------------------------------------------------------------------
-# configuration options related to the XML output
-#---------------------------------------------------------------------------
-
-# If the GENERATE_XML tag is set to YES Doxygen will
-# generate an XML file that captures the structure of
-# the code including all documentation.
-
-GENERATE_XML           = NO
-
-# The XML_OUTPUT tag is used to specify where the XML pages will be put.
-# If a relative path is entered the value of OUTPUT_DIRECTORY will be
-# put in front of it. If left blank `xml' will be used as the default path.
-
-XML_OUTPUT             = xml
-
-# The XML_SCHEMA tag can be used to specify an XML schema,
-# which can be used by a validating XML parser to check the
-# syntax of the XML files.
-
-XML_SCHEMA             =
-
-# The XML_DTD tag can be used to specify an XML DTD,
-# which can be used by a validating XML parser to check the
-# syntax of the XML files.
-
-XML_DTD                =
-
-# If the XML_PROGRAMLISTING tag is set to YES Doxygen will
-# dump the program listings (including syntax highlighting
-# and cross-referencing information) to the XML output. Note that
-# enabling this will significantly increase the size of the XML output.
-
-XML_PROGRAMLISTING     = YES
-
-#---------------------------------------------------------------------------
-# configuration options for the AutoGen Definitions output
-#---------------------------------------------------------------------------
-
-# If the GENERATE_AUTOGEN_DEF tag is set to YES Doxygen will
-# generate an AutoGen Definitions (see autogen.sf.net) file
-# that captures the structure of the code including all
-# documentation. Note that this feature is still experimental
-# and incomplete at the moment.
-
-GENERATE_AUTOGEN_DEF   = NO
-
-#---------------------------------------------------------------------------
-# configuration options related to the Perl module output
-#---------------------------------------------------------------------------
-
-# If the GENERATE_PERLMOD tag is set to YES Doxygen will
-# generate a Perl module file that captures the structure of
-# the code including all documentation. Note that this
-# feature is still experimental and incomplete at the
-# moment.
-
-GENERATE_PERLMOD       = NO
-
-# If the PERLMOD_LATEX tag is set to YES Doxygen will generate
-# the necessary Makefile rules, Perl scripts and LaTeX code to be able
-# to generate PDF and DVI output from the Perl module output.
-
-PERLMOD_LATEX          = NO
-
-# If the PERLMOD_PRETTY tag is set to YES the Perl module output will be
-# nicely formatted so it can be parsed by a human reader.
-# This is useful
-# if you want to understand what is going on.
-# On the other hand, if this
-# tag is set to NO the size of the Perl module output will be much smaller
-# and Perl will parse it just the same.
-
-PERLMOD_PRETTY         = YES
-
-# The names of the make variables in the generated doxyrules.make file
-# are prefixed with the string contained in PERLMOD_MAKEVAR_PREFIX.
-# This is useful so different doxyrules.make files included by the same
-# Makefile don't overwrite each other's variables.
-
-PERLMOD_MAKEVAR_PREFIX =
-
-#---------------------------------------------------------------------------
-# Configuration options related to the preprocessor
-#---------------------------------------------------------------------------
-
-# If the ENABLE_PREPROCESSING tag is set to YES (the default) Doxygen will
-# evaluate all C-preprocessor directives found in the sources and include
-# files.
-
-ENABLE_PREPROCESSING   = YES
-
-# If the MACRO_EXPANSION tag is set to YES Doxygen will expand all macro
-# names in the source code. If set to NO (the default) only conditional
-# compilation will be performed. Macro expansion can be done in a controlled
-# way by setting EXPAND_ONLY_PREDEF to YES.
-
-MACRO_EXPANSION        = NO
-
-# If the EXPAND_ONLY_PREDEF and MACRO_EXPANSION tags are both set to YES
-# then the macro expansion is limited to the macros specified with the
-# PREDEFINED and EXPAND_AS_DEFINED tags.
-
-EXPAND_ONLY_PREDEF     = NO
-
-# If the SEARCH_INCLUDES tag is set to YES (the default) the includes files
-# pointed to by INCLUDE_PATH will be searched when a #include is found.
-
-SEARCH_INCLUDES        = YES
-
-# The INCLUDE_PATH tag can be used to specify one or more directories that
-# contain include files that are not input files but should be processed by
-# the preprocessor.
-
-INCLUDE_PATH           =
-
-# You can use the INCLUDE_FILE_PATTERNS tag to specify one or more wildcard
-# patterns (like *.h and *.hpp) to filter out the header-files in the
-# directories. If left blank, the patterns specified with FILE_PATTERNS will
-# be used.
-
-INCLUDE_FILE_PATTERNS  =
-
-# The PREDEFINED tag can be used to specify one or more macro names that
-# are defined before the preprocessor is started (similar to the -D option of
-# gcc). The argument of the tag is a list of macros of the form: name
-# or name=definition (no spaces). If the definition and the = are
-# omitted =1 is assumed. To prevent a macro definition from being
-# undefined via #undef or recursively expanded use the := operator
-# instead of the = operator.
-
-PREDEFINED             =
-
-# If the MACRO_EXPANSION and EXPAND_ONLY_PREDEF tags are set to YES then
-# this tag can be used to specify a list of macro names that should be expanded.
-# The macro definition that is found in the sources will be used.
-# Use the PREDEFINED tag if you want to use a different macro definition that
-# overrules the definition found in the source code.
-
-EXPAND_AS_DEFINED      =
-
-# If the SKIP_FUNCTION_MACROS tag is set to YES (the default) then
-# doxygen's preprocessor will remove all references to function-like macros
-# that are alone on a line, have an all uppercase name, and do not end with a
-# semicolon, because these will confuse the parser if not removed.
-
-SKIP_FUNCTION_MACROS   = YES
-
-#---------------------------------------------------------------------------
-# Configuration::additions related to external references
-#---------------------------------------------------------------------------
-
-# The TAGFILES option can be used to specify one or more tagfiles.
-# Optionally an initial location of the external documentation
-# can be added for each tagfile. The format of a tag file without
-# this location is as follows:
-#
-# TAGFILES = file1 file2 ...
-# Adding location for the tag files is done as follows:
-#
-# TAGFILES = file1=loc1 "file2 = loc2" ...
-# where "loc1" and "loc2" can be relative or absolute paths or
-# URLs. If a location is present for each tag, the installdox tool
-# does not have to be run to correct the links.
-# Note that each tag file must have a unique name
-# (where the name does NOT include the path)
-# If a tag file is not located in the directory in which doxygen
-# is run, you must also specify the path to the tagfile here.
-
-TAGFILES               =
-
-# When a file name is specified after GENERATE_TAGFILE, doxygen will create
-# a tag file that is based on the input files it reads.
-
-GENERATE_TAGFILE       =
-
-# If the ALLEXTERNALS tag is set to YES all external classes will be listed
-# in the class index. If set to NO only the inherited external classes
-# will be listed.
-
-ALLEXTERNALS           = NO
-
-# If the EXTERNAL_GROUPS tag is set to YES all external groups will be listed
-# in the modules index. If set to NO, only the current project's groups will
-# be listed.
-
-EXTERNAL_GROUPS        = YES
-
-# The PERL_PATH should be the absolute path and name of the perl script
-# interpreter (i.e. the result of `which perl').
-
-PERL_PATH              = /usr/bin/perl
-
-#---------------------------------------------------------------------------
-# Configuration options related to the dot tool
-#---------------------------------------------------------------------------
-
-# If the CLASS_DIAGRAMS tag is set to YES (the default) Doxygen will
-# generate a inheritance diagram (in HTML, RTF and LaTeX) for classes with base
-# or super classes. Setting the tag to NO turns the diagrams off. Note that
-# this option also works with HAVE_DOT disabled, but it is recommended to
-# install and use dot, since it yields more powerful graphs.
-
-CLASS_DIAGRAMS         = YES
-
-# You can define message sequence charts within doxygen comments using the \msc
-# command. Doxygen will then run the mscgen tool (see
-# http://www.mcternan.me.uk/mscgen/) to produce the chart and insert it in the
-# documentation. The MSCGEN_PATH tag allows you to specify the directory where
-# the mscgen tool resides. If left empty the tool is assumed to be found in the
-# default search path.
-
-MSCGEN_PATH            =
-
-# If set to YES, the inheritance and collaboration graphs will hide
-# inheritance and usage relations if the target is undocumented
-# or is not a class.
-
-HIDE_UNDOC_RELATIONS   = YES
-
-# If you set the HAVE_DOT tag to YES then doxygen will assume the dot tool is
-# available from the path. This tool is part of Graphviz, a graph visualization
-# toolkit from AT&T and Lucent Bell Labs. The other options in this section
-# have no effect if this option is set to NO (the default)
-
-HAVE_DOT               = NO
-
-# The DOT_NUM_THREADS specifies the number of dot invocations doxygen is
-# allowed to run in parallel. When set to 0 (the default) doxygen will
-# base this on the number of processors available in the system. You can set it
-# explicitly to a value larger than 0 to get control over the balance
-# between CPU load and processing speed.
-
-DOT_NUM_THREADS        = 0
-
-# By default doxygen will use the Helvetica font for all dot files that
-# doxygen generates. When you want a differently looking font you can specify
-# the font name using DOT_FONTNAME. You need to make sure dot is able to find
-# the font, which can be done by putting it in a standard location or by setting
-# the DOTFONTPATH environment variable or by setting DOT_FONTPATH to the
-# directory containing the font.
-
-DOT_FONTNAME           = Helvetica
-
-# The DOT_FONTSIZE tag can be used to set the size of the font of dot graphs.
-# The default size is 10pt.
-
-DOT_FONTSIZE           = 10
-
-# By default doxygen will tell dot to use the Helvetica font.
-# If you specify a different font using DOT_FONTNAME you can use DOT_FONTPATH to
-# set the path where dot can find it.
-
-DOT_FONTPATH           =
-
-# If the CLASS_GRAPH and HAVE_DOT tags are set to YES then doxygen
-# will generate a graph for each documented class showing the direct and
-# indirect inheritance relations. Setting this tag to YES will force the
-# CLASS_DIAGRAMS tag to NO.
-
-CLASS_GRAPH            = YES
-
-# If the COLLABORATION_GRAPH and HAVE_DOT tags are set to YES then doxygen
-# will generate a graph for each documented class showing the direct and
-# indirect implementation dependencies (inheritance, containment, and
-# class references variables) of the class with other documented classes.
-
-COLLABORATION_GRAPH    = YES
-
-# If the GROUP_GRAPHS and HAVE_DOT tags are set to YES then doxygen
-# will generate a graph for groups, showing the direct groups dependencies
-
-GROUP_GRAPHS           = YES
-
-# If the UML_LOOK tag is set to YES doxygen will generate inheritance and
-# collaboration diagrams in a style similar to the OMG's Unified Modeling
-# Language.
-
-UML_LOOK               = NO
-
-# If set to YES, the inheritance and collaboration graphs will show the
-# relations between templates and their instances.
-
-TEMPLATE_RELATIONS     = NO
-
-# If the ENABLE_PREPROCESSING, SEARCH_INCLUDES, INCLUDE_GRAPH, and HAVE_DOT
-# tags are set to YES then doxygen will generate a graph for each documented
-# file showing the direct and indirect include dependencies of the file with
-# other documented files.
-
-INCLUDE_GRAPH          = YES
-
-# If the ENABLE_PREPROCESSING, SEARCH_INCLUDES, INCLUDED_BY_GRAPH, and
-# HAVE_DOT tags are set to YES then doxygen will generate a graph for each
-# documented header file showing the documented files that directly or
-# indirectly include this file.
-
-INCLUDED_BY_GRAPH      = YES
-
-# If the CALL_GRAPH and HAVE_DOT options are set to YES then
-# doxygen will generate a call dependency graph for every global function
-# or class method. Note that enabling this option will significantly increase
-# the time of a run. So in most cases it will be better to enable call graphs
-# for selected functions only using the \callgraph command.
-
-CALL_GRAPH             = NO
-
-# If the CALLER_GRAPH and HAVE_DOT tags are set to YES then
-# doxygen will generate a caller dependency graph for every global function
-# or class method. Note that enabling this option will significantly increase
-# the time of a run. So in most cases it will be better to enable caller
-# graphs for selected functions only using the \callergraph command.
-
-CALLER_GRAPH           = NO
-
-# If the GRAPHICAL_HIERARCHY and HAVE_DOT tags are set to YES then doxygen
-# will generate a graphical hierarchy of all classes instead of a textual one.
-
-GRAPHICAL_HIERARCHY    = YES
-
-# If the DIRECTORY_GRAPH, SHOW_DIRECTORIES and HAVE_DOT tags are set to YES
-# then doxygen will show the dependencies a directory has on other directories
-# in a graphical way. The dependency relations are determined by the #include
-# relations between the files in the directories.
-
-DIRECTORY_GRAPH        = YES
-
-# The DOT_IMAGE_FORMAT tag can be used to set the image format of the images
-# generated by dot. Possible values are svg, png, jpg, or gif.
-# If left blank png will be used. If you choose svg you need to set
-# HTML_FILE_EXTENSION to xhtml in order to make the SVG files
-# visible in IE 9+ (other browsers do not have this requirement).
-
-DOT_IMAGE_FORMAT       = png
-
-# If DOT_IMAGE_FORMAT is set to svg, then this option can be set to YES to
-# enable generation of interactive SVG images that allow zooming and panning.
-# Note that this requires a modern browser other than Internet Explorer.
-# Tested and working are Firefox, Chrome, Safari, and Opera. For IE 9+ you
-# need to set HTML_FILE_EXTENSION to xhtml in order to make the SVG files
-# visible. Older versions of IE do not have SVG support.
-
-INTERACTIVE_SVG        = NO
-
-# The tag DOT_PATH can be used to specify the path where the dot tool can be
-# found. If left blank, it is assumed the dot tool can be found in the path.
-
-DOT_PATH               =
-
-# The DOTFILE_DIRS tag can be used to specify one or more directories that
-# contain dot files that are included in the documentation (see the
-# \dotfile command).
-
-DOTFILE_DIRS           =
-
-# The MSCFILE_DIRS tag can be used to specify one or more directories that
-# contain msc files that are included in the documentation (see the
-# \mscfile command).
-
-MSCFILE_DIRS           =
-
-# The DOT_GRAPH_MAX_NODES tag can be used to set the maximum number of
-# nodes that will be shown in the graph. If the number of nodes in a graph
-# becomes larger than this value, doxygen will truncate the graph, which is
-# visualized by representing a node as a red box. Note that doxygen if the
-# number of direct children of the root node in a graph is already larger than
-# DOT_GRAPH_MAX_NODES then the graph will not be shown at all. Also note
-# that the size of a graph can be further restricted by MAX_DOT_GRAPH_DEPTH.
-
-DOT_GRAPH_MAX_NODES    = 50
-
-# The MAX_DOT_GRAPH_DEPTH tag can be used to set the maximum depth of the
-# graphs generated by dot. A depth value of 3 means that only nodes reachable
-# from the root by following a path via at most 3 edges will be shown. Nodes
-# that lay further from the root node will be omitted. Note that setting this
-# option to 1 or 2 may greatly reduce the computation time needed for large
-# code bases. Also note that the size of a graph can be further restricted by
-# DOT_GRAPH_MAX_NODES. Using a depth of 0 means no depth restriction.
-
-MAX_DOT_GRAPH_DEPTH    = 0
-
-# Set the DOT_TRANSPARENT tag to YES to generate images with a transparent
-# background. This is disabled by default, because dot on Windows does not
-# seem to support this out of the box. Warning: Depending on the platform used,
-# enabling this option may lead to badly anti-aliased labels on the edges of
-# a graph (i.e. they become hard to read).
-
-DOT_TRANSPARENT        = NO
-
-# Set the DOT_MULTI_TARGETS tag to YES allow dot to generate multiple output
-# files in one run (i.e. multiple -o and -T options on the command line). This
-# makes dot run faster, but since only newer versions of dot (>1.8.10)
-# support this, this feature is disabled by default.
-
-DOT_MULTI_TARGETS      = YES
-
-# If the GENERATE_LEGEND tag is set to YES (the default) Doxygen will
-# generate a legend page explaining the meaning of the various boxes and
-# arrows in the dot generated graphs.
-
-GENERATE_LEGEND        = YES
-
-# If the DOT_CLEANUP tag is set to YES (the default) Doxygen will
-# remove the intermediate dot files that are used to generate
-# the various graphs.
-
-DOT_CLEANUP            = YES
diff --git a/CPU_version/svo/doc/.gitignore b/CPU_version/svo/doc/.gitignore
deleted file mode 100644
index cf57c3b..0000000
--- a/CPU_version/svo/doc/.gitignore
+++ /dev/null
@@ -1,2 +0,0 @@
-.gitignore
-!.gitignore
\ No newline at end of file
diff --git a/CPU_version/svo/doc/notation.ipe b/CPU_version/svo/doc/notation.ipe
deleted file mode 100644
index f8c1efe..0000000
--- a/CPU_version/svo/doc/notation.ipe
+++ /dev/null
@@ -1,312 +0,0 @@
-<?xml version="1.0"?>
-<!DOCTYPE ipe SYSTEM "ipe.dtd">
-<ipe version="70005" creator="Ipe 7.1.1">
-<info created="D:20120312120943" modified="D:20140611144527"/>
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diff --git a/CPU_version/svo/include/svo/bundle_adjustment.h b/CPU_version/svo/include/svo/bundle_adjustment.h
deleted file mode 100644
index f3c3501..0000000
--- a/CPU_version/svo/include/svo/bundle_adjustment.h
+++ /dev/null
@@ -1,109 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#ifndef SVO_BUNDLE_ADJUSTMENT_H_
-#define SVO_BUNDLE_ADJUSTMENT_H_
-
-#include <svo/global.h>
-
-namespace g2o {
-class EdgeProjectXYZ2UV;
-class SparseOptimizer;
-class VertexSE3Expmap;
-class VertexSBAPointXYZ;
-}
-
-namespace svo {
-
-typedef g2o::EdgeProjectXYZ2UV g2oEdgeSE3;
-typedef g2o::VertexSE3Expmap g2oFrameSE3;
-typedef g2o::VertexSBAPointXYZ g2oPoint;
-
-class Frame;
-class Point;
-class Feature;
-class Map;
-
-/// Local, global and 2-view bundle adjustment with g2o
-namespace ba {
-
-/// Temporary container to hold the g2o edge with reference to frame and point.
-struct EdgeContainerSE3
-{
-  g2oEdgeSE3*     edge;
-  Frame*          frame;
-  Feature*        feature;
-  bool            is_deleted;
-  EdgeContainerSE3(g2oEdgeSE3* e, Frame* frame, Feature* feature) :
-    edge(e), frame(frame), feature(feature), is_deleted(false)
-  {}
-};
-
-/// Optimize two camera frames and their observed 3D points.
-/// Is used after initialization.
-void twoViewBA(Frame* frame1, Frame* frame2, double reproj_thresh, Map* map);
-
-/// Local bundle adjustment.
-/// Optimizes core_kfs and their observed map points while keeping the
-/// neighbourhood fixed.
-void localBA(
-    Frame* center_kf,
-    set<FramePtr>* core_kfs,
-    Map* map,
-    size_t& n_incorrect_edges_1,
-    size_t& n_incorrect_edges_2,
-    double& init_error,
-    double& final_error);
-
-/// Global bundle adjustment.
-/// Optimizes the whole map. Is currently not used in SVO.
-void globalBA(Map* map);
-
-/// Initialize g2o with solver type, optimization strategy and camera model.
-void setupG2o(g2o::SparseOptimizer * optimizer);
-
-/// Run the optimization on the provided graph.
-void runSparseBAOptimizer(
-    g2o::SparseOptimizer* optimizer,
-    unsigned int num_iter,
-    double& init_error,
-    double& final_error);
-
-/// Create a g2o vertice from a keyframe object.
-g2oFrameSE3* createG2oFrameSE3(
-    Frame* kf,
-    size_t id,
-    bool fixed);
-
-/// Creates a g2o vertice from a mappoint object.
-g2oPoint* createG2oPoint(
-    Vector3d pos,
-    size_t id,
-    bool fixed);
-
-/// Creates a g2o edge between a g2o keyframe and mappoint vertice with the provided measurement.
-g2oEdgeSE3* createG2oEdgeSE3(
-    g2oFrameSE3* v_kf,
-    g2oPoint* v_mp,
-    const Vector2d& f_up,
-    bool robust_kernel,
-    double huber_width,
-    double weight = 1);
-
-} // namespace ba
-} // namespace svo
-
-#endif // SVO_BUNDLE_ADJUSTMENT_H_
diff --git a/CPU_version/svo/include/svo/config.h b/CPU_version/svo/include/svo/config.h
deleted file mode 100644
index e1c97b1..0000000
--- a/CPU_version/svo/include/svo/config.h
+++ /dev/null
@@ -1,177 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#ifndef SVO_CONFIG_H_
-#define SVO_CONFIG_H_
-
-#include <string>
-#include <stdint.h>
-#include <stdio.h>
-
-namespace svo {
-
-using std::string;
-
-/// Global configuration file of SVO.
-/// Implements the Singleton design pattern to allow global access and to ensure
-/// that only one instance exists.
-class Config
-{
-public:
-  static Config& getInstance();
-
-  /// Base-name of the tracefiles.
-  static string& traceName() { return getInstance().trace_name; }
-
-  /// Directory where the tracefiles are saved.
-  static string& traceDir() { return getInstance().trace_dir; }
-
-  /// Number of pyramid levels used for features.
-  static size_t& nPyrLevels() { return getInstance().n_pyr_levels; }
-
-  /// Use the IMU to get relative rotations.
-  static bool& useImu() { return getInstance().use_imu; }
-
-  /// Number of keyframes in the core. The core-kfs are optimized through bundle adjustment.
-  static size_t& coreNKfs() { return getInstance().core_n_kfs; }
-
-  /// Initial scale of the map. Depends on the distance the camera is moved for the initialization.
-  static double& mapScale() { return getInstance().map_scale; }
-
-  /// Feature grid size of a cell in [px].
-  static size_t& gridSize() { return getInstance().grid_size; }
-
-  /// Initialization: Minimum required disparity between the first two frames.
-  static double& initMinDisparity() { return getInstance().init_min_disparity; }
-
-  /// Initialization: Minimum number of tracked features.
-  static size_t& initMinTracked() { return getInstance().init_min_tracked; }
-
-  /// Initialization: Minimum number of inliers after RANSAC.
-  static size_t& initMinInliers() { return getInstance().init_min_inliers; }
-
-  /// Maximum level of the Lucas Kanade tracker.
-  static size_t& kltMaxLevel() { return getInstance().klt_max_level; }
-
-  /// Minimum level of the Lucas Kanade tracker.
-  static size_t& kltMinLevel() { return getInstance().klt_min_level; }
-
-  /// Reprojection threshold [px].
-  static double& reprojThresh() { return getInstance().reproj_thresh; }
-
-  /// Reprojection threshold after pose optimization.
-  static double& poseOptimThresh() { return getInstance().poseoptim_thresh; }
-
-  /// Number of iterations in local bundle adjustment.
-  static size_t& poseOptimNumIter() { return getInstance().poseoptim_num_iter; }
-
-  /// Maximum number of points to optimize at every iteration.
-  static size_t& structureOptimMaxPts() { return getInstance().structureoptim_max_pts; }
-
-  /// Number of iterations in structure optimization.
-  static size_t& structureOptimNumIter() { return getInstance().structureoptim_num_iter; }
-
-  /// Reprojection threshold after bundle adjustment.
-  static double& lobaThresh() { return getInstance().loba_thresh; }
-
-  /// Threshold for the robust Huber kernel of the local bundle adjustment.
-  static double& lobaRobustHuberWidth() { return getInstance().loba_robust_huber_width; }
-
-  /// Number of iterations in the local bundle adjustment.
-  static size_t& lobaNumIter() { return getInstance().loba_num_iter; }
-
-  /// Minimum distance between two keyframes. Relative to the average height in the map.
-  static double& kfSelectMinDist() { return getInstance().kfselect_mindist; }
-
-  /// Select only features with a minimum Harris corner score for triangulation.
-  static double& triangMinCornerScore() { return getInstance().triang_min_corner_score; }
-
-  /// Subpixel refinement of reprojection and triangulation. Set to 0 if no subpix refinement required!
-  static size_t& subpixNIter() { return getInstance().subpix_n_iter; }
-
-  /// Limit the number of keyframes in the map. This makes nslam essentially.
-  /// a Visual Odometry. Set to 0 if unlimited number of keyframes are allowed.
-  /// Minimum number of keyframes is 3.
-  static size_t& maxNKfs() { return getInstance().max_n_kfs; }
-
-  /// How much (in milliseconds) is the camera delayed with respect to the imu.
-  static double& imgImuDelay() { return getInstance().img_imu_delay; }
-
-  /// Maximum number of features that should be tracked.
-  static size_t& maxFts() { return getInstance().max_fts; }
-
-  /// If the number of tracked features drops below this threshold. Tracking quality is bad.
-  static size_t& qualityMinFts() { return getInstance().quality_min_fts; }
-
-  /// If within one frame, this amount of features are dropped. Tracking quality is bad.
-  static int& qualityMaxFtsDrop() { return getInstance().quality_max_drop_fts; }
-
-  /// acc white noise in continuous.
-  static double& ACC_Noise() { return getInstance().ACC_noise; }
-
-  /// acc white noise in continuous.
-  static double& GYO_Noise() { return getInstance().GYO_noise; }
-  /// integration uncertainty continuous
-  static double& IUC() { return getInstance().iuc; }
-    // acc bias in continuous
-  static double& ABC() { return getInstance().abc; }
-    // gyro bias in continuous
-  static double& GBC() { return getInstance().gbc; }
-    // error in the bias used for preintegration
-  static double& EBP() { return getInstance().ebp; }
-    // the noise used for projection
-  static double& NRP() { return getInstance().nrp; }
-
-
-private:
-  Config();
-  Config(Config const&);
-  void operator=(Config const&);
-  string trace_name;
-  string trace_dir;
-  size_t n_pyr_levels;
-  bool use_imu;
-  size_t core_n_kfs;
-  double map_scale;
-  size_t grid_size;
-  double init_min_disparity;
-  size_t init_min_tracked;
-  size_t init_min_inliers;
-  size_t klt_max_level;
-  size_t klt_min_level;
-  double reproj_thresh;
-  double poseoptim_thresh;
-  size_t poseoptim_num_iter;
-  size_t structureoptim_max_pts;
-  size_t structureoptim_num_iter;
-  double loba_thresh;
-  double loba_robust_huber_width;
-  size_t loba_num_iter;
-  double kfselect_mindist;
-  double triang_min_corner_score;
-  size_t triang_half_patch_size;
-  size_t subpix_n_iter;
-  size_t max_n_kfs;
-  double img_imu_delay;
-  size_t max_fts;
-  size_t quality_min_fts;
-  int quality_max_drop_fts;
-  double nrp,ebp,gbc,abc,iuc,ACC_noise,GYO_noise;
-};
-
-} // namespace svo
-
-#endif // SVO_CONFIG_H_
diff --git a/CPU_version/svo/include/svo/depth_filter.h b/CPU_version/svo/include/svo/depth_filter.h
deleted file mode 100644
index 1612d0e..0000000
--- a/CPU_version/svo/include/svo/depth_filter.h
+++ /dev/null
@@ -1,171 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#ifndef SVO_DEPTH_FILTER_H_
-#define SVO_DEPTH_FILTER_H_
-
-#include <queue>
-#include <boost/thread.hpp>
-#include <boost/function.hpp>
-#include <vikit/performance_monitor.h>
-#include <svo/global.h>
-#include <svo/feature_detection.h>
-#include <svo/matcher.h>
-
-namespace svo {
-
-class Frame;
-class Feature;
-class Point;
-
-/// A seed is a probabilistic depth estimate for a single pixel.
-struct Seed
-{
-  EIGEN_MAKE_ALIGNED_OPERATOR_NEW
-
-  static int batch_counter;
-  static int seed_counter;
-  int batch_id;                //!< Batch id is the id of the keyframe for which the seed was created.
-  int id;                      //!< Seed ID, only used for visualization.
-  Feature* ftr;                //!< Feature in the keyframe for which the depth should be computed.
-  float a;                     //!< a of Beta distribution: When high, probability of inlier is large.
-  float b;                     //!< b of Beta distribution: When high, probability of outlier is large.
-  float mu;                    //!< Mean of normal distribution.
-  float z_range;               //!< Max range of the possible depth.
-  float sigma2;                //!< Variance of normal distribution.
-  Matrix2d patch_cov;          //!< Patch covariance in reference image.
-  Seed(Feature* ftr, float depth_mean, float depth_min);
-};
-
-/// Depth filter implements the Bayesian Update proposed in:
-/// "Video-based, Real-Time Multi View Stereo" by G. Vogiatzis and C. Hernández.
-/// In Image and Vision Computing, 29(7):434-441, 2011.
-///
-/// The class uses a callback mechanism such that it can be used also by other
-/// algorithms than nslam and for simplified testing.
-class DepthFilter
-{
-public:
-  EIGEN_MAKE_ALIGNED_OPERATOR_NEW
-
-  typedef boost::unique_lock<boost::mutex> lock_t;
-  typedef boost::function<void ( Point*, double )> callback_t;
-
-  /// Depth-filter config parameters
-  struct Options
-  {
-    bool check_ftr_angle;                       //!< gradient features are only updated if the epipolar line is orthogonal to the gradient.
-    bool epi_search_1d;                         //!< restrict Gauss Newton in the epipolar search to the epipolar line.
-    bool verbose;                               //!< display output.
-    bool use_photometric_disparity_error;       //!< use photometric disparity error instead of 1px error in tau computation.
-    int max_n_kfs;                              //!< maximum number of keyframes for which we maintain seeds.
-    double sigma_i_sq;                          //!< image noise.
-    double seed_convergence_sigma2_thresh;      //!< threshold on depth uncertainty for convergence.
-    Options()
-    : check_ftr_angle(false),
-      epi_search_1d(false),
-      verbose(false),
-      use_photometric_disparity_error(false),
-      max_n_kfs(3),
-      sigma_i_sq(5e-4),
-      seed_convergence_sigma2_thresh(200.0)
-    {}
-  } options_;
-
-  DepthFilter(
-      feature_detection::DetectorPtr feature_detector,
-      callback_t seed_converged_cb);
-
-  virtual ~DepthFilter();
-
-  /// Start this thread when seed updating should be in a parallel thread.
-  void startThread();
-
-  /// Stop the parallel thread that is running.
-  void stopThread();
-
-  /// Add frame to the queue to be processed.
-  void addFrame(FramePtr frame);
-
-  /// Add new keyframe to the queue
-  void addKeyframe(FramePtr frame, double depth_mean, double depth_min);
-
-  /// Remove all seeds which are initialized from the specified keyframe. This
-  /// function is used to make sure that no seeds points to a non-existent frame
-  /// when a frame is removed from the map.
-  void removeKeyframe(FramePtr frame);
-
-  /// If the map is reset, call this function such that we don't have pointers
-  /// to old frames.
-  void reset();
-
-  /// Returns a copy of the seeds belonging to frame. Thread-safe.
-  /// Can be used to compute the Next-Best-View in parallel.
-  /// IMPORTANT! Make sure you hold a valid reference counting pointer to frame
-  /// so it is not being deleted while you use it.
-  void getSeedsCopy(const FramePtr& frame, std::list<Seed>& seeds);
-
-  /// Return a reference to the seeds. This is NOT THREAD SAFE!
-  //std::list<Seed>& getSeeds() { return seeds_; } Bug 238
-  std::list<Seed, Eigen::aligned_allocator<Seed>>& getSeeds() { return seeds_; }
-
-  /// Bayes update of the seed, x is the measurement, tau2 the measurement uncertainty
-  static void updateSeed(
-      const float x,
-      const float tau2,
-      Seed* seed);
-
-  /// Compute the uncertainty of the measurement.
-  static double computeTau(
-      const SE3& T_ref_cur,
-      const Vector3d& f,
-      const double z,
-      const double px_error_angle);
-
-protected:
-  feature_detection::DetectorPtr feature_detector_;
-  callback_t seed_converged_cb_;
-  //std::list<Seed> seeds_;
-  std::list<Seed, Eigen::aligned_allocator<Seed>> seeds_;
-  boost::mutex seeds_mut_;
-  bool seeds_updating_halt_;            //!< Set this value to true when seeds updating should be interrupted.
-  boost::thread* thread_;
-  std::queue<FramePtr> frame_queue_;
-  boost::mutex frame_queue_mut_;
-  boost::condition_variable frame_queue_cond_;
-  FramePtr new_keyframe_;               //!< Next keyframe to extract new seeds.
-  bool new_keyframe_set_;               //!< Do we have a new keyframe to process?.
-  double new_keyframe_min_depth_;       //!< Minimum depth in the new keyframe. Used for range in new seeds.
-  double new_keyframe_mean_depth_;      //!< Maximum depth in the new keyframe. Used for range in new seeds.
-  vk::PerformanceMonitor permon_;       //!< Separate performance monitor since the DepthFilter runs in a parallel thread.
-  Matcher matcher_;
-
-  /// Initialize new seeds from a frame.
-  void initializeSeeds(FramePtr frame);
-
-  /// Update all seeds with a new measurement frame.
-  virtual void updateSeeds(FramePtr frame);
-
-  /// When a new keyframe arrives, the frame queue should be cleared.
-  void clearFrameQueue();
-
-  /// A thread that is continuously updating the seeds.
-  void updateSeedsLoop();
-};
-
-} // namespace svo
-
-#endif // SVO_DEPTH_FILTER_H_
diff --git a/CPU_version/svo/include/svo/feature.h b/CPU_version/svo/include/svo/feature.h
deleted file mode 100644
index 6f90a9a..0000000
--- a/CPU_version/svo/include/svo/feature.h
+++ /dev/null
@@ -1,75 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#ifndef SVO_FEATURE_H_
-#define SVO_FEATURE_H_
-
-#include <svo/frame.h>
-
-namespace svo {
-
-/// A salient image region that is tracked across frames.
-struct Feature
-{
-  EIGEN_MAKE_ALIGNED_OPERATOR_NEW
-
-  enum FeatureType {
-    CORNER,
-    EDGELET
-  };
-
-  FeatureType type;     //!< Type can be corner or edgelet.
-  Frame* frame;         //!< Pointer to frame in which the feature was detected.
-  Vector2d px;          //!< Coordinates in pixels on pyramid level 0.
-  Vector3d f;           //!< Unit-bearing vector of the feature.
-  int level;            //!< Image pyramid level where feature was extracted.
-  Point* point;         //!< Pointer to 3D point which corresponds to the feature.
-  Vector2d grad;        //!< Dominant gradient direction for edglets, normalized.
-
-  Feature(Frame* _frame, const Vector2d& _px, int _level) :
-    type(CORNER),
-    frame(_frame),
-    px(_px),
-    f(frame->cam_->cam2world(px)),
-    level(_level),
-    point(NULL),
-    grad(1.0,0.0)
-  {}
-
-  Feature(Frame* _frame, const Vector2d& _px, const Vector3d& _f, int _level) :
-    type(CORNER),
-    frame(_frame),
-    px(_px),
-    f(_f),
-    level(_level),
-    point(NULL),
-    grad(1.0,0.0)
-  {}
-
-  Feature(Frame* _frame, Point* _point, const Vector2d& _px, const Vector3d& _f, int _level) :
-    type(CORNER),
-    frame(_frame),
-    px(_px),
-    f(_f),
-    level(_level),
-    point(_point),
-    grad(1.0,0.0)
-  {}
-};
-
-} // namespace svo
-
-#endif // SVO_FEATURE_H_
diff --git a/CPU_version/svo/include/svo/feature_alignment.h b/CPU_version/svo/include/svo/feature_alignment.h
deleted file mode 100644
index 12523e3..0000000
--- a/CPU_version/svo/include/svo/feature_alignment.h
+++ /dev/null
@@ -1,63 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#ifndef SVO_FEATURE_ALIGNMENT_H_
-#define SVO_FEATURE_ALIGNMENT_H_
-
-#include <svo/global.h>
-
-namespace svo {
-
-/// Subpixel refinement of a reference feature patch with the current image.
-/// Implements the inverse-compositional approach (see "Lucas-Kanade 20 Years on"
-/// paper by Baker.
-namespace feature_alignment {
-
-bool align1D(
-    const cv::Mat& cur_img,
-    const Vector2f& dir,                  // direction in which the patch is allowed to move
-    uint8_t* ref_patch_with_border,
-    uint8_t* ref_patch,
-    const int n_iter,
-    Vector2d& cur_px_estimate,
-    double& h_inv);
-
-bool align2D(
-    const cv::Mat& cur_img,
-    uint8_t* ref_patch_with_border,
-    uint8_t* ref_patch,
-    const int n_iter,
-    Vector2d& cur_px_estimate,
-    bool no_simd = false);
-
-bool align2D_SSE2(
-    const cv::Mat& cur_img,
-    uint8_t* ref_patch_with_border,
-    uint8_t* ref_patch,
-    const int n_iter,
-    Vector2d& cur_px_estimate);
-
-bool align2D_NEON(
-    const cv::Mat& cur_img,
-    uint8_t* ref_patch_with_border,
-    uint8_t* ref_patch,
-    const int n_iter,
-    Vector2d& cur_px_estimate);
-
-} // namespace feature_alignment
-} // namespace svo
-
-#endif // SVO_FEATURE_ALIGNMENT_H_
diff --git a/CPU_version/svo/include/svo/feature_detection.h b/CPU_version/svo/include/svo/feature_detection.h
deleted file mode 100644
index d0990a8..0000000
--- a/CPU_version/svo/include/svo/feature_detection.h
+++ /dev/null
@@ -1,107 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#ifndef SVO_FEATURE_DETECTION_H_
-#define SVO_FEATURE_DETECTION_H_
-
-#include <svo/global.h>
-#include <svo/frame.h>
-
-namespace svo {
-
-/// Implementation of various feature detectors.
-namespace feature_detection {
-
-/// Temporary container used for corner detection. Features are initialized from these.
-struct Corner
-{
-  int x;        //!< x-coordinate of corner in the image.
-  int y;        //!< y-coordinate of corner in the image.
-  int level;    //!< pyramid level of the corner.
-  float score;  //!< shi-tomasi score of the corner.
-  float angle;  //!< for gradient-features: dominant gradient angle.
-  Corner(int x, int y, float score, int level, float angle) :
-    x(x), y(y), level(level), score(score), angle(angle)
-  {}
-};
-typedef vector<Corner> Corners;
-
-/// All detectors should derive from this abstract class.
-class AbstractDetector
-{
-public:
-  AbstractDetector(
-      const int img_width,
-      const int img_height,
-      const int cell_size,
-      const int n_pyr_levels);
-
-  virtual ~AbstractDetector() {};
-
-  virtual void detect(
-      Frame* frame,
-      const ImgPyr& img_pyr,
-      const double detection_threshold,
-      Features& fts) = 0;
-
-  /// Flag the grid cell as occupied
-  void setGridOccpuancy(const Vector2d& px);
-
-  /// Set grid cells of existing features as occupied
-  void setExistingFeatures(const Features& fts);
-
-protected:
-
-  static const int border_ = 8; //!< no feature should be within 8px of border.
-  const int cell_size_;
-  const int n_pyr_levels_;
-  const int grid_n_cols_;
-  const int grid_n_rows_;
-  vector<bool> grid_occupancy_;
-
-  void resetGrid();
-
-  inline int getCellIndex(int x, int y, int level)
-  {
-    const int scale = (1<<level);
-    return (scale*y)/cell_size_*grid_n_cols_ + (scale*x)/cell_size_;
-  }
-};
-typedef boost::shared_ptr<AbstractDetector> DetectorPtr;
-
-/// FAST detector by Edward Rosten.
-class FastDetector : public AbstractDetector
-{
-public:
-  FastDetector(
-      const int img_width,
-      const int img_height,
-      const int cell_size,
-      const int n_pyr_levels);
-
-  virtual ~FastDetector() {}
-
-  virtual void detect(
-      Frame* frame,
-      const ImgPyr& img_pyr,
-      const double detection_threshold,
-      Features& fts);
-};
-
-} // namespace feature_detection
-} // namespace svo
-
-#endif // SVO_FEATURE_DETECTION_H_
diff --git a/CPU_version/svo/include/svo/frame.h b/CPU_version/svo/include/svo/frame.h
deleted file mode 100644
index c926277..0000000
--- a/CPU_version/svo/include/svo/frame.h
+++ /dev/null
@@ -1,154 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#ifndef SVO_FRAME_H_
-#define SVO_FRAME_H_
-
-#include <sophus/se3.h>
-#include <vikit/math_utils.h>
-#include <vikit/abstract_camera.h>
-#include <boost/noncopyable.hpp>
-#include <svo/global.h>
-
-namespace g2o {
-class VertexSE3Expmap;
-}
-typedef g2o::VertexSE3Expmap g2oFrameSE3;
-
-namespace svo {
-
-class Point;
-struct Feature;
-
-typedef list<Feature*> Features;
-typedef vector<cv::Mat> ImgPyr;
-
-/// A frame saves the image, the associated features and the estimated pose.
-class Frame : boost::noncopyable
-{
-public:
-  EIGEN_MAKE_ALIGNED_OPERATOR_NEW
-    
-  static int                    frame_counter_;         //!< Counts the number of created frames. Used to set the unique id.
-  int                           id_;                    //!< Unique id of the frame.
-  double                        timestamp_;             //!< Timestamp of when the image was recorded.
-  vk::AbstractCamera*           cam_;                   //!< Camera model.
-  Sophus::SE3                   T_f_w_;                 //!< Transform (f)rame from (w)orld.
-  Matrix<double, 6, 6>          Cov_;                   //!< Covariance.
-  ImgPyr                        img_pyr_;               //!< Image Pyramid.
-  Features                      fts_;                   //!< List of features in the image.
-  vector<Feature*>              key_pts_;               //!< Five features and associated 3D points which are used to detect if two frames have overlapping field of view.
-  bool                          is_keyframe_;           //!< Was this frames selected as keyframe?
-  g2oFrameSE3*                  v_kf_;                  //!< Temporary pointer to the g2o node object of the keyframe.
-  int                           last_published_ts_;     //!< Timestamp of last publishing.
-
-  Frame(vk::AbstractCamera* cam, const cv::Mat& img, double timestamp);
-  ~Frame();
-
-  /// Initialize new frame and create image pyramid.
-  void initFrame(const cv::Mat& img);
-
-  /// Select this frame as keyframe.
-  void setKeyframe();
-
-  /// Add a feature to the image
-  void addFeature(Feature* ftr);
-
-  /// The KeyPoints are those five features which are closest to the 4 image corners
-  /// and to the center and which have a 3D point assigned. These points are used
-  /// to quickly check whether two frames have overlapping field of view.
-  void setKeyPoints();
-
-  /// Check if we can select five better key-points.
-  void checkKeyPoints(Feature* ftr);
-
-  /// If a point is deleted, we must remove the corresponding key-point.
-  void removeKeyPoint(Feature* ftr);
-
-  /// Return number of point observations.
-  inline size_t nObs() const { return fts_.size(); }
-
-  /// Check if a point in (w)orld coordinate frame is visible in the image.
-  bool isVisible(const Vector3d& xyz_w) const;
-
-  /// Full resolution image stored in the frame.
-  inline const cv::Mat& img() const { return img_pyr_[0]; }
-
-  /// Was this frame selected as keyframe?
-  inline bool isKeyframe() const { return is_keyframe_; }
-
-  /// Transforms point coordinates in world-frame (w) to camera pixel coordinates (c).
-  inline Vector2d w2c(const Vector3d& xyz_w) const { return cam_->world2cam( T_f_w_ * xyz_w ); }
-
-  /// Transforms pixel coordinates (c) to frame unit sphere coordinates (f).
-  inline Vector3d c2f(const Vector2d& px) const { return cam_->cam2world(px[0], px[1]); }
-
-  /// Transforms pixel coordinates (c) to frame unit sphere coordinates (f).
-  inline Vector3d c2f(const double x, const double y) const { return cam_->cam2world(x, y); }
-
-  /// Transforms point coordinates in world-frame (w) to camera-frams (f).
-  inline Vector3d w2f(const Vector3d& xyz_w) const { return T_f_w_ * xyz_w; }
-
-  /// Transforms point from frame unit sphere (f) frame to world coordinate frame (w).
-  inline Vector3d f2w(const Vector3d& f) const { return T_f_w_.inverse() * f; }
-
-  /// Projects Point from unit sphere (f) in camera pixels (c).
-  inline Vector2d f2c(const Vector3d& f) const { return cam_->world2cam( f ); }
-
-  /// Return the pose of the frame in the (w)orld coordinate frame.
-  inline Vector3d pos() const { return T_f_w_.inverse().translation(); }
-
-  /// Frame jacobian for projection of 3D point in (f)rame coordinate to
-  /// unit plane coordinates uv (focal length = 1).
-  inline static void jacobian_xyz2uv(
-      const Vector3d& xyz_in_f,
-      Matrix<double,2,6>& J)
-  {
-    const double x = xyz_in_f[0];
-    const double y = xyz_in_f[1];
-    const double z_inv = 1./xyz_in_f[2];
-    const double z_inv_2 = z_inv*z_inv;
-
-    J(0,0) = -z_inv;              // -1/z
-    J(0,1) = 0.0;                 // 0
-    J(0,2) = x*z_inv_2;           // x/z^2
-    J(0,3) = y*J(0,2);            // x*y/z^2
-    J(0,4) = -(1.0 + x*J(0,2));   // -(1.0 + x^2/z^2)
-    J(0,5) = y*z_inv;             // y/z
-
-    J(1,0) = 0.0;                 // 0
-    J(1,1) = -z_inv;              // -1/z
-    J(1,2) = y*z_inv_2;           // y/z^2
-    J(1,3) = 1.0 + y*J(1,2);      // 1.0 + y^2/z^2
-    J(1,4) = -J(0,3);             // -x*y/z^2
-    J(1,5) = -x*z_inv;            // x/z
-  }
-};
-
-
-/// Some helper functions for the frame object.
-namespace frame_utils {
-
-/// Creates an image pyramid of half-sampled images.
-void createImgPyramid(const cv::Mat& img_level_0, int n_levels, ImgPyr& pyr);
-
-/// Get the average depth of the features in the image.
-bool getSceneDepth(const Frame& frame, double& depth_mean, double& depth_min);
-
-} // namespace frame_utils
-} // namespace svo
-
-#endif // SVO_FRAME_H_
diff --git a/CPU_version/svo/include/svo/frame_handler_base.h b/CPU_version/svo/include/svo/frame_handler_base.h
deleted file mode 100644
index 9a78639..0000000
--- a/CPU_version/svo/include/svo/frame_handler_base.h
+++ /dev/null
@@ -1,123 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#ifndef SVO_FRAME_HANDLER_BASE_H_
-#define SVO_FRAME_HANDLER_BASE_H_
-
-#include <queue>
-#include <vikit/timer.h>
-#include <vikit/ringbuffer.h>
-#include <boost/noncopyable.hpp>
-#include <boost/function.hpp>
-#include <boost/thread.hpp>
-#include <svo/global.h>
-#include <svo/map.h>
-
-namespace vk
-{
-class AbstractCamera;
-class PerformanceMonitor;
-}
-
-namespace svo
-{
-class Point;
-class Matcher;
-class DepthFilter;
-
-/// Base class for various VO pipelines. Manages the map and the state machine.
-class FrameHandlerBase : boost::noncopyable
-{
-public:
-  enum Stage {
-    STAGE_PAUSED,
-    STAGE_FIRST_FRAME,
-    STAGE_SECOND_FRAME,
-    STAGE_DEFAULT_FRAME,
-    STAGE_RELOCALIZING
-  };
-  enum TrackingQuality {
-    TRACKING_INSUFFICIENT,
-    TRACKING_BAD,
-    TRACKING_GOOD
-  };
-  enum UpdateResult {
-    RESULT_NO_KEYFRAME,
-    RESULT_IS_KEYFRAME,
-    RESULT_FAILURE
-  };
-
-  FrameHandlerBase();
-
-  virtual ~FrameHandlerBase();
-
-  /// Get the current map.
-  const Map& map() const { return map_; }
-
-  /// Will reset the map as soon as the current frame is finished processing.
-  void reset() { set_reset_ = true; }
-
-  /// Start processing.
-  void start() { set_start_ = true; }
-
-  /// Get the current stage of the algorithm.
-  Stage stage() const { return stage_; }
-
-  /// Get tracking quality.
-  TrackingQuality trackingQuality() const { return tracking_quality_; }
-
-  /// Get the processing time of the previous iteration.
-  double lastProcessingTime() const { return timer_.getTime(); }
-
-  /// Get the number of feature observations of the last frame.
-  size_t lastNumObservations() const { return num_obs_last_; }
-
-protected:
-  Stage stage_;                 //!< Current stage of the algorithm.
-  bool set_reset_;              //!< Flag that the user can set. Will reset the system before the next iteration.
-  bool set_start_;              //!< Flag the user can set to start the system when the next image is received.
-  Map map_;                     //!< Map of keyframes created by the slam system.
-  vk::Timer timer_;             //!< Stopwatch to measure time to process frame.
-  vk::RingBuffer<double> acc_frame_timings_;    //!< Total processing time of the last 10 frames, used to give some user feedback on the performance.
-  vk::RingBuffer<size_t> acc_num_obs_;          //!< Number of observed features of the last 10 frames, used to give some user feedback on the tracking performance.
-  size_t num_obs_last_;                         //!< Number of observations in the previous frame.
-  TrackingQuality tracking_quality_;            //!< An estimate of the tracking quality based on the number of tracked features.
-
-  /// Before a frame is processed, this function is called.
-  bool startFrameProcessingCommon(const double timestamp);
-
-  /// When a frame is finished processing, this function is called.
-  int finishFrameProcessingCommon(
-      const size_t update_id,
-      const UpdateResult dropout,
-      const size_t num_observations);
-
-  /// Reset the map and frame handler to start from scratch.
-  void resetCommon();
-
-  /// Reset the frame handler. Implement in derived class.
-  virtual void resetAll() { resetCommon(); }
-
-  /// Set the tracking quality based on the number of tracked features.
-  virtual void setTrackingQuality(const size_t num_observations);
-
-  /// Optimize some of the observed 3D points.
-  virtual void optimizeStructure(FramePtr frame, size_t max_n_pts, int max_iter);
-};
-
-} // namespace nslam
-
-#endif // SVO_FRAME_HANDLER_BASE_H_
diff --git a/CPU_version/svo/include/svo/frame_handler_mono.h b/CPU_version/svo/include/svo/frame_handler_mono.h
deleted file mode 100644
index 58789c8..0000000
--- a/CPU_version/svo/include/svo/frame_handler_mono.h
+++ /dev/null
@@ -1,104 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#ifndef SVO_FRAME_HANDLER_H_
-#define SVO_FRAME_HANDLER_H_
-
-#include <set>
-#include <vikit/abstract_camera.h>
-#include <svo/frame_handler_base.h>
-#include <svo/reprojector.h>
-#include <svo/initialization.h>
-#include <svo/imu_integration.h>
-
-namespace svo {
-
-/// Monocular Visual Odometry Pipeline as described in the SVO paper.
-class FrameHandlerMono : public FrameHandlerBase
-{
-public:
-  EIGEN_MAKE_ALIGNED_OPERATOR_NEW
-  
-  FrameHandlerMono(vk::AbstractCamera* cam,Sophus::SE3& SE_init);
-  virtual ~FrameHandlerMono();
-
-  /// Provide an image.
-  void addImage(const cv::Mat& img, double timestamp);
-
-  /// Set the first frame (used for synthetic datasets in benchmark node)
-  void setFirstFrame(const FramePtr& first_frame);
-
-  /// Get the last frame that has been processed.
-  FramePtr lastFrame() { return last_frame_; }
-
-  /// Get the set of spatially closest keyframes of the last frame.
-  const set<FramePtr>& coreKeyframes() { return core_kfs_; }
-
-  /// Return the feature track to visualize the KLT tracking during initialization.
-  const vector<cv::Point2f>& initFeatureTrackRefPx() const { return klt_homography_init_.px_ref_; }
-  const vector<cv::Point2f>& initFeatureTrackCurPx() const { return klt_homography_init_.px_cur_; }
-
-  /// Access the depth filter.
-  DepthFilter* depthFilter() const { return depth_filter_; }
-
-  /// An external place recognition module may know where to relocalize.
-  bool relocalizeFrameAtPose(
-      const int keyframe_id,
-      const SE3& T_kf_f,
-      const cv::Mat& img,
-      const double timestamp);
-  std::unique_ptr<Imu_Integration> imu_integPtr_;  //Integration of IMU
-
-protected:
-  vk::AbstractCamera* cam_;                     //!< Camera model, can be ATAN, Pinhole or Ocam (see vikit).
-  Reprojector reprojector_;                     //!< Projects points from other keyframes into the current frame
-  FramePtr new_frame_;                          //!< Current frame.
-  FramePtr last_frame_;                         //!< Last frame, not necessarily a keyframe.
-  set<FramePtr> core_kfs_;                      //!< Keyframes in the closer neighbourhood.
-  vector< pair<FramePtr,size_t> > overlap_kfs_; //!< All keyframes with overlapping field of view. the paired number specifies how many common mappoints are observed TODO: why vector!?
-  initialization::KltHomographyInit klt_homography_init_; //!< Used to estimate pose of the first two keyframes by estimating a homography.
-  DepthFilter* depth_filter_;                   //!< Depth estimation algorithm runs in a parallel thread and is used to initialize new 3D points.
-
-
-  /// Initialize the visual odometry algorithm.
-  virtual void initialize();
-
-  /// Processes the first frame and sets it as a keyframe.
-  virtual UpdateResult processFirstFrame();
-
-  /// Processes all frames after the first frame until a keyframe is selected.
-  virtual UpdateResult processSecondFrame();
-
-  /// Processes all frames after the first two keyframes.
-  virtual UpdateResult processFrame();
-
-  /// Try relocalizing the frame at relative position to provided keyframe.
-  virtual UpdateResult relocalizeFrame(
-      const SE3& T_cur_ref,
-      FramePtr ref_keyframe);
-
-  /// Reset the frame handler. Implement in derived class.
-  virtual void resetAll();
-
-  /// Keyframe selection criterion.
-  virtual bool needNewKf(double scene_depth_mean);
-
-  void setCoreKfs(size_t n_closest);
-};
-
-} // namespace svo
-
-#endif // SVO_FRAME_HANDLER_H_
diff --git a/CPU_version/svo/include/svo/global.h b/CPU_version/svo/include/svo/global.h
deleted file mode 100644
index 03aff4e..0000000
--- a/CPU_version/svo/include/svo/global.h
+++ /dev/null
@@ -1,101 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#ifndef SVO_GLOBAL_H_
-#define SVO_GLOBAL_H_
-
-#include <list>
-#include <vector>
-#include <string>
-#include <stdint.h>
-#include <stdio.h>
-#include <math.h>
-
-#include <Eigen/Core>
-#include <opencv2/opencv.hpp>
-#include <sophus/se3.h>
-#include <vikit/performance_monitor.h>
-#include <boost/shared_ptr.hpp>
-#include<Eigen/StdVector>
-#ifndef RPG_SVO_VIKIT_IS_VECTOR_SPECIALIZED //Guard for rpg_vikit
-#define RPG_SVO_VIKIT_IS_VECTOR_SPECIALIZED
-EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(Eigen::Vector3d)
-EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(Eigen::Vector2d)
-#endif
-
-#ifdef SVO_USE_ROS
-  #include <ros/console.h>
-  #define SVO_DEBUG_STREAM(x) ROS_DEBUG_STREAM(x)
-  #define SVO_INFO_STREAM(x) ROS_INFO_STREAM(x)
-  #define SVO_WARN_STREAM(x) ROS_WARN_STREAM(x)
-  #define SVO_WARN_STREAM_THROTTLE(rate, x) ROS_WARN_STREAM_THROTTLE(rate, x)
-  #define SVO_ERROR_STREAM(x) ROS_ERROR_STREAM(x)
-#else
-  #define SVO_INFO_STREAM(x) std::cerr<<"\033[0;0m[INFO] "<<x<<"\033[0;0m"<<std::endl;
-  #ifdef SVO_DEBUG_OUTPUT
-    #define SVO_DEBUG_STREAM(x) SVO_INFO_STREAM(x)
-  #else
-    #define SVO_DEBUG_STREAM(x)
-  #endif
-  #define SVO_WARN_STREAM(x) std::cerr<<"\033[0;33m[WARN] "<<x<<"\033[0;0m"<<std::endl;
-  #define SVO_ERROR_STREAM(x) std::cerr<<"\033[1;31m[ERROR] "<<x<<"\033[0;0m"<<std::endl;
-  #include <chrono> // Adapted from rosconsole. Copyright (c) 2008, Willow Garage, Inc.
-  #define SVO_WARN_STREAM_THROTTLE(rate, x) \
-    do { \
-      static double __log_stream_throttle__last_hit__ = 0.0; \
-      std::chrono::time_point<std::chrono::system_clock> __log_stream_throttle__now__ = \
-      std::chrono::system_clock::now(); \
-      if (__log_stream_throttle__last_hit__ + rate <= \
-          std::chrono::duration_cast<std::chrono::seconds>( \
-          __log_stream_throttle__now__.time_since_epoch()).count()) { \
-        __log_stream_throttle__last_hit__ = \
-        std::chrono::duration_cast<std::chrono::seconds>( \
-        __log_stream_throttle__now__.time_since_epoch()).count(); \
-        SVO_WARN_STREAM(x); \
-      } \
-    } while(0)
-#endif
-
-namespace svo
-{
-  using namespace Eigen;
-  using namespace Sophus;
-
-  const double EPS = 0.0000000001;
-  const double PI = 3.14159265;
-
-#ifdef SVO_TRACE
-  extern vk::PerformanceMonitor* g_permon;
-  #define SVO_LOG(value) g_permon->log(std::string((#value)),(value))
-  #define SVO_LOG2(value1, value2) SVO_LOG(value1); SVO_LOG(value2)
-  #define SVO_LOG3(value1, value2, value3) SVO_LOG2(value1, value2); SVO_LOG(value3)
-  #define SVO_LOG4(value1, value2, value3, value4) SVO_LOG2(value1, value2); SVO_LOG2(value3, value4)
-  #define SVO_START_TIMER(name) g_permon->startTimer((name))
-  #define SVO_STOP_TIMER(name) g_permon->stopTimer((name))
-#else
-  #define SVO_LOG(v)
-  #define SVO_LOG2(v1, v2)
-  #define SVO_LOG3(v1, v2, v3)
-  #define SVO_LOG4(v1, v2, v3, v4)
-  #define SVO_START_TIMER(name)
-  #define SVO_STOP_TIMER(name)
-#endif
-
-  class Frame;
-  typedef boost::shared_ptr<Frame> FramePtr;
-} // namespace svo
-
-#endif // SVO_GLOBAL_H_
diff --git a/CPU_version/svo/include/svo/imu_integration.h b/CPU_version/svo/include/svo/imu_integration.h
deleted file mode 100644
index 11b9055..0000000
--- a/CPU_version/svo/include/svo/imu_integration.h
+++ /dev/null
@@ -1,121 +0,0 @@
-//
-// Created by gufe on 4/9/21.
-//
-
-#ifndef SVO_IMU_INTEGRATION_H
-#define SVO_IMU_INTEGRATION_H
-#include <gtsam/navigation/CombinedImuFactor.h>
-#include <gtsam/navigation/ImuFactor.h>
-#include <gtsam/nonlinear/NonlinearFactorGraph.h>
-#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
-#include <gtsam/navigation/ImuBias.h>
-#include <gtsam/inference/Symbol.h>
-#include <gtsam/slam/ProjectionFactor.h>
-#include <gtsam/nonlinear/ISAM2.h>
-#include <sophus/se3.h>
-#include <svo/frame.h>
-
-using gtsam::symbol_shorthand::B;  // Bias  (ax,ay,az,gx,gy,gz)
-using gtsam::symbol_shorthand::V;  // Vel   (xdot,ydot,zdot)
-using gtsam::symbol_shorthand::P;  // Pose3 (x,y,z,r,p,y)
-using gtsam::symbol_shorthand::C;  // Camera pose
-
-//https://stackoverflow.com/questions/24881799/get-index-in-c11-foreach-loop
-// Wrapper class
-template <typename T>
-class enumerate_impl
-{
-public:
-    // The return value of the operator* of the iterator, this
-    // is what you will get inside of the for loop
-    struct item
-    {
-        size_t index;
-        typename T::value_type & item;
-    };
-    typedef item value_type;
-
-    // Custom iterator with minimal interface
-    struct iterator
-    {
-        iterator(typename T::iterator _it, size_t counter=0) :
-                it(_it), counter(counter)
-        {}
-
-        iterator operator++()
-        {
-            return iterator(++it, ++counter);
-        }
-
-        bool operator!=(iterator other)
-        {
-            return it != other.it;
-        }
-
-        typename T::iterator::value_type item()
-        {
-            return *it;
-        }
-
-        value_type operator*()
-        {
-            return value_type{counter, *it};
-        }
-
-        size_t index()
-        {
-            return counter;
-        }
-
-    private:
-        typename T::iterator it;
-        size_t counter;
-    };
-
-    enumerate_impl(T & t) : container(t) {}
-
-    iterator begin()
-    {
-        return iterator(container.begin());
-    }
-
-    iterator end()
-    {
-        return iterator(container.end());
-    }
-
-private:
-    T & container;
-};
-
-// A templated free function allows you to create the wrapper class
-// conveniently
-template <typename T>
-enumerate_impl<T> enumerate(T & t)
-{
-    return enumerate_impl<T>(t);
-}
-
-class Imu_Integration{
-public:
-    Imu_Integration(Sophus::SE3& SE_init);
-    ~Imu_Integration();
-    bool reset(gtsam::ISAM2& optimizer,boost::shared_ptr<svo::Frame>& new_frame);
-    bool reset(gtsam::LevenbergMarquardtOptimizer& optimizer,boost::shared_ptr<svo::Frame>& new_frame);
-    bool update(double* imu= nullptr);
-    bool predict(boost::shared_ptr<svo::Frame>&,std::size_t&,const double reproj_thresh);
-private:
-    std::shared_ptr<gtsam::NavState> statePtr;
-    std::shared_ptr<gtsam::imuBias::ConstantBias> imu_biasPtr;
-    std::shared_ptr<gtsam::Values> valuesPtr;
-    std::shared_ptr<gtsam::NonlinearFactorGraph> graphPtr;
-    boost::shared_ptr<gtsam::PreintegratedCombinedMeasurements::Params> parameterPtr;
-    std::shared_ptr<gtsam::PreintegratedCombinedMeasurements> preintegratedPtr;
-    boost::shared_ptr<gtsam::noiseModel::Isotropic> ProjectNoisePtr;
-    std::chrono::steady_clock::time_point t_1;
-    std::uint32_t imu_factor_id=0;
-    uint imu_n=0;
-    std::shared_ptr<gtsam::ISAM2Params> optimizerParamPtr;
-    bool syn=false;
-};
-#endif //SVO_IMU_INTEGRATION_H
diff --git a/CPU_version/svo/include/svo/initialization.h b/CPU_version/svo/include/svo/initialization.h
deleted file mode 100644
index cb562e5..0000000
--- a/CPU_version/svo/include/svo/initialization.h
+++ /dev/null
@@ -1,83 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#ifndef SVO_INITIALIZATION_H
-#define SVO_INITIALIZATION_H
-
-#include <svo/global.h>
-
-namespace svo {
-
-class FrameHandlerMono;
-
-/// Bootstrapping the map from the first two views.
-namespace initialization {
-
-enum InitResult { FAILURE, NO_KEYFRAME, SUCCESS };
-
-/// Tracks features using Lucas-Kanade tracker and then estimates a homography.
-class KltHomographyInit {
-  friend class svo::FrameHandlerMono;
-public:
-  EIGEN_MAKE_ALIGNED_OPERATOR_NEW
-
-  FramePtr frame_ref_;
-  KltHomographyInit() {};
-  ~KltHomographyInit() {};
-  InitResult addFirstFrame(FramePtr frame_ref);
-  InitResult addSecondFrame(FramePtr frame_ref);
-  void reset();
-
-protected:
-  vector<cv::Point2f> px_ref_;      //!< keypoints to be tracked in reference frame.
-  vector<cv::Point2f> px_cur_;      //!< tracked keypoints in current frame.
-  vector<Vector3d> f_ref_;          //!< bearing vectors corresponding to the keypoints in the reference image.
-  vector<Vector3d> f_cur_;          //!< bearing vectors corresponding to the keypoints in the current image.
-  vector<double> disparities_;      //!< disparity between first and second frame.
-  vector<int> inliers_;             //!< inliers after the geometric check (e.g., Homography).
-  vector<Vector3d> xyz_in_cur_;     //!< 3D points computed during the geometric check.
-  SE3 T_cur_from_ref_;              //!< computed transformation between the first two frames.
-};
-
-/// Detect Fast corners in the image.
-void detectFeatures(
-    FramePtr frame,
-    vector<cv::Point2f>& px_vec,
-    vector<Vector3d>& f_vec);
-
-/// Compute optical flow (Lucas Kanade) for selected keypoints.
-void trackKlt(
-    FramePtr frame_ref,
-    FramePtr frame_cur,
-    vector<cv::Point2f>& px_ref,
-    vector<cv::Point2f>& px_cur,
-    vector<Vector3d>& f_ref,
-    vector<Vector3d>& f_cur,
-    vector<double>& disparities);
-
-void computeHomography(
-    const vector<Vector3d>& f_ref,
-    const vector<Vector3d>& f_cur,
-    double focal_length,
-    double reprojection_threshold,
-    vector<int>& inliers,
-    vector<Vector3d>& xyz_in_cur,
-    SE3& T_cur_from_ref);
-
-} // namespace initialization
-} // namespace svo
-
-#endif // SVO_INITIALIZATION_H
diff --git a/CPU_version/svo/include/svo/map.h b/CPU_version/svo/include/svo/map.h
deleted file mode 100644
index 458622b..0000000
--- a/CPU_version/svo/include/svo/map.h
+++ /dev/null
@@ -1,136 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#ifndef SVO_MAP_H_
-#define SVO_MAP_H_
-
-#include <queue>
-#include <boost/noncopyable.hpp>
-#include <boost/thread.hpp>
-#include <svo/global.h>
-
-namespace svo {
-
-class Point;
-class Feature;
-class Seed;
-
-/// Container for converged 3D points that are not already assigned to two keyframes.
-class MapPointCandidates
-{
-public:
-  typedef pair<Point*, Feature*> PointCandidate;
-  typedef list<PointCandidate> PointCandidateList;
-
-  /// The depth-filter is running in a parallel thread and fills the canidate list.
-  /// This mutex controls concurrent access to point_candidates.
-  boost::mutex mut_;
-
-  /// Candidate points are created from converged seeds.
-  /// Until the next keyframe, these points can be used for reprojection and pose optimization.
-  PointCandidateList candidates_;
-  list< Point* > trash_points_;
-
-  MapPointCandidates();
-  ~MapPointCandidates();
-
-  /// Add a candidate point.
-  void newCandidatePoint(Point* point, double depth_sigma2);
-
-  /// Adds the feature to the frame and deletes candidate from list.
-  void addCandidatePointToFrame(FramePtr frame);
-
-  /// Remove a candidate point from the list of candidates.
-  bool deleteCandidatePoint(Point* point);
-
-  /// Remove all candidates that belong to a frame.
-  void removeFrameCandidates(FramePtr frame);
-
-  /// Reset the candidate list, remove and delete all points.
-  void reset();
-
-  void deleteCandidate(PointCandidate& c);
-
-  void emptyTrash();
-};
-
-/// Map object which saves all keyframes which are in a map.
-class Map : boost::noncopyable
-{
-public:
-  list< FramePtr > keyframes_;          //!< List of keyframes in the map.
-  list< Point* > trash_points_;         //!< A deleted point is moved to the trash bin. Now and then this is cleaned. One reason is that the visualizer must remove the points also.
-  MapPointCandidates point_candidates_;
-
-  Map();
-  ~Map();
-
-  /// Reset the map. Delete all keyframes and reset the frame and point counters.
-  void reset();
-
-  /// Delete a point in the map and remove all references in keyframes to it.
-  void safeDeletePoint(Point* pt);
-
-  /// Moves the point to the trash queue which is cleaned now and then.
-  void deletePoint(Point* pt);
-
-  /// Moves the frame to the trash queue which is cleaned now and then.
-  bool safeDeleteFrame(FramePtr frame);
-
-  /// Remove the references between a point and a frame.
-  void removePtFrameRef(Frame* frame, Feature* ftr);
-
-  /// Add a new keyframe to the map.
-  void addKeyframe(FramePtr new_keyframe);
-
-  /// Given a frame, return all keyframes which have an overlapping field of view.
-  void getCloseKeyframes(const FramePtr& frame, list< pair<FramePtr,double> >& close_kfs) const;
-
-  /// Return the keyframe which is spatially closest and has overlapping field of view.
-  FramePtr getClosestKeyframe(const FramePtr& frame) const;
-
-  /// Return the keyframe which is furthest apart from pos.
-  FramePtr getFurthestKeyframe(const Vector3d& pos) const;
-
-  bool getKeyframeById(const int id, FramePtr& frame) const;
-
-  /// Transform the whole map with rotation R, translation t and scale s.
-  void transform(const Matrix3d& R, const Vector3d& t, const double& s);
-
-  /// Empty trash bin of deleted keyframes and map points. We don't delete the
-  /// points immediately to ensure proper cleanup and to provide the visualizer
-  /// a list of objects which must be removed.
-  void emptyTrash();
-
-  /// Return the keyframe which was last inserted in the map.
-  inline FramePtr lastKeyframe() { return keyframes_.back(); }
-
-  /// Return the number of keyframes in the map
-  inline size_t size() const { return keyframes_.size(); }
-};
-
-/// A collection of debug functions to check the data consistency.
-namespace map_debug {
-
-void mapStatistics(Map* map);
-void mapValidation(Map* map, int id);
-void frameValidation(Frame* frame, int id);
-void pointValidation(Point* point, int id);
-
-} // namespace map_debug
-} // namespace svo
-
-#endif // SVO_MAP_H_
diff --git a/CPU_version/svo/include/svo/matcher.h b/CPU_version/svo/include/svo/matcher.h
deleted file mode 100644
index b53340e..0000000
--- a/CPU_version/svo/include/svo/matcher.h
+++ /dev/null
@@ -1,130 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#ifndef SVO_MATCHER_H_
-#define SVO_MATCHER_H_
-
-#include <svo/global.h>
-
-namespace vk {
-  class AbstractCamera;
-  namespace patch_score {
-    template<int HALF_PATCH_SIZE> class ZMSSD;
-  }
-}
-
-namespace svo {
-
-class Point;
-class Frame;
-class Feature;
-
-/// Warp a patch from the reference view to the current view.
-namespace warp {
-
-void getWarpMatrixAffine(
-    const vk::AbstractCamera& cam_ref,
-    const vk::AbstractCamera& cam_cur,
-    const Vector2d& px_ref,
-    const Vector3d& f_ref,
-    const double depth_ref,
-    const SE3& T_cur_ref,
-    const int level_ref,
-    Matrix2d& A_cur_ref);
-
-int getBestSearchLevel(
-    const Matrix2d& A_cur_ref,
-    const int max_level);
-
-void warpAffine(
-    const Matrix2d& A_cur_ref,
-    const cv::Mat& img_ref,
-    const Vector2d& px_ref,
-    const int level_ref,
-    const int level_cur,
-    const int halfpatch_size,
-    uint8_t* patch);
-
-} // namespace warp
-
-/// Patch-matcher for reprojection-matching and epipolar search in triangulation.
-class Matcher
-{
-public:
-  EIGEN_MAKE_ALIGNED_OPERATOR_NEW
-
-  static const int halfpatch_size_ = 4;
-  static const int patch_size_ = 8;
-
-  typedef vk::patch_score::ZMSSD<halfpatch_size_> PatchScore;
-
-  struct Options
-  {
-    bool align_1d;              //!< in epipolar search: align patch 1D along epipolar line
-    int align_max_iter;         //!< number of iterations for aligning the feature patches in gauss newton
-    double max_epi_length_optim;//!< max length of epipolar line to skip epipolar search and directly go to img align
-    size_t max_epi_search_steps;//!< max number of evaluations along epipolar line
-    bool subpix_refinement;     //!< do gauss newton feature patch alignment after epipolar search
-    bool epi_search_edgelet_filtering;
-    double epi_search_edgelet_max_angle;
-    Options() :
-      align_1d(false),
-      align_max_iter(10),
-      max_epi_length_optim(2.0),
-      max_epi_search_steps(1000),
-      subpix_refinement(true),
-      epi_search_edgelet_filtering(true),
-      epi_search_edgelet_max_angle(0.7)
-    {}
-  } options_;
-
-  uint8_t patch_[patch_size_*patch_size_] __attribute__ ((aligned (16)));
-  uint8_t patch_with_border_[(patch_size_+2)*(patch_size_+2)] __attribute__ ((aligned (16)));
-  Matrix2d A_cur_ref_;          //!< affine warp matrix
-  Vector2d epi_dir_;
-  double epi_length_;           //!< length of epipolar line segment in pixels (only used for epipolar search)
-  double h_inv_;                //!< hessian of 1d image alignment along epipolar line
-  int search_level_;
-  bool reject_;
-  Feature* ref_ftr_;
-  Vector2d px_cur_;
-
-  Matcher() = default;
-  ~Matcher() = default;
-
-  /// Find a match by directly applying subpix refinement.
-  /// IMPORTANT! This function assumes that px_cur is already set to an estimate that is within ~2-3 pixel of the final result!
-  bool findMatchDirect(
-      const Point& pt,
-      const Frame& frame,
-      Vector2d& px_cur);
-
-  /// Find a match by searching along the epipolar line without using any features.
-  bool findEpipolarMatchDirect(
-      const Frame& ref_frame,
-      const Frame& cur_frame,
-      const Feature& ref_ftr,
-      const double d_estimate,
-      const double d_min,
-      const double d_max,
-      double& depth);
-
-  void createPatchFromPatchWithBorder();
-};
-
-} // namespace svo
-
-#endif // SVO_MATCHER_H_
diff --git a/CPU_version/svo/include/svo/point.h b/CPU_version/svo/include/svo/point.h
deleted file mode 100644
index e1bb81b..0000000
--- a/CPU_version/svo/include/svo/point.h
+++ /dev/null
@@ -1,108 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#ifndef SVO_POINT_H_
-#define SVO_POINT_H_
-
-#include <boost/noncopyable.hpp>
-#include <svo/global.h>
-
-namespace g2o {
-  class VertexSBAPointXYZ;
-}
-typedef g2o::VertexSBAPointXYZ g2oPoint;
-
-namespace svo {
-
-class Feature;
-
-typedef Matrix<double, 2, 3> Matrix23d;
-
-/// A 3D point on the surface of the scene.
-class Point : boost::noncopyable
-{
-public:
-  EIGEN_MAKE_ALIGNED_OPERATOR_NEW
-  
-  enum PointType {
-    TYPE_DELETED,
-    TYPE_CANDIDATE,
-    TYPE_UNKNOWN,
-    TYPE_GOOD
-  };
-
-  static int                  point_counter_;           //!< Counts the number of created points. Used to set the unique id.
-  int                         id_;                      //!< Unique ID of the point.
-  Vector3d                    pos_;                     //!< 3d pos of the point in the world coordinate frame.
-  Vector3d                    normal_;                  //!< Surface normal at point.
-  Matrix3d                    normal_information_;      //!< Inverse covariance matrix of normal estimation.
-  bool                        normal_set_;              //!< Flag whether the surface normal was estimated or not.
-  list<Feature*>              obs_;                     //!< References to keyframes which observe the point.
-  size_t                      n_obs_;                   //!< Number of obervations: Keyframes AND successful reprojections in intermediate frames.
-  g2oPoint*                   v_pt_;                    //!< Temporary pointer to the point-vertex in g2o during bundle adjustment.
-  int                         last_published_ts_;       //!< Timestamp of last publishing.
-  int                         last_projected_kf_id_;    //!< Flag for the reprojection: don't reproject a pt twice.
-  PointType                   type_;                    //!< Quality of the point.
-  int                         n_failed_reproj_;         //!< Number of failed reprojections. Used to assess the quality of the point.
-  int                         n_succeeded_reproj_;      //!< Number of succeeded reprojections. Used to assess the quality of the point.
-  int                         last_structure_optim_;    //!< Timestamp of last point optimization
-
-  Point(const Vector3d& pos);
-  Point(const Vector3d& pos, Feature* ftr);
-  ~Point();
-
-  /// Add a reference to a frame.
-  void addFrameRef(Feature* ftr);
-
-  /// Remove reference to a frame.
-  bool deleteFrameRef(Frame* frame);
-
-  /// Initialize point normal. The inital estimate will point towards the frame.
-  void initNormal();
-
-  /// Check whether mappoint has reference to a frame.
-  Feature* findFrameRef(Frame* frame);
-
-  /// Get Frame with similar viewpoint.
-  bool getCloseViewObs(const Vector3d& pos, Feature*& obs) const;
-
-  /// Get number of observations.
-  inline size_t nRefs() const { return obs_.size(); }
-
-  /// Optimize point position through minimizing the reprojection error.
-  void optimize(const size_t n_iter);
-
-  /// Jacobian of point projection on unit plane (focal length = 1) in frame (f).
-  inline static void jacobian_xyz2uv(
-      const Vector3d& p_in_f,
-      const Matrix3d& R_f_w,
-      Matrix23d& point_jac)
-  {
-    const double z_inv = 1.0/p_in_f[2];
-    const double z_inv_sq = z_inv*z_inv;
-    point_jac(0, 0) = z_inv;
-    point_jac(0, 1) = 0.0;
-    point_jac(0, 2) = -p_in_f[0] * z_inv_sq;
-    point_jac(1, 0) = 0.0;
-    point_jac(1, 1) = z_inv;
-    point_jac(1, 2) = -p_in_f[1] * z_inv_sq;
-    point_jac = - point_jac * R_f_w;
-  }
-};
-
-} // namespace svo
-
-#endif // SVO_POINT_H_
diff --git a/CPU_version/svo/include/svo/pose_optimizer.h b/CPU_version/svo/include/svo/pose_optimizer.h
deleted file mode 100644
index ca048ae..0000000
--- a/CPU_version/svo/include/svo/pose_optimizer.h
+++ /dev/null
@@ -1,50 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#ifndef SVO_POSE_OPTIMIZER_H_
-#define SVO_POSE_OPTIMIZER_H_
-
-#include <svo/global.h>
-
-namespace svo {
-
-using namespace Eigen;
-using namespace Sophus;
-using namespace std;
-
-typedef Matrix<double,6,6> Matrix6d;
-typedef Matrix<double,2,6> Matrix26d;
-typedef Matrix<double,6,1> Vector6d;
-
-class Point;
-
-/// Motion-only bundle adjustment. Minimize the reprojection error of a single frame.
-namespace pose_optimizer {
-
-void optimizeGaussNewton(
-    const double reproj_thresh,
-    const size_t n_iter,
-    const bool verbose,
-    FramePtr& frame,
-    double& estimated_scale,
-    double& error_init,
-    double& error_final,
-    size_t& num_obs);
-
-} // namespace pose_optimizer
-} // namespace svo
-
-#endif // SVO_POSE_OPTIMIZER_H_
diff --git a/CPU_version/svo/include/svo/reprojector.h b/CPU_version/svo/include/svo/reprojector.h
deleted file mode 100644
index e345f0d..0000000
--- a/CPU_version/svo/include/svo/reprojector.h
+++ /dev/null
@@ -1,101 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#ifndef SVO_REPROJECTION_H_
-#define SVO_REPROJECTION_H_
-
-#include <svo/global.h>
-#include <svo/matcher.h>
-
-namespace vk {
-class AbstractCamera;
-}
-
-namespace svo {
-
-class Map;
-class Point;
-
-/// Project points from the map into the image and find the corresponding
-/// feature (corner). We don't search a match for every point but only for one
-/// point per cell. Thereby, we achieve a homogeneously distributed set of
-/// matched features and at the same time we can save processing time by not
-/// projecting all points.
-class Reprojector
-{
-public:
-  EIGEN_MAKE_ALIGNED_OPERATOR_NEW
-
-  /// Reprojector config parameters
-  struct Options {
-    size_t max_n_kfs;   //!< max number of keyframes to reproject from
-    bool find_match_direct;
-    Options()
-    : max_n_kfs(10),
-      find_match_direct(true)
-    {}
-  } options_;
-
-  size_t n_matches_;
-  size_t n_trials_;
-
-  Reprojector(vk::AbstractCamera* cam, Map& map);
-
-  ~Reprojector();
-
-  /// Project points from the map into the image. First finds keyframes with
-  /// overlapping field of view and projects only those map-points.
-  void reprojectMap(
-      FramePtr frame,
-      std::vector< std::pair<FramePtr,std::size_t> >& overlap_kfs);
-
-private:
-
-  /// A candidate is a point that projects into the image plane and for which we
-  /// will search a maching feature in the image.
-  struct Candidate {
-    EIGEN_MAKE_ALIGNED_OPERATOR_NEW
-    Point* pt;       //!< 3D point.
-    Vector2d px;     //!< projected 2D pixel location.
-    Candidate(Point* pt, Vector2d& px) : pt(pt), px(px) {}
-  };
-  typedef std::list<Candidate > Cell;
-  typedef std::vector<Cell*> CandidateGrid;
-
-  /// The grid stores a set of candidate matches. For every grid cell we try to find one match.
-  struct Grid
-  {
-    CandidateGrid cells;
-    vector<int> cell_order;
-    int cell_size;
-    int grid_n_cols;
-    int grid_n_rows;
-  };
-
-  Grid grid_;
-  Matcher matcher_;
-  Map& map_;
-
-  static bool pointQualityComparator(Candidate& lhs, Candidate& rhs);
-  void initializeGrid(vk::AbstractCamera* cam);
-  void resetGrid();
-  bool reprojectCell(Cell& cell, FramePtr frame);
-  bool reprojectPoint(FramePtr frame, Point* point);
-};
-
-} // namespace svo
-
-#endif // SVO_REPROJECTION_H_
diff --git a/CPU_version/svo/include/svo/sparse_img_align.h b/CPU_version/svo/include/svo/sparse_img_align.h
deleted file mode 100644
index 1bedfed..0000000
--- a/CPU_version/svo/include/svo/sparse_img_align.h
+++ /dev/null
@@ -1,83 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#ifndef SVO_SPARSE_IMG_ALIGN_H_
-#define SVO_SPARSE_IMG_ALIGN_H_
-
-#include <vikit/nlls_solver.h>
-#include <vikit/performance_monitor.h>
-#include <svo/global.h>
-
-namespace vk {
-class AbstractCamera;
-}
-
-namespace svo {
-
-class Feature;
-
-/// Optimize the pose of the frame by minimizing the photometric error of feature patches.
-class SparseImgAlign : public vk::NLLSSolver<6, SE3>
-{
-  static const int patch_halfsize_ = 2;
-  static const int patch_size_ = 2*patch_halfsize_;
-  static const int patch_area_ = patch_size_*patch_size_;
-public:
-  EIGEN_MAKE_ALIGNED_OPERATOR_NEW
-
-  cv::Mat resimg_;
-
-  SparseImgAlign(
-      int n_levels,
-      int min_level,
-      int n_iter,
-      Method method,
-      bool display,
-      bool verbose);
-
-  size_t run(
-      FramePtr ref_frame,
-      FramePtr cur_frame);
-
-  /// Return fisher information matrix, i.e. the Hessian of the log-likelihood
-  /// at the converged state.
-  Matrix<double, 6, 6> getFisherInformation();
-
-protected:
-  FramePtr ref_frame_;            //!< reference frame, has depth for gradient pixels.
-  FramePtr cur_frame_;            //!< only the image is known!
-  int level_;                     //!< current pyramid level on which the optimization runs.
-  bool display_;                  //!< display residual image.
-  int max_level_;                 //!< coarsest pyramid level for the alignment.
-  int min_level_;                 //!< finest pyramid level for the alignment.
-
-  // cache:
-  Matrix<double, 6, Dynamic, ColMajor> jacobian_cache_;
-  bool have_ref_patch_cache_;
-  cv::Mat ref_patch_cache_;
-  std::vector<bool> visible_fts_;
-
-  void precomputeReferencePatches();
-  virtual double computeResiduals(const SE3& model, bool linearize_system, bool compute_weight_scale = false);
-  virtual int solve();
-  virtual void update (const ModelType& old_model, ModelType& new_model);
-  virtual void startIteration();
-  virtual void finishIteration();
-};
-
-} // namespace svo
-
-#endif // SVO_SPARSE_IMG_ALIGN_H_
diff --git a/CPU_version/svo/include/svo/svoVisionFactor.h b/CPU_version/svo/include/svo/svoVisionFactor.h
deleted file mode 100644
index cd00816..0000000
--- a/CPU_version/svo/include/svo/svoVisionFactor.h
+++ /dev/null
@@ -1,70 +0,0 @@
-//
-// Created by root on 4/13/21.
-//
-
-#ifndef SVO_SVOVISIONFACTOR_H
-#define SVO_SVOVISIONFACTOR_H
-#pragma once
-
-#include <gtsam/nonlinear/NonlinearFactor.h>
-#include <gtsam/base/Matrix.h>
-#include <gtsam/base/Vector.h>
-#include <gtsam/geometry/Pose3.h>
-#include <vikit/robust_cost.h>
-#include <vikit/math_utils.h>
-#include <svo/frame.h>
-
-namespace svo {
-
-    class VisionFactor: public gtsam::NoiseModelFactor1<gtsam::Pose3> {
-
-    private:
-        // measurement information
-        gtsam::Point3 feature;   ///<Unit-bearing vector of the feature.
-        gtsam::Point3 landmark;   ///<Unit-bearing vector of the feature.
-        boost::optional<gtsam::Point3> body_P_sensor_; ///< TODO The pose of the sensor in the body frame
-        int level;            ///< Image pyramid level where feature was extracted.
-
-    public:
-        /// shorthand for a smart pointer to a factor
-        typedef boost::shared_ptr<VisionFactor> shared_ptr;
-
-        /**
-        * Constructor
-        * @param feature Unit-bearing vector of the feature.
-        * @param model is the standard deviation
-        * @param pointKey is the index of the landmark
-        * @param poseKey is the index of the camera pose
-        * @param landmark 3D position of the landmark
-        * @param body_P_sensor is the transform from body to sensor frame (default identity)
-        * @param level Image pyramid level where feature was extracted.
-        */
-        VisionFactor(const gtsam::Point3& feature, const gtsam::Point3& landmark,const int level, const gtsam::SharedNoiseModel& Hp,
-                      gtsam::Key poseKey,boost::optional<gtsam::Point3> body_P_sensor = boost::none) :
-                gtsam::NoiseModelFactor1<gtsam::Pose3>(Hp, poseKey), feature(feature), landmark(landmark),body_P_sensor_(body_P_sensor),level(level){}
-        virtual ~VisionFactor(){}
-
-        /// error function
-        /// @param p    the Estimated pose in Pose3
-        /// @param H    the optional Jacobian matrix, which use boost optional and has default null pointer
-        gtsam::Vector evaluateError(const gtsam::Pose3& p, boost::optional<gtsam::Matrix&> Hp = boost::none) const {
-            // note that use boost optional like a pointer
-            // only calculate jacobian matrix when non-null pointer exists
-            gtsam::Matrix26 J;
-            gtsam::Point3 point(p*landmark);
-            svo::Frame::jacobian_xyz2uv(point, J);
-            Vector2d e = (vk::project2d(feature) - vk::project2d(point))*1.0 / (1<<level);
-            if(Hp)(*Hp) = (gtsam::Matrix(2,6)<< J * 1.0 / (1<<level)).finished();
-            return e;
-        }
-        // The second is a 'clone' function that allows the factor to be copied. Under most
-        // circumstances, the following code that employs the default copy constructor should
-        // work fine.
-        virtual gtsam::NonlinearFactor::shared_ptr clone() const {
-            return boost::static_pointer_cast<gtsam::NonlinearFactor>(
-                    gtsam::NonlinearFactor::shared_ptr(new VisionFactor(*this))); }
-
-    };
-
-} // namespace gtsamexamples
-#endif //SVO_SVOVISIONFACTOR_H
diff --git a/CPU_version/svo/package.xml b/CPU_version/svo/package.xml
deleted file mode 100644
index 4d71cb3..0000000
--- a/CPU_version/svo/package.xml
+++ /dev/null
@@ -1,27 +0,0 @@
-<?xml version="1.0"?>
-<package>
-  <name>svo</name>
-  <version>0.1.0</version>
-  <description>
-    Monocular Visual Odometry
-  </description>
-  <author>Christian Forster</author>
-  <maintainer email="forster@ifi.uzh.ch">Christian Forster</maintainer>
-  <license>GPLv3</license>
-
-  <!-- Dependencies which this package needs to build itself. -->
-  <buildtool_depend>catkin</buildtool_depend>
-
-  <!-- Dependencies needed to compile this package. -->
-  <build_depend>cmake_modules</build_depend> <!-- for FindEigen.cmake -->
-  <build_depend>roscpp</build_depend>
-  <build_depend>roslib</build_depend>
-  <build_depend>vikit_common</build_depend>
-  <build_depend>vikit_ros</build_depend>
-
-  <!-- Dependencies needed after this package is compiled. -->
-  <run_depend>roscpp</run_depend>
-  <run_depend>roslib</run_depend>
-  <run_depend>vikit_common</run_depend>
-  <run_depend>vikit_ros</run_depend>
-</package>
\ No newline at end of file
diff --git a/CPU_version/svo/src/bundle_adjustment.cpp b/CPU_version/svo/src/bundle_adjustment.cpp
deleted file mode 100644
index eaba2b0..0000000
--- a/CPU_version/svo/src/bundle_adjustment.cpp
+++ /dev/null
@@ -1,435 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#include <vikit/math_utils.h>
-#include <boost/thread.hpp>
-#include <g2o/core/sparse_optimizer.h>
-#include <g2o/core/block_solver.h>
-#include <g2o/core/solver.h>
-#include <g2o/core/robust_kernel_impl.h>
-#include <g2o/core/optimization_algorithm_levenberg.h>
-#include <g2o/solvers/cholmod/linear_solver_cholmod.h>
-#include <g2o/solvers/csparse/linear_solver_csparse.h>
-#include <g2o/solvers/dense/linear_solver_dense.h>
-#include <g2o/types/sba/types_six_dof_expmap.h>
-#include <g2o/solvers/structure_only/structure_only_solver.h>
-#include <svo/bundle_adjustment.h>
-#include <svo/frame.h>
-#include <svo/feature.h>
-#include <svo/point.h>
-#include <svo/config.h>
-#include <svo/map.h>
-
-#define SCHUR_TRICK 1
-
-namespace svo {
-namespace ba {
-
-void twoViewBA(
-    Frame* frame1,
-    Frame* frame2,
-    double reproj_thresh,
-    Map* map)
-{
-  // scale reprojection threshold in pixels to unit plane
-  reproj_thresh /= frame1->cam_->errorMultiplier2();
-
-  // init g2o
-  g2o::SparseOptimizer optimizer;
-  setupG2o(&optimizer);
-
-  list<EdgeContainerSE3> edges;
-  size_t v_id = 0;
-
-  // New Keyframe Vertex 1: This Keyframe is set to fixed!
-  g2oFrameSE3* v_frame1 = createG2oFrameSE3(frame1, v_id++, true);
-  optimizer.addVertex(v_frame1);
-
-  // New Keyframe Vertex 2
-  g2oFrameSE3* v_frame2 = createG2oFrameSE3(frame2, v_id++, false);
-  optimizer.addVertex(v_frame2);
-
-  // Create Point Vertices
-  for(Features::iterator it_ftr=frame1->fts_.begin(); it_ftr!=frame1->fts_.end(); ++it_ftr)
-  {
-    Point* pt = (*it_ftr)->point;
-    if(pt == NULL)
-      continue;
-    g2oPoint* v_pt = createG2oPoint(pt->pos_, v_id++, false);
-    optimizer.addVertex(v_pt);
-    pt->v_pt_ = v_pt;
-    g2oEdgeSE3* e = createG2oEdgeSE3(v_frame1, v_pt, vk::project2d((*it_ftr)->f), true, reproj_thresh*Config::lobaRobustHuberWidth());
-    optimizer.addEdge(e);
-    edges.push_back(EdgeContainerSE3(e, frame1, *it_ftr)); // TODO feature now links to frame, so we can simplify edge container!
-
-    // find at which index the second frame observes the point
-    Feature* ftr_frame2 = pt->findFrameRef(frame2);
-    e = createG2oEdgeSE3(v_frame2, v_pt, vk::project2d(ftr_frame2->f), true, reproj_thresh*Config::lobaRobustHuberWidth());
-    optimizer.addEdge(e);
-    edges.push_back(EdgeContainerSE3(e, frame2, ftr_frame2));
-  }
-
-  // Optimization
-  double init_error, final_error;
-  runSparseBAOptimizer(&optimizer, Config::lobaNumIter(), init_error, final_error);
-  printf("2-View BA: Error before/after = %f / %f\n", init_error, final_error);
-
-  // Update Keyframe Positions
-  frame1->T_f_w_.rotation_matrix() = v_frame1->estimate().rotation().toRotationMatrix();
-  frame1->T_f_w_.translation() = v_frame1->estimate().translation();
-  frame2->T_f_w_.rotation_matrix() = v_frame2->estimate().rotation().toRotationMatrix();
-  frame2->T_f_w_.translation() = v_frame2->estimate().translation();
-
-  // Update Mappoint Positions
-  for(Features::iterator it=frame1->fts_.begin(); it!=frame1->fts_.end(); ++it)
-  {
-    if((*it)->point == NULL)
-     continue;
-    (*it)->point->pos_ = (*it)->point->v_pt_->estimate();
-    (*it)->point->v_pt_ = NULL;
-  }
-
-  // Find Mappoints with too large reprojection error
-  const double reproj_thresh_squared = reproj_thresh*reproj_thresh;
-  size_t n_incorrect_edges = 0;
-  for(list<EdgeContainerSE3>::iterator it_e = edges.begin(); it_e != edges.end(); ++it_e)
-    if(it_e->edge->chi2() > reproj_thresh_squared)
-    {
-      if(it_e->feature->point != NULL)
-      {
-        map->safeDeletePoint(it_e->feature->point);
-        it_e->feature->point = NULL;
-      }
-      ++n_incorrect_edges;
-    }
-
-  printf("2-View BA: Wrong edges =  %zu\n", n_incorrect_edges);
-}
-
-void localBA(
-    Frame* center_kf,
-    set<FramePtr>* core_kfs,
-    Map* map,
-    size_t& n_incorrect_edges_1,
-    size_t& n_incorrect_edges_2,
-    double& init_error,
-    double& final_error)
-{
-
-  // init g2o
-  g2o::SparseOptimizer optimizer;
-  setupG2o(&optimizer);
-
-  list<EdgeContainerSE3> edges;
-  set<Point*> mps;
-  list<Frame*> neib_kfs;
-  size_t v_id = 0;
-  size_t n_mps = 0;
-  size_t n_fix_kfs = 0;
-  size_t n_var_kfs = 1;
-  size_t n_edges = 0;
-  n_incorrect_edges_1 = 0;
-  n_incorrect_edges_2 = 0;
-
-  // Add all core keyframes
-  for(set<FramePtr>::iterator it_kf = core_kfs->begin(); it_kf != core_kfs->end(); ++it_kf)
-  {
-    g2oFrameSE3* v_kf = createG2oFrameSE3(it_kf->get(), v_id++, false);
-    (*it_kf)->v_kf_ = v_kf;
-    ++n_var_kfs;
-    assert(optimizer.addVertex(v_kf));
-
-    // all points that the core keyframes observe are also optimized:
-    for(Features::iterator it_pt=(*it_kf)->fts_.begin(); it_pt!=(*it_kf)->fts_.end(); ++it_pt)
-      if((*it_pt)->point != NULL)
-        mps.insert((*it_pt)->point);
-  }
-
-  // Now go throug all the points and add a measurement. Add a fixed neighbour
-  // Keyframe if it is not in the set of core kfs
-  double reproj_thresh_2 = Config::lobaThresh() / center_kf->cam_->errorMultiplier2();
-  double reproj_thresh_1 = Config::poseOptimThresh() / center_kf->cam_->errorMultiplier2();
-  double reproj_thresh_1_squared = reproj_thresh_1*reproj_thresh_1;
-  for(set<Point*>::iterator it_pt = mps.begin(); it_pt!=mps.end(); ++it_pt)
-  {
-    // Create point vertex
-    g2oPoint* v_pt = createG2oPoint((*it_pt)->pos_, v_id++, false);
-    (*it_pt)->v_pt_ = v_pt;
-    assert(optimizer.addVertex(v_pt));
-    ++n_mps;
-
-    // Add edges
-    list<Feature*>::iterator it_obs=(*it_pt)->obs_.begin();
-    while(it_obs!=(*it_pt)->obs_.end())
-    {
-      Vector2d error = vk::project2d((*it_obs)->f) - vk::project2d((*it_obs)->frame->w2f((*it_pt)->pos_));
-
-      if((*it_obs)->frame->v_kf_ == NULL)
-      {
-        // frame does not have a vertex yet -> it belongs to the neib kfs and
-        // is fixed. create one:
-        g2oFrameSE3* v_kf = createG2oFrameSE3((*it_obs)->frame, v_id++, true);
-        (*it_obs)->frame->v_kf_ = v_kf;
-        ++n_fix_kfs;
-        assert(optimizer.addVertex(v_kf));
-        neib_kfs.push_back((*it_obs)->frame);
-      }
-
-      // create edge
-      g2oEdgeSE3* e = createG2oEdgeSE3((*it_obs)->frame->v_kf_, v_pt,
-                                       vk::project2d((*it_obs)->f),
-                                       true,
-                                       reproj_thresh_2*Config::lobaRobustHuberWidth(),
-                                       1.0 / (1<<(*it_obs)->level));
-      assert(optimizer.addEdge(e));
-      edges.push_back(EdgeContainerSE3(e, (*it_obs)->frame, *it_obs));
-      ++n_edges;
-      ++it_obs;
-    }
-  }
-
-  // structure only
-  g2o::StructureOnlySolver<3> structure_only_ba;
-  g2o::OptimizableGraph::VertexContainer points;
-  for (g2o::OptimizableGraph::VertexIDMap::const_iterator it = optimizer.vertices().begin(); it != optimizer.vertices().end(); ++it)
-  {
-    g2o::OptimizableGraph::Vertex* v = static_cast<g2o::OptimizableGraph::Vertex*>(it->second);
-      if (v->dimension() == 3 && v->edges().size() >= 2)
-        points.push_back(v);
-  }
-  structure_only_ba.calc(points, 10);
-
-  // Optimization
-  if(Config::lobaNumIter() > 0)
-    runSparseBAOptimizer(&optimizer, Config::lobaNumIter(), init_error, final_error);
-
-  // Update Keyframes
-  for(set<FramePtr>::iterator it = core_kfs->begin(); it != core_kfs->end(); ++it)
-  {
-    (*it)->T_f_w_ = SE3( (*it)->v_kf_->estimate().rotation(),
-                         (*it)->v_kf_->estimate().translation());
-    (*it)->v_kf_ = NULL;
-  }
-
-  for(list<Frame*>::iterator it = neib_kfs.begin(); it != neib_kfs.end(); ++it)
-    (*it)->v_kf_ = NULL;
-
-  // Update Mappoints
-  for(set<Point*>::iterator it = mps.begin(); it != mps.end(); ++it)
-  {
-    (*it)->pos_ = (*it)->v_pt_->estimate();
-    (*it)->v_pt_ = NULL;
-  }
-
-  // Remove Measurements with too large reprojection error
-  double reproj_thresh_2_squared = reproj_thresh_2*reproj_thresh_2;
-  for(list<EdgeContainerSE3>::iterator it = edges.begin(); it != edges.end(); ++it)
-  {
-    if(it->edge->chi2() > reproj_thresh_2_squared) //*(1<<it->feature_->level))
-    {
-      map->removePtFrameRef(it->frame, it->feature);
-      ++n_incorrect_edges_2;
-    }
-  }
-
-  // TODO: delete points and edges!
-  init_error = sqrt(init_error)*center_kf->cam_->errorMultiplier2();
-  final_error = sqrt(final_error)*center_kf->cam_->errorMultiplier2();
-}
-
-void globalBA(Map* map)
-{
-  // init g2o
-  g2o::SparseOptimizer optimizer;
-  setupG2o(&optimizer);
-
-  list<EdgeContainerSE3> edges;
-  list< pair<FramePtr,Feature*> > incorrect_edges;
-
-  // Go through all Keyframes
-  size_t v_id = 0;
-  double reproj_thresh_2 = Config::lobaThresh() / map->lastKeyframe()->cam_->errorMultiplier2();
-  double reproj_thresh_1_squared = Config::poseOptimThresh() / map->lastKeyframe()->cam_->errorMultiplier2();
-  reproj_thresh_1_squared *= reproj_thresh_1_squared;
-  for(list<FramePtr>::iterator it_kf = map->keyframes_.begin();
-      it_kf != map->keyframes_.end(); ++it_kf)
-  {
-    // New Keyframe Vertex
-    g2oFrameSE3* v_kf = createG2oFrameSE3(it_kf->get(), v_id++, false);
-    (*it_kf)->v_kf_ = v_kf;
-    optimizer.addVertex(v_kf);
-    for(Features::iterator it_ftr=(*it_kf)->fts_.begin(); it_ftr!=(*it_kf)->fts_.end(); ++it_ftr)
-    {
-      // for each keyframe add edges to all observed mapoints
-      Point* mp = (*it_ftr)->point;
-      if(mp == NULL)
-        continue;
-      g2oPoint* v_mp = mp->v_pt_;
-      if(v_mp == NULL)
-      {
-        // mappoint-vertex doesn't exist yet. create a new one:
-        v_mp = createG2oPoint(mp->pos_, v_id++, false);
-        mp->v_pt_ = v_mp;
-        optimizer.addVertex(v_mp);
-      }
-
-      // Due to merging of mappoints it is possible that references in kfs suddenly
-      // have a very large reprojection error which may result in distorted results.
-      Vector2d error = vk::project2d((*it_ftr)->f) - vk::project2d((*it_kf)->w2f(mp->pos_));
-      if(error.squaredNorm() > reproj_thresh_1_squared)
-        incorrect_edges.push_back(pair<FramePtr,Feature*>(*it_kf, *it_ftr));
-      else
-      {
-        g2oEdgeSE3* e = createG2oEdgeSE3(v_kf, v_mp, vk::project2d((*it_ftr)->f),
-                                         true,
-                                         reproj_thresh_2*Config::lobaRobustHuberWidth());
-
-        edges.push_back(EdgeContainerSE3(e, it_kf->get(), *it_ftr));
-        optimizer.addEdge(e);
-      }
-    }
-  }
-
-  // Optimization
-  double init_error=0.0, final_error=0.0;
-  if(Config::lobaNumIter() > 0)
-    runSparseBAOptimizer(&optimizer, Config::lobaNumIter(), init_error, final_error);
-
-  // Update Keyframe and MapPoint Positions
-  for(list<FramePtr>::iterator it_kf = map->keyframes_.begin();
-        it_kf != map->keyframes_.end(); ++it_kf)
-  {
-    (*it_kf)->T_f_w_ = SE3( (*it_kf)->v_kf_->estimate().rotation(),
-                            (*it_kf)->v_kf_->estimate().translation());
-    (*it_kf)->v_kf_ = NULL;
-    for(Features::iterator it_ftr=(*it_kf)->fts_.begin(); it_ftr!=(*it_kf)->fts_.end(); ++it_ftr)
-    {
-      Point* mp = (*it_ftr)->point;
-      if(mp == NULL)
-        continue;
-      if(mp->v_pt_ == NULL)
-        continue;       // mp was updated before
-      mp->pos_ = mp->v_pt_->estimate();
-      mp->v_pt_ = NULL;
-    }
-  }
-
-  // Remove Measurements with too large reprojection error
-  for(list< pair<FramePtr,Feature*> >::iterator it=incorrect_edges.begin();
-      it!=incorrect_edges.end(); ++it)
-    map->removePtFrameRef(it->first.get(), it->second);
-
-  double reproj_thresh_2_squared = reproj_thresh_2*reproj_thresh_2;
-  for(list<EdgeContainerSE3>::iterator it = edges.begin(); it != edges.end(); ++it)
-  {
-    if(it->edge->chi2() > reproj_thresh_2_squared)
-    {
-      map->removePtFrameRef(it->frame, it->feature);
-    }
-  }
-}
-
-void setupG2o(g2o::SparseOptimizer * optimizer)
-{
-  // TODO: What's happening with all this HEAP stuff? Memory Leak?
-  optimizer->setVerbose(false);
-
-#if SCHUR_TRICK
-  // solver
-  g2o::BlockSolver_6_3::LinearSolverType* linearSolver;
-  linearSolver = new g2o::LinearSolverCholmod<g2o::BlockSolver_6_3::PoseMatrixType>();
-  //linearSolver = new g2o::LinearSolverCSparse<g2o::BlockSolver_6_3::PoseMatrixType>();
-
-  g2o::BlockSolver_6_3 * solver_ptr = new g2o::BlockSolver_6_3(linearSolver);
-  g2o::OptimizationAlgorithmLevenberg * solver = new g2o::OptimizationAlgorithmLevenberg(solver_ptr);
-#else
-  g2o::BlockSolverX::LinearSolverType * linearSolver;
-  linearSolver = new g2o::LinearSolverCholmod<g2o::BlockSolverX::PoseMatrixType>();
-  //linearSolver = new g2o::LinearSolverCSparse<g2o::BlockSolverX::PoseMatrixType>();
-  g2o::BlockSolverX * solver_ptr = new g2o::BlockSolverX(linearSolver);
-  g2o::OptimizationAlgorithmLevenberg* solver = new g2o::OptimizationAlgorithmLevenberg(solver_ptr);
-#endif
-
-  solver->setMaxTrialsAfterFailure(5);
-  optimizer->setAlgorithm(solver);
-
-  // setup camera
-  g2o::CameraParameters * cam_params = new g2o::CameraParameters(1.0, Vector2d(0.,0.), 0.);
-  cam_params->setId(0);
-  if (!optimizer->addParameter(cam_params)) {
-    assert(false);
-  }
-}
-
-void
-runSparseBAOptimizer(g2o::SparseOptimizer* optimizer,
-                     unsigned int num_iter,
-                     double& init_error, double& final_error)
-{
-  optimizer->initializeOptimization();
-  optimizer->computeActiveErrors();
-  init_error = optimizer->activeChi2();
-  optimizer->optimize(num_iter);
-  final_error = optimizer->activeChi2();
-}
-
-g2oFrameSE3*
-createG2oFrameSE3(Frame* frame, size_t id, bool fixed)
-{
-  g2oFrameSE3* v = new g2oFrameSE3();
-  v->setId(id);
-  v->setFixed(fixed);
-  v->setEstimate(g2o::SE3Quat(frame->T_f_w_.unit_quaternion(), frame->T_f_w_.translation()));
-  return v;
-}
-
-g2oPoint*
-createG2oPoint(Vector3d pos,
-               size_t id,
-               bool fixed)
-{
-  g2oPoint* v = new g2oPoint();
-  v->setId(id);
-#if SCHUR_TRICK
-  v->setMarginalized(true);
-#endif
-  v->setFixed(fixed);
-  v->setEstimate(pos);
-  return v;
-}
-
-g2oEdgeSE3*
-createG2oEdgeSE3( g2oFrameSE3* v_frame,
-                  g2oPoint* v_point,
-                  const Vector2d& f_up,
-                  bool robust_kernel,
-                  double huber_width,
-                  double weight)
-{
-  g2oEdgeSE3* e = new g2oEdgeSE3();
-  e->setVertex(0, dynamic_cast<g2o::OptimizableGraph::Vertex*>(v_point));
-  e->setVertex(1, dynamic_cast<g2o::OptimizableGraph::Vertex*>(v_frame));
-  e->setMeasurement(f_up);
-  e->information() = weight * Eigen::Matrix2d::Identity(2,2);
-  g2o::RobustKernelHuber* rk = new g2o::RobustKernelHuber();      // TODO: memory leak
-  rk->setDelta(huber_width);
-  e->setRobustKernel(rk);
-  e->setParameterId(0, 0); //old: e->setId(v_point->id());
-  return e;
-}
-
-} // namespace ba
-} // namespace svo
diff --git a/CPU_version/svo/src/config.cpp b/CPU_version/svo/src/config.cpp
deleted file mode 100644
index e8475fe..0000000
--- a/CPU_version/svo/src/config.cpp
+++ /dev/null
@@ -1,102 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#ifdef SVO_USE_ROS
-#include <vikit/params_helper.h>
-#endif
-#include <svo/config.h>
-
-namespace svo {
-
-Config::Config() :
-#ifdef SVO_USE_ROS
-    trace_name(vk::getParam<string>("svo/trace_name", "svo")),
-    trace_dir(vk::getParam<string>("svo/trace_dir", "/tmp")),
-    n_pyr_levels(vk::getParam<int>("svo/n_pyr_levels", 3)),
-    use_imu(vk::getParam<bool>("svo/use_imu", false)),
-    core_n_kfs(vk::getParam<int>("svo/core_n_kfs", 3)),
-    map_scale(vk::getParam<double>("svo/map_scale", 1.0)),
-    grid_size(vk::getParam<int>("svo/grid_size", 30)),
-    init_min_disparity(vk::getParam<double>("svo/init_min_disparity", 50.0)),
-    init_min_tracked(vk::getParam<int>("svo/init_min_tracked", 50)),
-    init_min_inliers(vk::getParam<int>("svo/init_min_inliers", 40)),
-    klt_max_level(vk::getParam<int>("svo/klt_max_level", 4)),
-    klt_min_level(vk::getParam<int>("svo/klt_min_level", 2)),
-    reproj_thresh(vk::getParam<double>("svo/reproj_thresh", 2.0)),
-    poseoptim_thresh(vk::getParam<double>("svo/poseoptim_thresh", 2.0)),
-    poseoptim_num_iter(vk::getParam<int>("svo/poseoptim_num_iter", 10)),
-    structureoptim_max_pts(vk::getParam<int>("svo/structureoptim_max_pts", 20)),
-    structureoptim_num_iter(vk::getParam<int>("svo/structureoptim_num_iter", 5)),
-    loba_thresh(vk::getParam<double>("svo/loba_thresh", 2.0)),
-    loba_robust_huber_width(vk::getParam<double>("svo/loba_robust_huber_width", 1.0)),
-    loba_num_iter(vk::getParam<int>("svo/loba_num_iter", 0)),
-    kfselect_mindist(vk::getParam<double>("svo/kfselect_mindist", 0.12)),
-    triang_min_corner_score(vk::getParam<double>("svo/triang_min_corner_score", 20.0)),
-    triang_half_patch_size(vk::getParam<int>("svo/triang_half_patch_size", 4)),
-    subpix_n_iter(vk::getParam<int>("svo/subpix_n_iter", 10)),
-    max_n_kfs(vk::getParam<int>("svo/max_n_kfs", 10)),
-    img_imu_delay(vk::getParam<double>("svo/img_imu_delay", 0.0)),
-    max_fts(vk::getParam<int>("svo/max_fts", 120)),
-    quality_min_fts(vk::getParam<int>("svo/quality_min_fts", 50)),
-    quality_max_drop_fts(vk::getParam<int>("svo/quality_max_drop_fts", 40)),
-    ACC_noise(vk::getParam<double>("svo/ACC_noise", 1e-4)),
-    GYO_noise(vk::getParam<double>("svo/GYO_noise", 1e-4)),
-    iuc(vk::getParam<double>("svo/IUC", 1e-1)),
-    abc(vk::getParam<double>("svo/ABC", 1e-1)),
-    gbc(vk::getParam<double>("svo/GBC", 1e-1)),
-    ebp(vk::getParam<double>("svo/EBP", 1e-2)),
-    nrp(vk::getParam<double>("svo/NRP", 1e-5))
-#else
-    trace_name("svo"),
-    trace_dir("/tmp"),
-    n_pyr_levels(3),
-    use_imu(false),
-    core_n_kfs(3),
-    map_scale(1.0),
-    grid_size(25),
-    init_min_disparity(50.0),
-    init_min_tracked(50),
-    init_min_inliers(40),
-    klt_max_level(4),
-    klt_min_level(2),
-    reproj_thresh(2.0),
-    poseoptim_thresh(2.0),
-    poseoptim_num_iter(10),
-    structureoptim_max_pts(20),
-    structureoptim_num_iter(5),
-    loba_thresh(2.0),
-    loba_robust_huber_width(1.0),
-    loba_num_iter(0),
-    kfselect_mindist(0.12),
-    triang_min_corner_score(20.0),
-    triang_half_patch_size(4),
-    subpix_n_iter(10),
-    max_n_kfs(0),
-    img_imu_delay(0.0),
-    max_fts(120),
-    quality_min_fts(50),
-    quality_max_drop_fts(40)
-#endif
-{}
-
-Config& Config::getInstance()
-{
-  static Config instance; // Instantiated on first use and guaranteed to be destroyed
-  return instance;
-}
-
-} // namespace svo
-
diff --git a/CPU_version/svo/src/depth_filter.cpp b/CPU_version/svo/src/depth_filter.cpp
deleted file mode 100644
index db24408..0000000
--- a/CPU_version/svo/src/depth_filter.cpp
+++ /dev/null
@@ -1,352 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#include <algorithm>
-#include <vikit/math_utils.h>
-#include <vikit/abstract_camera.h>
-#include <vikit/vision.h>
-#include <boost/bind.hpp>
-#include <boost/math/distributions/normal.hpp>
-#include <svo/global.h>
-#include <svo/depth_filter.h>
-#include <svo/frame.h>
-#include <svo/point.h>
-#include <svo/feature.h>
-#include <svo/matcher.h>
-#include <svo/config.h>
-#include <svo/feature_detection.h>
-
-namespace svo {
-
-int Seed::batch_counter = 0;
-int Seed::seed_counter = 0;
-
-Seed::Seed(Feature* ftr, float depth_mean, float depth_min) :
-    batch_id(batch_counter),
-    id(seed_counter++),
-    ftr(ftr),
-    a(10),
-    b(10),
-    mu(1.0/depth_mean),
-    z_range(1.0/depth_min),
-    sigma2(z_range*z_range/36)
-{}
-
-DepthFilter::DepthFilter(feature_detection::DetectorPtr feature_detector, callback_t seed_converged_cb) :
-    feature_detector_(feature_detector),
-    seed_converged_cb_(seed_converged_cb),
-    seeds_updating_halt_(false),
-    thread_(NULL),
-    new_keyframe_set_(false),
-    new_keyframe_min_depth_(0.0),
-    new_keyframe_mean_depth_(0.0)
-{}
-
-DepthFilter::~DepthFilter()
-{
-  stopThread();
-  SVO_INFO_STREAM("DepthFilter destructed.");
-}
-
-void DepthFilter::startThread()
-{
-  thread_ = new boost::thread(&DepthFilter::updateSeedsLoop, this);
-}
-
-void DepthFilter::stopThread()
-{
-  SVO_INFO_STREAM("DepthFilter stop thread invoked.");
-  if(thread_ != NULL)
-  {
-    SVO_INFO_STREAM("DepthFilter interrupt and join thread... ");
-    seeds_updating_halt_ = true;
-    thread_->interrupt();
-    thread_->join();
-    thread_ = NULL;
-  }
-}
-
-void DepthFilter::addFrame(FramePtr frame)
-{
-  if(thread_ != NULL)
-  {
-    {
-      lock_t lock(frame_queue_mut_);
-      if(frame_queue_.size() > 2)
-        frame_queue_.pop();
-      frame_queue_.push(frame);
-    }
-    seeds_updating_halt_ = false;
-    frame_queue_cond_.notify_one();
-  }
-  else
-    updateSeeds(frame);
-}
-
-void DepthFilter::addKeyframe(FramePtr frame, double depth_mean, double depth_min)
-{
-  new_keyframe_min_depth_ = depth_min;
-  new_keyframe_mean_depth_ = depth_mean;
-  if(thread_ != NULL)
-  {
-    new_keyframe_ = frame;
-    new_keyframe_set_ = true;
-    seeds_updating_halt_ = true;
-    frame_queue_cond_.notify_one();
-  }
-  else
-    initializeSeeds(frame);
-}
-
-void DepthFilter::initializeSeeds(FramePtr frame)
-{
-  Features new_features;
-  feature_detector_->setExistingFeatures(frame->fts_);
-  feature_detector_->detect(frame.get(), frame->img_pyr_,
-                            Config::triangMinCornerScore(), new_features);
-
-  // initialize a seed for every new feature
-  seeds_updating_halt_ = true;
-  lock_t lock(seeds_mut_); // by locking the updateSeeds function stops
-  ++Seed::batch_counter;
-  std::for_each(new_features.begin(), new_features.end(), [&](Feature* ftr){
-    seeds_.push_back(Seed(ftr, new_keyframe_mean_depth_, new_keyframe_min_depth_));
-  });
-
-  if(options_.verbose)
-    SVO_INFO_STREAM("DepthFilter: Initialized "<<new_features.size()<<" new seeds");
-  seeds_updating_halt_ = false;
-}
-
-void DepthFilter::removeKeyframe(FramePtr frame)
-{
-  seeds_updating_halt_ = true;
-  lock_t lock(seeds_mut_);
-  std::list<Seed>::iterator it=seeds_.begin();
-  size_t n_removed = 0;
-  while(it!=seeds_.end())
-  {
-    if(it->ftr->frame == frame.get())
-    {
-      it = seeds_.erase(it);
-      ++n_removed;
-    }
-    else
-      ++it;
-  }
-  seeds_updating_halt_ = false;
-}
-
-void DepthFilter::reset()
-{
-  seeds_updating_halt_ = true;
-  {
-    lock_t lock(seeds_mut_);
-    seeds_.clear();
-  }
-  lock_t lock();
-  while(!frame_queue_.empty())
-    frame_queue_.pop();
-  seeds_updating_halt_ = false;
-
-  if(options_.verbose)
-    SVO_INFO_STREAM("DepthFilter: RESET.");
-}
-
-void DepthFilter::updateSeedsLoop()
-{
-  while(!boost::this_thread::interruption_requested())
-  {
-    FramePtr frame;
-    {
-      lock_t lock(frame_queue_mut_);
-      while(frame_queue_.empty() && new_keyframe_set_ == false)
-        frame_queue_cond_.wait(lock);
-      if(new_keyframe_set_)
-      {
-        new_keyframe_set_ = false;
-        seeds_updating_halt_ = false;
-        clearFrameQueue();
-        frame = new_keyframe_;
-      }
-      else
-      {
-        frame = frame_queue_.front();
-        frame_queue_.pop();
-      }
-    }
-    updateSeeds(frame);
-    if(frame->isKeyframe())
-      initializeSeeds(frame);
-  }
-}
-
-void DepthFilter::updateSeeds(FramePtr frame)
-{
-  // update only a limited number of seeds, because we don't have time to do it
-  // for all the seeds in every frame!
-  size_t n_updates=0, n_failed_matches=0, n_seeds = seeds_.size();
-  lock_t lock(seeds_mut_);
-  std::list<Seed>::iterator it=seeds_.begin();
-
-  const double focal_length = frame->cam_->errorMultiplier2();
-  double px_noise = 1.0;
-  double px_error_angle = atan(px_noise/(2.0*focal_length))*2.0; // law of chord (sehnensatz)
-
-  while( it!=seeds_.end())
-  {
-    // set this value true when seeds updating should be interrupted
-    if(seeds_updating_halt_)
-      return;
-
-    // check if seed is not already too old
-    if((Seed::batch_counter - it->batch_id) > options_.max_n_kfs) {
-      it = seeds_.erase(it);
-      continue;
-    }
-
-    // check if point is visible in the current image
-    SE3 T_ref_cur = it->ftr->frame->T_f_w_ * frame->T_f_w_.inverse();
-    const Vector3d xyz_f(T_ref_cur.inverse()*(1.0/it->mu * it->ftr->f) );
-    if(xyz_f.z() < 0.0)  {
-      ++it; // behind the camera
-      continue;
-    }
-    if(!frame->cam_->isInFrame(frame->f2c(xyz_f).cast<int>())) {
-      ++it; // point does not project in image
-      continue;
-    }
-
-    // we are using inverse depth coordinates
-    float z_inv_min = it->mu + sqrt(it->sigma2);
-    float z_inv_max = max(it->mu - sqrt(it->sigma2), 0.00000001f);
-    double z;
-    if(!matcher_.findEpipolarMatchDirect(
-        *it->ftr->frame, *frame, *it->ftr, 1.0/it->mu, 1.0/z_inv_min, 1.0/z_inv_max, z))
-    {
-      it->b++; // increase outlier probability when no match was found
-      ++it;
-      ++n_failed_matches;
-      continue;
-    }
-
-    // compute tau
-    double tau = computeTau(T_ref_cur, it->ftr->f, z, px_error_angle);
-    double tau_inverse = 0.5 * (1.0/max(0.0000001, z-tau) - 1.0/(z+tau));
-
-    // update the estimate
-    updateSeed(1./z, tau_inverse*tau_inverse, &*it);
-    ++n_updates;
-
-    if(frame->isKeyframe())
-    {
-      // The feature detector should not initialize new seeds close to this location
-      feature_detector_->setGridOccpuancy(matcher_.px_cur_);
-    }
-
-    // if the seed has converged, we initialize a new candidate point and remove the seed
-    if(sqrt(it->sigma2) < it->z_range/options_.seed_convergence_sigma2_thresh)
-    {
-      assert(it->ftr->point == NULL); // TODO this should not happen anymore
-      Vector3d xyz_world(it->ftr->frame->T_f_w_.inverse() * (it->ftr->f * (1.0/it->mu)));
-      Point* point = new Point(xyz_world, it->ftr);
-      it->ftr->point = point;
-      /* FIXME it is not threadsafe to add a feature to the frame here.
-      if(frame->isKeyframe())
-      {
-        Feature* ftr = new Feature(frame.get(), matcher_.px_cur_, matcher_.search_level_);
-        ftr->point = point;
-        point->addFrameRef(ftr);
-        frame->addFeature(ftr);
-        it->ftr->frame->addFeature(it->ftr);
-      }
-      else
-      */
-      {
-        seed_converged_cb_(point, it->sigma2); // put in candidate list
-      }
-      it = seeds_.erase(it);
-    }
-    else if(isnan(z_inv_min))
-    {
-      SVO_WARN_STREAM("z_min is NaN");
-      it = seeds_.erase(it);
-    }
-    else
-      ++it;
-  }
-}
-
-void DepthFilter::clearFrameQueue()
-{
-  while(!frame_queue_.empty())
-    frame_queue_.pop();
-}
-
-void DepthFilter::getSeedsCopy(const FramePtr& frame, std::list<Seed>& seeds)
-{
-  lock_t lock(seeds_mut_);
-  for(std::list<Seed>::iterator it=seeds_.begin(); it!=seeds_.end(); ++it)
-  {
-    if (it->ftr->frame == frame.get())
-      seeds.push_back(*it);
-  }
-}
-
-void DepthFilter::updateSeed(const float x, const float tau2, Seed* seed)
-{
-  float norm_scale = sqrt(seed->sigma2 + tau2);
-  if(std::isnan(norm_scale))
-    return;
-  boost::math::normal_distribution<float> nd(seed->mu, norm_scale);
-  float s2 = 1./(1./seed->sigma2 + 1./tau2);
-  float m = s2*(seed->mu/seed->sigma2 + x/tau2);
-  float C1 = seed->a/(seed->a+seed->b) * boost::math::pdf(nd, x);
-  float C2 = seed->b/(seed->a+seed->b) * 1./seed->z_range;
-  float normalization_constant = C1 + C2;
-  C1 /= normalization_constant;
-  C2 /= normalization_constant;
-  float f = C1*(seed->a+1.)/(seed->a+seed->b+1.) + C2*seed->a/(seed->a+seed->b+1.);
-  float e = C1*(seed->a+1.)*(seed->a+2.)/((seed->a+seed->b+1.)*(seed->a+seed->b+2.))
-          + C2*seed->a*(seed->a+1.0f)/((seed->a+seed->b+1.0f)*(seed->a+seed->b+2.0f));
-
-  // update parameters
-  float mu_new = C1*m+C2*seed->mu;
-  seed->sigma2 = C1*(s2 + m*m) + C2*(seed->sigma2 + seed->mu*seed->mu) - mu_new*mu_new;
-  seed->mu = mu_new;
-  seed->a = (e-f)/(f-e/f);
-  seed->b = seed->a*(1.0f-f)/f;
-}
-
-double DepthFilter::computeTau(
-      const SE3& T_ref_cur,
-      const Vector3d& f,
-      const double z,
-      const double px_error_angle)
-{
-  Vector3d t(T_ref_cur.translation());
-  Vector3d a = f*z-t;
-  double t_norm = t.norm();
-  double a_norm = a.norm();
-  double alpha = acos(f.dot(t)/t_norm); // dot product
-  double beta = acos(a.dot(-t)/(t_norm*a_norm)); // dot product
-  double beta_plus = beta + px_error_angle;
-  double gamma_plus = PI-alpha-beta_plus; // triangle angles sum to PI
-  double z_plus = t_norm*sin(beta_plus)/sin(gamma_plus); // law of sines
-  return (z_plus - z); // tau
-}
-
-} // namespace svo
diff --git a/CPU_version/svo/src/feature_alignment.cpp b/CPU_version/svo/src/feature_alignment.cpp
deleted file mode 100644
index faa4027..0000000
--- a/CPU_version/svo/src/feature_alignment.cpp
+++ /dev/null
@@ -1,601 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#ifdef __SSE2__
-#include <emmintrin.h>
-#endif
-#ifdef __ARM_NEON__
-#include <arm_neon.h>
-#endif
-#include <svo/feature_alignment.h>
-
-namespace svo {
-namespace feature_alignment {
-
-#define SUBPIX_VERBOSE 0
-
-bool align1D(
-    const cv::Mat& cur_img,
-    const Vector2f& dir,                  // direction in which the patch is allowed to move
-    uint8_t* ref_patch_with_border,
-    uint8_t* ref_patch,
-    const int n_iter,
-    Vector2d& cur_px_estimate,
-    double& h_inv)
-{
-  const int halfpatch_size_ = 4;
-  const int patch_size = 8;
-  const int patch_area = 64;
-  bool converged=false;
-
-  // compute derivative of template and prepare inverse compositional
-  float __attribute__((__aligned__(16))) ref_patch_dv[patch_area];
-  Matrix2f H; H.setZero();
-
-  // compute gradient and hessian
-  const int ref_step = patch_size+2;
-  float* it_dv = ref_patch_dv;
-  for(int y=0; y<patch_size; ++y)
-  {
-    uint8_t* it = ref_patch_with_border + (y+1)*ref_step + 1;
-    for(int x=0; x<patch_size; ++x, ++it, ++it_dv)
-    {
-      Vector2f J;
-      J[0] = 0.5*(dir[0]*(it[1] - it[-1]) + dir[1]*(it[ref_step] - it[-ref_step]));
-      J[1] = 1;
-      *it_dv = J[0];
-      H += J*J.transpose();
-    }
-  }
-  h_inv = 1.0/H(0,0)*patch_size*patch_size;
-  Matrix2f Hinv = H.inverse();
-  float mean_diff = 0;
-
-  // Compute pixel location in new image:
-  float u = cur_px_estimate.x();
-  float v = cur_px_estimate.y();
-
-  // termination condition
-  const float min_update_squared = 0.03*0.03;
-  const int cur_step = cur_img.step.p[0];
-  float chi2 = 0;
-  Vector2f update; update.setZero();
-  for(int iter = 0; iter<n_iter; ++iter)
-  {
-    int u_r = floor(u);
-    int v_r = floor(v);
-    if(u_r < halfpatch_size_ || v_r < halfpatch_size_ || u_r >= cur_img.cols-halfpatch_size_ || v_r >= cur_img.rows-halfpatch_size_)
-      break;
-
-    if(isnan(u) || isnan(v)) // TODO very rarely this can happen, maybe H is singular? should not be at corner.. check
-      return false;
-
-    // compute interpolation weights
-    float subpix_x = u-u_r;
-    float subpix_y = v-v_r;
-    float wTL = (1.0-subpix_x)*(1.0-subpix_y);
-    float wTR = subpix_x * (1.0-subpix_y);
-    float wBL = (1.0-subpix_x)*subpix_y;
-    float wBR = subpix_x * subpix_y;
-
-    // loop through search_patch, interpolate
-    uint8_t* it_ref = ref_patch;
-    float* it_ref_dv = ref_patch_dv;
-    float new_chi2 = 0.0;
-    Vector2f Jres; Jres.setZero();
-    for(int y=0; y<patch_size; ++y)
-    {
-      uint8_t* it = (uint8_t*) cur_img.data + (v_r+y-halfpatch_size_)*cur_step + u_r-halfpatch_size_;
-      for(int x=0; x<patch_size; ++x, ++it, ++it_ref, ++it_ref_dv)
-      {
-        float search_pixel = wTL*it[0] + wTR*it[1] + wBL*it[cur_step] + wBR*it[cur_step+1];
-        float res = search_pixel - *it_ref + mean_diff;
-        Jres[0] -= res*(*it_ref_dv);
-        Jres[1] -= res;
-        new_chi2 += res*res;
-      }
-    }
-
-    if(iter > 0 && new_chi2 > chi2)
-    {
-#if SUBPIX_VERBOSE
-      cout << "error increased." << endl;
-#endif
-      u -= update[0];
-      v -= update[1];
-      break;
-    }
-
-    chi2 = new_chi2;
-    update = Hinv * Jres;
-    u += update[0]*dir[0];
-    v += update[0]*dir[1];
-    mean_diff += update[1];
-
-#if SUBPIX_VERBOSE
-    cout << "Iter " << iter << ":"
-         << "\t u=" << u << ", v=" << v
-         << "\t update = " << update[0] << ", " << update[1]
-         << "\t new chi2 = " << new_chi2 << endl;
-#endif
-
-    if(update[0]*update[0]+update[1]*update[1] < min_update_squared)
-    {
-#if SUBPIX_VERBOSE
-      cout << "converged." << endl;
-#endif
-      converged=true;
-      break;
-    }
-  }
-
-  cur_px_estimate << u, v;
-  return converged;
-}
-
-bool align2D(
-    const cv::Mat& cur_img,
-    uint8_t* ref_patch_with_border,
-    uint8_t* ref_patch,
-    const int n_iter,
-    Vector2d& cur_px_estimate,
-    bool no_simd)
-{
-#ifdef __ARM_NEON__
-  if(!no_simd)
-    return align2D_NEON(cur_img, ref_patch_with_border, ref_patch, n_iter, cur_px_estimate);
-#endif
-
-  const int halfpatch_size_ = 4;
-  const int patch_size_ = 8;
-  const int patch_area_ = 64;
-  bool converged=false;
-
-  // compute derivative of template and prepare inverse compositional
-  float __attribute__((__aligned__(16))) ref_patch_dx[patch_area_];
-  float __attribute__((__aligned__(16))) ref_patch_dy[patch_area_];
-  Matrix3f H; H.setZero();
-
-  // compute gradient and hessian
-  const int ref_step = patch_size_+2;
-  float* it_dx = ref_patch_dx;
-  float* it_dy = ref_patch_dy;
-  for(int y=0; y<patch_size_; ++y)
-  {
-    uint8_t* it = ref_patch_with_border + (y+1)*ref_step + 1;
-    for(int x=0; x<patch_size_; ++x, ++it, ++it_dx, ++it_dy)
-    {
-      Vector3f J;
-      J[0] = 0.5 * (it[1] - it[-1]);
-      J[1] = 0.5 * (it[ref_step] - it[-ref_step]);
-      J[2] = 1;
-      *it_dx = J[0];
-      *it_dy = J[1];
-      H += J*J.transpose();
-    }
-  }
-  Matrix3f Hinv = H.inverse();
-  float mean_diff = 0;
-
-  // Compute pixel location in new image:
-  float u = cur_px_estimate.x();
-  float v = cur_px_estimate.y();
-
-  // termination condition
-  const float min_update_squared = 0.03*0.03;
-  const int cur_step = cur_img.step.p[0];
-//  float chi2 = 0;
-  Vector3f update; update.setZero();
-  for(int iter = 0; iter<n_iter; ++iter)
-  {
-    int u_r = floor(u);
-    int v_r = floor(v);
-    if(u_r < halfpatch_size_ || v_r < halfpatch_size_ || u_r >= cur_img.cols-halfpatch_size_ || v_r >= cur_img.rows-halfpatch_size_)
-      break;
-
-    if(isnan(u) || isnan(v)) // TODO very rarely this can happen, maybe H is singular? should not be at corner.. check
-      return false;
-
-    // compute interpolation weights
-    float subpix_x = u-u_r;
-    float subpix_y = v-v_r;
-    float wTL = (1.0-subpix_x)*(1.0-subpix_y);
-    float wTR = subpix_x * (1.0-subpix_y);
-    float wBL = (1.0-subpix_x)*subpix_y;
-    float wBR = subpix_x * subpix_y;
-
-    // loop through search_patch, interpolate
-    uint8_t* it_ref = ref_patch;
-    float* it_ref_dx = ref_patch_dx;
-    float* it_ref_dy = ref_patch_dy;
-//    float new_chi2 = 0.0;
-    Vector3f Jres; Jres.setZero();
-    for(int y=0; y<patch_size_; ++y)
-    {
-      uint8_t* it = (uint8_t*) cur_img.data + (v_r+y-halfpatch_size_)*cur_step + u_r-halfpatch_size_;
-      for(int x=0; x<patch_size_; ++x, ++it, ++it_ref, ++it_ref_dx, ++it_ref_dy)
-      {
-        float search_pixel = wTL*it[0] + wTR*it[1] + wBL*it[cur_step] + wBR*it[cur_step+1];
-        float res = search_pixel - *it_ref + mean_diff;
-        Jres[0] -= res*(*it_ref_dx);
-        Jres[1] -= res*(*it_ref_dy);
-        Jres[2] -= res;
-//        new_chi2 += res*res;
-      }
-    }
-
-
-/*
-    if(iter > 0 && new_chi2 > chi2)
-    {
-#if SUBPIX_VERBOSE
-      cout << "error increased." << endl;
-#endif
-      u -= update[0];
-      v -= update[1];
-      break;
-    }
-    chi2 = new_chi2;
-*/
-    update = Hinv * Jres;
-    u += update[0];
-    v += update[1];
-    mean_diff += update[2];
-
-#if SUBPIX_VERBOSE
-    cout << "Iter " << iter << ":"
-         << "\t u=" << u << ", v=" << v
-         << "\t update = " << update[0] << ", " << update[1]
-//         << "\t new chi2 = " << new_chi2 << endl;
-#endif
-
-    if(update[0]*update[0]+update[1]*update[1] < min_update_squared)
-    {
-#if SUBPIX_VERBOSE
-      cout << "converged." << endl;
-#endif
-      converged=true;
-      break;
-    }
-  }
-
-  cur_px_estimate << u, v;
-  return converged;
-}
-
-#define  DESCALE(x,n)     (((x) + (1 << ((n)-1))) >> (n)) // rounds to closest integer and descales
-
-bool align2D_SSE2(
-    const cv::Mat& cur_img,
-    uint8_t* ref_patch_with_border,
-    uint8_t* ref_patch,
-    const int n_iter,
-    Vector2d& cur_px_estimate)
-{
-  // TODO: This function should not be used as the alignment is not robust to illumination changes!
-  const int halfpatch_size = 4;
-  const int patch_size = 8;
-  const int patch_area = 64;
-  bool converged=false;
-  const int W_BITS = 14;
-
-  // compute derivative of template and prepare inverse compositional
-  int16_t __attribute__((__aligned__(16))) ref_patch_dx[patch_area];
-  int16_t __attribute__((__aligned__(16))) ref_patch_dy[patch_area];
-
-  // compute gradient and hessian
-  const int ref_step = patch_size+2;
-  int16_t* it_dx = ref_patch_dx;
-  int16_t* it_dy = ref_patch_dy;
-  float A11=0, A12=0, A22=0;
-  for(int y=0; y<patch_size; ++y)
-  {
-    uint8_t* it = ref_patch_with_border + (y+1)*ref_step + 1;
-    for(int x=0; x<patch_size; ++x, ++it, ++it_dx, ++it_dy)
-    {
-      int16_t dx = static_cast<int16_t>(it[1]) - it[-1];
-      int16_t dy = static_cast<int16_t>(it[ref_step]) - it[-ref_step];
-      *it_dx = dx;
-      *it_dy = dy;  // we are missing a factor 1/2
-      A11 += static_cast<float>(dx*dx); // we are missing a factor 1/4
-      A12 += static_cast<float>(dx*dy);
-      A22 += static_cast<float>(dy*dy);
-    }
-  }
-
-  // Compute pixel location in new image:
-  float u = cur_px_estimate.x();
-  float v = cur_px_estimate.y();
-
-  // termination condition
-  const float min_update_squared = 0.03*0.03;
-  const int cur_step = cur_img.step.p[0];
-  const float Dinv = 1.0f/(A11*A22 - A12*A12); // we are missing an extra factor 16
-  float chi2 = 0;
-  float update_u = 0, update_v = 0;
-
-  for(int iter = 0; iter<n_iter; ++iter)
-  {
-    int u_r = floor(u);
-    int v_r = floor(v);
-    if(u_r < halfpatch_size || v_r < halfpatch_size || u_r >= cur_img.cols-halfpatch_size || v_r >= cur_img.rows-halfpatch_size)
-      break;
-
-    if(isnan(u) || isnan(v)) // TODO very rarely this can happen, maybe H is singular? should not be at corner.. check
-      return false;
-
-    float subpix_x = u-u_r;
-    float subpix_y = v-v_r;
-    float b1=0, b2=0;
-    float new_chi2 = 0.0;
-
-#ifdef __SSE2__
-    // compute bilinear interpolation weights
-    int wTL = static_cast<int>((1.0f-subpix_x)*(1.0f-subpix_y)*(1 << W_BITS));
-    int wTR = static_cast<int>(subpix_x * (1.0f-subpix_y)*(1 << W_BITS));
-    int wBL = static_cast<int>((1.0f-subpix_x)*subpix_y*(1 << W_BITS));
-    int wBR = (1 << W_BITS) - wTL - wTR - wBL;
-
-    __m128i qw0 = _mm_set1_epi32(wTL + (wTR << 16)); // Sets the 4 signed 32-bit integer values to [wTL, wTR].
-    __m128i qw1 = _mm_set1_epi32(wBL + (wBR << 16));
-    __m128i z = _mm_setzero_si128();
-    __m128 qb0 = _mm_setzero_ps(); // 4 floats
-    __m128 qb1 = _mm_setzero_ps(); // 4 floats
-    __m128i qdelta = _mm_set1_epi32(1 << (W_BITS-1));
-    for(int y=0; y<patch_size; ++y)
-    {
-      const uint8_t* it  = (const uint8_t*) cur_img.data + (v_r+y-halfpatch_size)*cur_step + u_r-halfpatch_size;
-
-      // Iptr is aligned!
-      //__m128i diff0 = _mm_load_si128((const __m128i*)(ref_patch + y*8));
-      __m128i diff = _mm_unpacklo_epi8(_mm_loadl_epi64((const __m128i*)(ref_patch + y*8)), z);
-
-      // load the lower 64 bits and unpack [8u 0 8u 0..]
-      __m128i v00 = _mm_unpacklo_epi8(_mm_loadl_epi64((const __m128i*)(it)), z);
-      __m128i v01 = _mm_unpacklo_epi8(_mm_loadl_epi64((const __m128i*)(it + 1)), z);
-      __m128i v10 = _mm_unpacklo_epi8(_mm_loadl_epi64((const __m128i*)(it + cur_step)), z);
-      __m128i v11 = _mm_unpacklo_epi8(_mm_loadl_epi64((const __m128i*)(it + cur_step + 1)), z);
-
-      // interpolate top row and bottom row
-      // _mm_unpacklo_epi16: Interleaves the lower 4 signed or unsigned 16-bit integers in a with the lower 4 signed or unsigned 16-bit integers in b.
-      // _mm_madd_epi16: Multiplies the 8 signed 16-bit integers from a by the 8 signed 16-bit integers from b.
-      __m128i t0 = _mm_add_epi32(_mm_madd_epi16(_mm_unpacklo_epi16(v00, v01), qw0),
-                                 _mm_madd_epi16(_mm_unpacklo_epi16(v10, v11), qw1));
-      __m128i t1 = _mm_add_epi32(_mm_madd_epi16(_mm_unpackhi_epi16(v00, v01), qw0),
-                                 _mm_madd_epi16(_mm_unpackhi_epi16(v10, v11), qw1));
-
-      // _mm_srai_epi32: Shifts the 4 signed 32-bit integers in A right by count bits while shifting in the sign bit.
-      t0 = _mm_srai_epi32(_mm_add_epi32(t0, qdelta), W_BITS); // adding qdelta is for rounding closest int
-      t1 = _mm_srai_epi32(_mm_add_epi32(t1, qdelta), W_BITS);
-
-      // compute 8xres:
-      // _mm_packs_epi32: Packs the 8 signed 32-bit integers from a and b into signed 16-bit integers and saturates.
-      diff = _mm_subs_epi16(_mm_packs_epi32(t0, t1), diff);
-
-      // load gradient dX and dY, both are aligned!
-      v00 = _mm_load_si128((const __m128i*)(ref_patch_dx + y*patch_size)); // [dx1, dx2, dx3, dx4 ...]
-      v01 = _mm_load_si128((const __m128i*)(ref_patch_dy + y*patch_size)); // [dy1, dy2, dy3, dy4 ...]
-
-      // _mm_mulhi_epi16: Multiplies the 8 signed 16-bit integers from a by the 8 signed 16-bit integers from b.
-      v10 = _mm_mullo_epi16(v00, diff); // Packs the lower 16 bits of the 8 signed 32-bit results. [15:0]
-      v11 = _mm_mulhi_epi16(v00, diff); // Packs the upper 16 bits of the 8 signed 32-bit results. [31:16]
-
-      // _mm_unpacklo_epi16: Interleaves the lower 4 signed or unsigned 16-bit integers with the lower 4 signed or unsigned 16-bit integers in b.
-      v00 = _mm_unpacklo_epi16(v10, v11);
-      v10 = _mm_unpackhi_epi16(v10, v11);
-
-      // convert to float and add to dx
-      qb0 = _mm_add_ps(qb0, _mm_cvtepi32_ps(v00));
-      qb0 = _mm_add_ps(qb0, _mm_cvtepi32_ps(v10));
-
-      // same with dY
-      v10 = _mm_mullo_epi16(v01, diff);
-      v11 = _mm_mulhi_epi16(v01, diff);
-      v00 = _mm_unpacklo_epi16(v10, v11);
-      v10 = _mm_unpackhi_epi16(v10, v11);
-      qb1 = _mm_add_ps(qb1, _mm_cvtepi32_ps(v00));
-      qb1 = _mm_add_ps(qb1, _mm_cvtepi32_ps(v10));
-    }
-
-    float __attribute__((__aligned__(16))) buf[4];
-    _mm_store_ps(buf, qb0);
-    b1 += buf[0]+buf[1]+buf[2]+buf[3];
-    _mm_store_ps(buf, qb1);
-    b2 += buf[0]+buf[1]+buf[2]+buf[3];
-#endif
-
-    // compute -A^-1*b
-    update_u = ((A12*b2 - A22*b1) * Dinv)*2; // * 2 to compensate because above, we did not compute the derivative correctly
-    update_v = ((A12*b1 - A11*b2) * Dinv)*2;
-    u += update_u;
-    v += update_v;
-
-#if SUBPIX_VERBOSE
-    cout << "Iter " << iter << ":"
-         << "\t u=" << u << ", v=" << v
-         << "\t update = " << update_u << ", " << update_v
-         << "\t new chi2 = " << new_chi2 << endl;
-#endif
-
-    if(update_u*update_u+update_v*update_v < min_update_squared)
-    {
-#if SUBPIX_VERBOSE
-      cout << "converged." << endl;
-#endif
-      converged=true;
-      break;
-    }
-    chi2 = new_chi2;
-  }
-
-  cur_px_estimate << u, v;
-  return converged;
-}
-
-bool align2D_NEON (
-    const cv::Mat& cur_img,
-    uint8_t* ref_patch_with_border,
-    uint8_t* ref_patch,
-    const int n_iter,
-    Vector2d& cur_px_estimate)
-{
-  const int halfpatch_size = 4;
-  const int patch_size = 8;
-  const int patch_area = 64;
-  bool converged=false;
-  const int W_BITS = 14;
-
-  // compute derivative of template and prepare inverse compositional
-  int16_t __attribute__((__aligned__(16))) ref_patch_dx[patch_area];
-  int16_t __attribute__((__aligned__(16))) ref_patch_dy[patch_area];
-  
-  // compute gradient and hessian
-  const int ref_step = patch_size+2;
-  int16_t* it_dx = ref_patch_dx;
-  int16_t* it_dy = ref_patch_dy;
-  Matrix3f H; H.setZero();
-  for(int y=0; y<patch_size; ++y)
-  {
-    uint8_t* it = ref_patch_with_border + (y+1)*ref_step + 1;
-    for(int x=0; x<patch_size; ++x, ++it, ++it_dx, ++it_dy)
-    {
-      *it_dx = static_cast<int16_t>(it[1] - it[-1]);
-      *it_dy = static_cast<int16_t>(it[ref_step] - it[-ref_step]); // divide by 2 missing
-      Vector3f J(*it_dx, *it_dy, 1.0f);
-      H += J*J.transpose();
-    }
-  }
-  Matrix3f Hinv = H.inverse();
-  float mean_diff = 0.0;
-
-  // Compute pixel location in new image:
-  float u = cur_px_estimate.x();
-  float v = cur_px_estimate.y();
-
-  // termination condition
-  const float min_update_squared = 0.03*0.03;
-  const int cur_step = cur_img.step.p[0];
-  Vector3f update;
-  Vector3f Jres;
-  for(int iter = 0; iter<n_iter; ++iter)
-  {
-    int u_r = floor(u);
-    int v_r = floor(v);
-    if(u_r < halfpatch_size || v_r < halfpatch_size || u_r >= cur_img.cols-halfpatch_size || v_r >= cur_img.rows-halfpatch_size)
-      break;
-
-    if(isnan(u) || isnan(v)) // TODO very rarely this can happen, maybe H is singular? should not be at corner.. check
-      return false;
-
-    float subpix_x = u-u_r;
-    float subpix_y = v-v_r;
-    float b1=0, b2=0;
-
-#ifdef __ARM_NEON__
-    const int SHIFT_BITS = 7;
-    const uint16_t wTL = static_cast<uint16_t>((1.0f-subpix_x)*(1.0f-subpix_y)*(1<<SHIFT_BITS));
-    const uint16_t wTR = static_cast<uint16_t>(subpix_x*(1.0f-subpix_y)*(1<<SHIFT_BITS));
-    const uint16_t wBL = static_cast<uint16_t>((1.0f-subpix_x)*subpix_y*(1<<SHIFT_BITS));
-    const uint16_t wBR = static_cast<uint16_t>((1 << SHIFT_BITS) - wTL - wTR - wBL);
-
-    // initialize result to zero
-    int32x4_t vb1 = vdupq_n_s32(0);
-    int32x4_t vb2 = vdupq_n_s32(0);
-    int16x8_t vmean_diff = vdupq_n_s16( (int16_t) (mean_diff+0.5) );
-    int16x8_t vres_sum = vdupq_n_s16(0);
-    for(int y=0; y<patch_size; ++y)
-    {
-      const uint8_t* it  = (const uint8_t*) cur_img.data + (v_r+y-halfpatch_size)*cur_step + u_r-halfpatch_size;
-
-      // load and convert from uint8 to uint16
-      uint16x8_t v00 = vmovl_u8( vld1_u8( it ) );
-      uint16x8_t v01 = vmovl_u8( vld1_u8( it + 1 ) );
-      uint16x8_t v10 = vmovl_u8( vld1_u8( it + cur_step ) );
-      uint16x8_t v11 = vmovl_u8( vld1_u8( it + cur_step + 1 ) );
-
-      // vector multiply by scalar
-      v00 = vmulq_n_u16( v00, wTL );
-      v01 = vmulq_n_u16( v01, wTR );
-      v10 = vmulq_n_u16( v10, wBL );
-      v11 = vmulq_n_u16( v11, wBR );
-
-      // add all results together
-      v00 = vaddq_u16( v00, vaddq_u16( v01, vaddq_u16( v10, v11 ) ) );
-
-      // descale: shift right by constant
-      v00 = vshrq_n_u16(v00, SHIFT_BITS);
-
-      // compute difference between reference and interpolated patch,
-      // use reinterpet-cast to make signed [-255,255]
-      int16x8_t res = vsubq_s16(vreinterpretq_s16_u16(v00), vreinterpretq_s16_u16(vmovl_u8(vld1_u8( ref_patch + y*8 ))));
-
-      // correct res with mean difference
-      res = vaddq_s16(res, vmean_diff);
-
-      // compute sum of the residual
-      vres_sum = vaddq_s16(vres_sum, res); 
-
-      // Vector multiply accumulate long: vmla -> Vr[i] := Va[i] + Vb[i] * Vc[i]
-      // int32x4_t  vmlal_s16(int32x4_t a, int16x4_t b, int16x4_t c);    // VMLAL.S16 q0,d0,d0
-      int16x8_t grad = vld1q_s16(ref_patch_dx + y*patch_size);
-      vb1 = vmlal_s16(vb1, vget_low_s16(grad), vget_low_s16(res));
-      vb1 = vmlal_s16(vb1, vget_high_s16(grad), vget_high_s16(res));
-
-      grad = vld1q_s16(ref_patch_dy + y*patch_size);
-      vb2 = vmlal_s16(vb2, vget_low_s16(grad), vget_low_s16(res));
-      vb2 = vmlal_s16(vb2, vget_high_s16(grad), vget_high_s16(res));
-    }
-
-    // finally, sum results of vb1, vb2 and vres_sum
-    int32x2_t tmp;
-    tmp = vpadd_s32(vget_low_s32(vb1), vget_high_s32(vb1));
-    Jres[0] = -vget_lane_s32(tmp, 0) - vget_lane_s32(tmp, 1);
-
-    tmp = vpadd_s32(vget_low_s32(vb2), vget_high_s32(vb2));
-    Jres[1] = -vget_lane_s32(tmp, 0) - vget_lane_s32(tmp, 1);
-
-    int32x4_t vres_sum1 = vpaddlq_s16(vres_sum);
-    tmp = vpadd_s32(vget_low_s32(vres_sum1), vget_high_s32(vres_sum1));
-    Jres[2] = -vget_lane_s32(tmp, 0) - vget_lane_s32(tmp, 1);
-#endif
-
-    update = Hinv * Jres * 2; // * 2 to compensate because above, we did not compute the derivative correctly
-    u += update[0];
-    v += update[1];
-    mean_diff += update[2];
-
-#if SUBPIX_VERBOSE
-    cout << "Iter " << iter << ":"
-         << "\t u=" << u << ", v=" << v
-         << "\t update = " << update[0] << ", " << update[1] << endl;
-#endif
-
-    if(update[0]*update[0]+update[1]*update[1] < min_update_squared)
-    {
-#if SUBPIX_VERBOSE
-      cout << "converged." << endl;
-#endif
-      converged=true;
-      break;
-    }
-  }
-
-  cur_px_estimate << u, v;
-  return converged;
-}
-
-} // namespace feature_alignment
-} // namespace svo
diff --git a/CPU_version/svo/src/feature_detection.cpp b/CPU_version/svo/src/feature_detection.cpp
deleted file mode 100644
index 98183f8..0000000
--- a/CPU_version/svo/src/feature_detection.cpp
+++ /dev/null
@@ -1,118 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#include <svo/feature_detection.h>
-#include <svo/feature.h>
-#include <fast/fast.h>
-#include <vikit/vision.h>
-
-namespace svo {
-namespace feature_detection {
-
-AbstractDetector::AbstractDetector(
-    const int img_width,
-    const int img_height,
-    const int cell_size,
-    const int n_pyr_levels) :
-        cell_size_(cell_size),
-        n_pyr_levels_(n_pyr_levels),
-        grid_n_cols_(ceil(static_cast<double>(img_width)/cell_size_)),
-        grid_n_rows_(ceil(static_cast<double>(img_height)/cell_size_)),
-        grid_occupancy_(grid_n_cols_*grid_n_rows_, false)
-{}
-
-void AbstractDetector::resetGrid()
-{
-  std::fill(grid_occupancy_.begin(), grid_occupancy_.end(), false);
-}
-
-void AbstractDetector::setExistingFeatures(const Features& fts)
-{
-  std::for_each(fts.begin(), fts.end(), [&](Feature* i){
-    grid_occupancy_.at(
-        static_cast<int>(i->px[1]/cell_size_)*grid_n_cols_
-        + static_cast<int>(i->px[0]/cell_size_)) = true;
-  });
-}
-
-void AbstractDetector::setGridOccpuancy(const Vector2d& px)
-{
-  grid_occupancy_.at(
-      static_cast<int>(px[1]/cell_size_)*grid_n_cols_
-    + static_cast<int>(px[0]/cell_size_)) = true;
-}
-
-FastDetector::FastDetector(
-    const int img_width,
-    const int img_height,
-    const int cell_size,
-    const int n_pyr_levels) :
-        AbstractDetector(img_width, img_height, cell_size, n_pyr_levels)
-{}
-
-void FastDetector::detect(
-    Frame* frame,
-    const ImgPyr& img_pyr,
-    const double detection_threshold,
-    Features& fts)
-{
-  Corners corners(grid_n_cols_*grid_n_rows_, Corner(0,0,detection_threshold,0,0.0f));
-  for(int L=0; L<n_pyr_levels_; ++L)
-  {
-    const int scale = (1<<L);
-    vector<fast::fast_xy> fast_corners;
-#if __SSE2__
-      fast::fast_corner_detect_10_sse2(
-          (fast::fast_byte*) img_pyr[L].data, img_pyr[L].cols,
-          img_pyr[L].rows, img_pyr[L].cols, 20, fast_corners);
-#elif HAVE_FAST_NEON
-      fast::fast_corner_detect_9_neon(
-          (fast::fast_byte*) img_pyr[L].data, img_pyr[L].cols,
-          img_pyr[L].rows, img_pyr[L].cols, 20, fast_corners);
-#else
-      fast::fast_corner_detect_10(
-          (fast::fast_byte*) img_pyr[L].data, img_pyr[L].cols,
-          img_pyr[L].rows, img_pyr[L].cols, 20, fast_corners);
-#endif
-    vector<int> scores, nm_corners;
-    fast::fast_corner_score_10((fast::fast_byte*) img_pyr[L].data, img_pyr[L].cols, fast_corners, 20, scores);
-    fast::fast_nonmax_3x3(fast_corners, scores, nm_corners);
-
-    for(auto it=nm_corners.begin(), ite=nm_corners.end(); it!=ite; ++it)
-    {
-      fast::fast_xy& xy = fast_corners.at(*it);
-      const int k = static_cast<int>((xy.y*scale)/cell_size_)*grid_n_cols_
-                  + static_cast<int>((xy.x*scale)/cell_size_);
-      if(grid_occupancy_[k])
-        continue;
-      const float score = vk::shiTomasiScore(img_pyr[L], xy.x, xy.y);
-      if(score > corners.at(k).score)
-        corners.at(k) = Corner(xy.x*scale, xy.y*scale, score, L, 0.0f);
-    }
-  }
-
-  // Create feature for every corner that has high enough corner score
-  std::for_each(corners.begin(), corners.end(), [&](Corner& c) {
-    if(c.score > detection_threshold)
-      fts.push_back(new Feature(frame, Vector2d(c.x, c.y), c.level));
-  });
-
-  resetGrid();
-}
-
-} // namespace feature_detection
-} // namespace svo
-
diff --git a/CPU_version/svo/src/frame.cpp b/CPU_version/svo/src/frame.cpp
deleted file mode 100644
index 44ddab6..0000000
--- a/CPU_version/svo/src/frame.cpp
+++ /dev/null
@@ -1,190 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#include <stdexcept>
-#include <svo/frame.h>
-#include <svo/feature.h>
-#include <svo/point.h>
-#include <svo/config.h>
-#include <vikit/math_utils.h>
-#include <vikit/vision.h>
-#include <vikit/performance_monitor.h>
-#include <fast/fast.h>
-
-namespace svo {
-
-int Frame::frame_counter_ = 0;
-
-Frame::Frame(vk::AbstractCamera* cam, const cv::Mat& img, double timestamp) :
-    id_(frame_counter_++),
-    timestamp_(timestamp),
-    cam_(cam),
-    key_pts_(5),
-    is_keyframe_(false),
-    v_kf_(NULL)
-{
-  initFrame(img);
-}
-
-Frame::~Frame()
-{
-  std::for_each(fts_.begin(), fts_.end(), [&](Feature* i){delete i;});
-}
-
-void Frame::initFrame(const cv::Mat& img)
-{
-  // check image
-  if(img.empty() || img.type() != CV_8UC1 || img.cols != cam_->width() || img.rows != cam_->height())
-    throw std::runtime_error("Frame: provided image has not the same size as the camera model or image is not grayscale");
-
-  // Set keypoints to NULL
-  std::for_each(key_pts_.begin(), key_pts_.end(), [&](Feature* ftr){ ftr=NULL; });
-
-  // Build Image Pyramid
-  frame_utils::createImgPyramid(img, max(Config::nPyrLevels(), Config::kltMaxLevel()+1), img_pyr_);
-}
-
-void Frame::setKeyframe()
-{
-  is_keyframe_ = true;
-  setKeyPoints();
-}
-
-void Frame::addFeature(Feature* ftr)
-{
-  fts_.push_back(ftr);
-}
-
-void Frame::setKeyPoints()
-{
-  for(size_t i = 0; i < 5; ++i)
-    if(key_pts_[i] != NULL)
-      if(key_pts_[i]->point == NULL)
-        key_pts_[i] = NULL;
-
-  std::for_each(fts_.begin(), fts_.end(), [&](Feature* ftr){ if(ftr->point != NULL) checkKeyPoints(ftr); });
-}
-
-void Frame::checkKeyPoints(Feature* ftr)
-{
-  const int cu = cam_->width()/2;
-  const int cv = cam_->height()/2;
-
-  // center pixel
-  if(key_pts_[0] == NULL)
-    key_pts_[0] = ftr;
-  else if(std::max(std::fabs(ftr->px[0]-cu), std::fabs(ftr->px[1]-cv))
-        < std::max(std::fabs(key_pts_[0]->px[0]-cu), std::fabs(key_pts_[0]->px[1]-cv)))
-    key_pts_[0] = ftr;
-
-  if(ftr->px[0] >= cu && ftr->px[1] >= cv)
-  {
-    if(key_pts_[1] == NULL)
-      key_pts_[1] = ftr;
-    else if((ftr->px[0]-cu) * (ftr->px[1]-cv)
-          > (key_pts_[1]->px[0]-cu) * (key_pts_[1]->px[1]-cv))
-      key_pts_[1] = ftr;
-  }
-  if(ftr->px[0] >= cu && ftr->px[1] < cv)
-  {
-    if(key_pts_[2] == NULL)
-      key_pts_[2] = ftr;
-    else if((ftr->px[0]-cu) * (ftr->px[1]-cv)
-          > (key_pts_[2]->px[0]-cu) * (key_pts_[2]->px[1]-cv))
-      key_pts_[2] = ftr;
-  }
-  if(ftr->px[0] < cv && ftr->px[1] < cv)
-  {
-    if(key_pts_[3] == NULL)
-      key_pts_[3] = ftr;
-    else if((ftr->px[0]-cu) * (ftr->px[1]-cv)
-          > (key_pts_[3]->px[0]-cu) * (key_pts_[3]->px[1]-cv))
-      key_pts_[3] = ftr;
-  }
-  if(ftr->px[0] < cv && ftr->px[1] >= cv)
-  {
-    if(key_pts_[4] == NULL)
-      key_pts_[4] = ftr;
-    else if((ftr->px[0]-cu) * (ftr->px[1]-cv)
-          > (key_pts_[4]->px[0]-cu) * (key_pts_[4]->px[1]-cv))
-      key_pts_[4] = ftr;
-  }
-}
-
-void Frame::removeKeyPoint(Feature* ftr)
-{
-  bool found = false;
-  std::for_each(key_pts_.begin(), key_pts_.end(), [&](Feature*& i){
-    if(i == ftr) {
-      i = NULL;
-      found = true;
-    }
-  });
-  if(found)
-    setKeyPoints();
-}
-
-bool Frame::isVisible(const Vector3d& xyz_w) const
-{
-  Vector3d xyz_f = T_f_w_*xyz_w;
-  if(xyz_f.z() < 0.0)
-    return false; // point is behind the camera
-  Vector2d px = f2c(xyz_f);
-  if(px[0] >= 0.0 && px[1] >= 0.0 && px[0] < cam_->width() && px[1] < cam_->height())
-    return true;
-  return false;
-}
-
-
-/// Utility functions for the Frame class
-namespace frame_utils {
-
-void createImgPyramid(const cv::Mat& img_level_0, int n_levels, ImgPyr& pyr)
-{
-  pyr.resize(n_levels);
-  pyr[0] = img_level_0;
-  for(int i=1; i<n_levels; ++i)
-  {
-    pyr[i] = cv::Mat(pyr[i-1].rows/2, pyr[i-1].cols/2, CV_8U);
-    vk::halfSample(pyr[i-1], pyr[i]);
-  }
-}
-
-bool getSceneDepth(const Frame& frame, double& depth_mean, double& depth_min)
-{
-  vector<double> depth_vec;
-  depth_vec.reserve(frame.fts_.size());
-  depth_min = std::numeric_limits<double>::max();
-  for(auto it=frame.fts_.begin(), ite=frame.fts_.end(); it!=ite; ++it)
-  {
-    if((*it)->point != NULL)
-    {
-      const double z = frame.w2f((*it)->point->pos_).z();
-      depth_vec.push_back(z);
-      depth_min = fmin(z, depth_min);
-    }
-  }
-  if(depth_vec.empty())
-  {
-    SVO_WARN_STREAM("Cannot set scene depth. Frame has no point-observations!");
-    return false;
-  }
-  depth_mean = vk::getMedian(depth_vec);
-  return true;
-}
-
-} // namespace frame_utils
-} // namespace svo
diff --git a/CPU_version/svo/src/frame_handler_base.cpp b/CPU_version/svo/src/frame_handler_base.cpp
deleted file mode 100644
index 175ee01..0000000
--- a/CPU_version/svo/src/frame_handler_base.cpp
+++ /dev/null
@@ -1,199 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#include <vikit/abstract_camera.h>
-#include <stdlib.h>
-#include <Eigen/StdVector>
-#include <boost/bind.hpp>
-#include <fstream>
-#include <svo/frame_handler_base.h>
-#include <svo/config.h>
-#include <svo/feature.h>
-#include <svo/matcher.h>
-#include <svo/map.h>
-#include <svo/point.h>
-
-namespace svo
-{
-
-// definition of global and static variables which were declared in the header
-#ifdef SVO_TRACE
-vk::PerformanceMonitor* g_permon = NULL;
-#endif
-
-FrameHandlerBase::FrameHandlerBase() :
-  stage_(STAGE_PAUSED),
-  set_reset_(false),
-  set_start_(false),
-  acc_frame_timings_(10),
-  acc_num_obs_(10),
-  num_obs_last_(0),
-  tracking_quality_(TRACKING_INSUFFICIENT)
-{
-#ifdef SVO_TRACE
-  // Initialize Performance Monitor
-  g_permon = new vk::PerformanceMonitor();
-  g_permon->addTimer("pyramid_creation");
-  g_permon->addTimer("sparse_img_align");
-  g_permon->addTimer("reproject");
-  g_permon->addTimer("reproject_kfs");
-  g_permon->addTimer("reproject_candidates");
-  g_permon->addTimer("feature_align");
-  g_permon->addTimer("pose_optimizer");
-  g_permon->addTimer("point_optimizer");
-  g_permon->addTimer("local_ba");
-  g_permon->addTimer("tot_time");
-  g_permon->addLog("timestamp");
-  g_permon->addLog("img_align_n_tracked");
-  g_permon->addLog("repr_n_mps");
-  g_permon->addLog("repr_n_new_references");
-  g_permon->addLog("sfba_thresh");
-  g_permon->addLog("sfba_error_init");
-  g_permon->addLog("sfba_error_final");
-  g_permon->addLog("sfba_n_edges_final");
-  g_permon->addLog("loba_n_erredges_init");
-  g_permon->addLog("loba_n_erredges_fin");
-  g_permon->addLog("loba_err_init");
-  g_permon->addLog("loba_err_fin");
-  g_permon->addLog("n_candidates");
-  g_permon->addLog("dropout");
-  g_permon->init(Config::traceName(), Config::traceDir());
-#endif
-
-  SVO_INFO_STREAM("SVO initialized");
-}
-
-FrameHandlerBase::~FrameHandlerBase()
-{
-  SVO_INFO_STREAM("SVO destructor invoked");
-#ifdef SVO_TRACE
-  delete g_permon;
-#endif
-}
-
-bool FrameHandlerBase::startFrameProcessingCommon(const double timestamp)
-{
-  if(set_start_)
-  {
-    resetAll();
-    stage_ = STAGE_FIRST_FRAME;
-  }
-
-  if(stage_ == STAGE_PAUSED)
-    return false;
-
-  SVO_LOG(timestamp);
-  SVO_DEBUG_STREAM("New Frame");
-  SVO_START_TIMER("tot_time");
-  timer_.start();
-
-  // some cleanup from last iteration, can't do before because of visualization
-  map_.emptyTrash();
-  return true;
-}
-
-int FrameHandlerBase::finishFrameProcessingCommon(
-    const size_t update_id,
-    const UpdateResult dropout,
-    const size_t num_observations)
-{
-  SVO_DEBUG_STREAM("Frame: "<<update_id<<"\t fps-avg = "<< 1.0/acc_frame_timings_.getMean()<<"\t nObs = "<<acc_num_obs_.getMean());
-  SVO_LOG(dropout);
-
-  // save processing time to calculate fps
-  acc_frame_timings_.push_back(timer_.stop());
-  if(stage_ == STAGE_DEFAULT_FRAME)
-    acc_num_obs_.push_back(num_observations);
-  num_obs_last_ = num_observations;
-  SVO_STOP_TIMER("tot_time");
-
-#ifdef SVO_TRACE
-  g_permon->writeToFile();
-  {
-    boost::unique_lock<boost::mutex> lock(map_.point_candidates_.mut_);
-    size_t n_candidates = map_.point_candidates_.candidates_.size();
-    SVO_LOG(n_candidates);
-  }
-#endif
-
-  if(dropout == RESULT_FAILURE &&
-      (stage_ == STAGE_DEFAULT_FRAME || stage_ == STAGE_RELOCALIZING ))
-  {
-    stage_ = STAGE_RELOCALIZING;
-    tracking_quality_ = TRACKING_INSUFFICIENT;
-  }
-  else if (dropout == RESULT_FAILURE)
-    resetAll();
-  if(set_reset_)
-    resetAll();
-
-  return 0;
-}
-
-void FrameHandlerBase::resetCommon()
-{
-  map_.reset();
-  stage_ = STAGE_PAUSED;
-  set_reset_ = false;
-  set_start_ = false;
-  tracking_quality_ = TRACKING_INSUFFICIENT;
-  num_obs_last_ = 0;
-  SVO_INFO_STREAM("RESET");
-}
-
-void FrameHandlerBase::setTrackingQuality(const size_t num_observations)
-{
-  tracking_quality_ = TRACKING_GOOD;
-  if(num_observations < Config::qualityMinFts())
-  {
-    SVO_WARN_STREAM_THROTTLE(0.5, "Tracking less than "<< Config::qualityMinFts() <<" features!");
-    tracking_quality_ = TRACKING_INSUFFICIENT;
-  }
-  const int feature_drop = static_cast<int>(std::min(num_obs_last_, Config::maxFts())) - num_observations;
-  if(feature_drop > Config::qualityMaxFtsDrop())
-  {
-    SVO_WARN_STREAM("Lost "<< feature_drop <<" features!");
-    tracking_quality_ = TRACKING_INSUFFICIENT;
-  }
-}
-
-bool ptLastOptimComparator(Point* lhs, Point* rhs)
-{
-  return (lhs->last_structure_optim_ < rhs->last_structure_optim_);
-}
-
-void FrameHandlerBase::optimizeStructure(
-    FramePtr frame,
-    size_t max_n_pts,
-    int max_iter)
-{
-  deque<Point*> pts;
-  for(Features::iterator it=frame->fts_.begin(); it!=frame->fts_.end(); ++it)
-  {
-    if((*it)->point != NULL)
-      pts.push_back((*it)->point);
-  }
-  max_n_pts = min(max_n_pts, pts.size());
-  nth_element(pts.begin(), pts.begin() + max_n_pts, pts.end(), ptLastOptimComparator);
-  for(deque<Point*>::iterator it=pts.begin(); it!=pts.begin()+max_n_pts; ++it)
-  {
-    (*it)->optimize(max_iter);
-    (*it)->last_structure_optim_ = frame->id_;
-  }
-}
-
-
-} // namespace svo
diff --git a/CPU_version/svo/src/frame_handler_mono.cpp b/CPU_version/svo/src/frame_handler_mono.cpp
deleted file mode 100644
index 799cb8c..0000000
--- a/CPU_version/svo/src/frame_handler_mono.cpp
+++ /dev/null
@@ -1,307 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#include <svo/config.h>
-#include <svo/frame_handler_mono.h>
-#include <svo/map.h>
-#include <svo/frame.h>
-#include <svo/feature.h>
-#include <svo/point.h>
-#include <svo/pose_optimizer.h>
-#include <svo/sparse_img_align.h>
-#include <vikit/performance_monitor.h>
-#include <svo/depth_filter.h>
-#ifdef USE_BUNDLE_ADJUSTMENT
-#include <svo/bundle_adjustment.h>
-#endif
-
-namespace svo {
-
-FrameHandlerMono::FrameHandlerMono(vk::AbstractCamera* cam,Sophus::SE3& SE_init) :
-  FrameHandlerBase(),
-  cam_(cam),
-  reprojector_(cam_, map_),
-  depth_filter_(NULL)
-{
-  initialize();
-  imu_integPtr_=std::make_unique<Imu_Integration>(SE_init);
-}
-
-void FrameHandlerMono::initialize()
-{
-  feature_detection::DetectorPtr feature_detector(
-      new feature_detection::FastDetector(
-          cam_->width(), cam_->height(), Config::gridSize(), Config::nPyrLevels()));
-  DepthFilter::callback_t depth_filter_cb = boost::bind(
-      &MapPointCandidates::newCandidatePoint, &map_.point_candidates_, _1, _2);
-  depth_filter_ = new DepthFilter(feature_detector, depth_filter_cb);
-  depth_filter_->startThread();
-}
-
-FrameHandlerMono::~FrameHandlerMono()
-{
-  delete depth_filter_;
-}
-
-void FrameHandlerMono::addImage(const cv::Mat& img, const double timestamp)
-{
-  if(!startFrameProcessingCommon(timestamp))
-    return;
-
-  // some cleanup from last iteration, can't do before because of visualization
-  core_kfs_.clear();
-  overlap_kfs_.clear();
-
-  // create new frame
-  new_frame_.reset(new Frame(cam_, img.clone(), timestamp));
-
-  // process frame
-  UpdateResult res = RESULT_FAILURE;
-  if(stage_ == STAGE_DEFAULT_FRAME)
-    res = processFrame();
-  else if(stage_ == STAGE_SECOND_FRAME)
-    res = processSecondFrame();
-  else if(stage_ == STAGE_FIRST_FRAME)
-    res = processFirstFrame();
-  else if(stage_ == STAGE_RELOCALIZING)
-    res = relocalizeFrame(SE3(Matrix3d::Identity(), Vector3d::Zero()),
-                          map_.getClosestKeyframe(last_frame_));
-
-  // set last frame
-  last_frame_ = new_frame_;
-  new_frame_.reset();
-  // finish processing
-  finishFrameProcessingCommon(last_frame_->id_, res, last_frame_->nObs());
-}
-
-FrameHandlerMono::UpdateResult FrameHandlerMono::processFirstFrame()
-{
-  new_frame_->T_f_w_ = SE3(Matrix3d::Identity(), Vector3d::Zero());
-  if(klt_homography_init_.addFirstFrame(new_frame_) == initialization::FAILURE)
-    return RESULT_NO_KEYFRAME;
-  new_frame_->setKeyframe();
-  map_.addKeyframe(new_frame_);
-  stage_ = STAGE_SECOND_FRAME;
-  SVO_INFO_STREAM("Init: Selected first frame.");
-  return RESULT_IS_KEYFRAME;
-}
-
-FrameHandlerBase::UpdateResult FrameHandlerMono::processSecondFrame()
-{
-  initialization::InitResult res = klt_homography_init_.addSecondFrame(new_frame_);
-  if(res == initialization::FAILURE)
-    return RESULT_FAILURE;
-  else if(res == initialization::NO_KEYFRAME)
-    return RESULT_NO_KEYFRAME;
-
-  // two-frame bundle adjustment
-#ifdef USE_BUNDLE_ADJUSTMENT
-  ba::twoViewBA(new_frame_.get(), map_.lastKeyframe().get(), Config::lobaThresh(), &map_);
-#endif
-
-  new_frame_->setKeyframe();
-  double depth_mean, depth_min;
-  frame_utils::getSceneDepth(*new_frame_, depth_mean, depth_min);
-  depth_filter_->addKeyframe(new_frame_, depth_mean, 0.5*depth_min);
-
-  // add frame to map
-  map_.addKeyframe(new_frame_);
-  stage_ = STAGE_DEFAULT_FRAME;
-  klt_homography_init_.reset();
-  SVO_INFO_STREAM("Init: Selected second frame, triangulated initial map.");
-  return RESULT_IS_KEYFRAME;
-}
-
-FrameHandlerBase::UpdateResult FrameHandlerMono::processFrame()
-{
-  // Set initial pose TODO use prior
-  new_frame_->T_f_w_ = last_frame_->T_f_w_;
-
-  // sparse image align
-  SparseImgAlign img_align(Config::kltMaxLevel(), Config::kltMinLevel(),
-                           30, SparseImgAlign::GaussNewton, false, false);
-  img_align.run(last_frame_, new_frame_);
-  // map reprojection & feature alignment
-  reprojector_.reprojectMap(new_frame_, overlap_kfs_);
-  std::cerr<<"Reprojection Map:\t nPoints = "<<reprojector_.n_trials_<<"\t \t nMatches = "<<reprojector_.n_matches_<<" \t Quality min: "<<Config::qualityMinFts()<<'\n';
-  if(reprojector_.n_matches_< Config::qualityMinFts())
-  {
-    new_frame_->T_f_w_ = last_frame_->T_f_w_; // reset to avoid crazy pose jumps
-    tracking_quality_ = TRACKING_INSUFFICIENT;
-    return RESULT_FAILURE;
-  }
-
-  // pose optimization subject to change for adding IMU
-  size_t sfba_n_edges_final;
-  if(!imu_integPtr_->predict(new_frame_,sfba_n_edges_final,Config::poseOptimThresh()))
-      return RESULT_FAILURE;
-
-
-  std::cerr<<"Reprojected points after opmization: "<<sfba_n_edges_final<<'\n';
-  if(sfba_n_edges_final < Config::qualityMinFts())
-    return RESULT_FAILURE;
-
-  // structure optimization
-  //SVO_START_TIMER("point_optimizer");
-  optimizeStructure(new_frame_, Config::structureOptimMaxPts(), Config::structureOptimNumIter());
-  //SVO_STOP_TIMER("point_optimizer");
-
-  // select keyframe
-  core_kfs_.insert(new_frame_);
-  setTrackingQuality(sfba_n_edges_final);
-  if(tracking_quality_ == TRACKING_INSUFFICIENT)
-  {
-    new_frame_->T_f_w_ = last_frame_->T_f_w_; // reset to avoid crazy pose jumps
-    return RESULT_FAILURE;
-  }
-  double depth_mean, depth_min;
-  frame_utils::getSceneDepth(*new_frame_, depth_mean, depth_min);
-  if(!needNewKf(depth_mean) || tracking_quality_ == TRACKING_BAD)
-  {
-    depth_filter_->addFrame(new_frame_);
-    return RESULT_NO_KEYFRAME;
-  }
-  new_frame_->setKeyframe();
-
-  // new keyframe selected
-  for(Features::iterator it=new_frame_->fts_.begin(); it!=new_frame_->fts_.end(); ++it)
-    if((*it)->point != NULL)
-      (*it)->point->addFrameRef(*it);
-  map_.point_candidates_.addCandidatePointToFrame(new_frame_);
-
-  // optional bundle adjustment
-#ifdef USE_BUNDLE_ADJUSTMENT
-  if(Config::lobaNumIter() > 0)
-  {
-    SVO_START_TIMER("local_ba");
-    setCoreKfs(Config::coreNKfs());
-    size_t loba_n_erredges_init, loba_n_erredges_fin;
-    double loba_err_init, loba_err_fin;
-    ba::localBA(new_frame_.get(), &core_kfs_, &map_,
-                loba_n_erredges_init, loba_n_erredges_fin,
-                loba_err_init, loba_err_fin);
-    SVO_STOP_TIMER("local_ba");
-    SVO_LOG4(loba_n_erredges_init, loba_n_erredges_fin, loba_err_init, loba_err_fin);
-    SVO_DEBUG_STREAM("Local BA:\t RemovedEdges {"<<loba_n_erredges_init<<", "<<loba_n_erredges_fin<<"} \t "
-                     "Error {"<<loba_err_init<<", "<<loba_err_fin<<"}");
-  }
-#endif
-
-  // init new depth-filters
-  depth_filter_->addKeyframe(new_frame_, depth_mean, 0.5*depth_min);
-
-  // if limited number of keyframes, remove the one furthest apart
-  if(Config::maxNKfs() > 2 && map_.size() >= Config::maxNKfs())
-  {
-    FramePtr furthest_frame = map_.getFurthestKeyframe(new_frame_->pos());
-    depth_filter_->removeKeyframe(furthest_frame); // TODO this interrupts the mapper thread, maybe we can solve this better
-    map_.safeDeleteFrame(furthest_frame);
-  }
-
-  // add keyframe to map
-  map_.addKeyframe(new_frame_);
-  std::cerr<<"Svo pipline was finished\n";
-  return RESULT_IS_KEYFRAME;
-}
-
-FrameHandlerMono::UpdateResult FrameHandlerMono::relocalizeFrame(
-    const SE3& T_cur_ref,
-    FramePtr ref_keyframe)
-{
-  if(ref_keyframe == nullptr)
-  {
-    return RESULT_FAILURE;
-  }
-  SparseImgAlign img_align(Config::kltMaxLevel(), Config::kltMinLevel(),
-                           30, SparseImgAlign::GaussNewton, false, false);
-  size_t img_align_n_tracked = img_align.run(ref_keyframe, new_frame_);
-  usleep(2000);
-  if(img_align_n_tracked > Config::qualityMinFts())
-  {
-    SE3 T_f_w_last = last_frame_->T_f_w_;
-    last_frame_ = ref_keyframe;
-    FrameHandlerMono::UpdateResult res = processFrame();
-    if(res != RESULT_FAILURE)
-    {
-      stage_ = STAGE_DEFAULT_FRAME;
-    }
-    else
-      new_frame_->T_f_w_ = T_f_w_last; // reset to last well localized pose
-    return res;
-  }
-  return RESULT_FAILURE;
-}
-
-bool FrameHandlerMono::relocalizeFrameAtPose(
-    const int keyframe_id,
-    const SE3& T_f_kf,
-    const cv::Mat& img,
-    const double timestamp)
-{
-  FramePtr ref_keyframe;
-  if(!map_.getKeyframeById(keyframe_id, ref_keyframe))
-    return false;
-  new_frame_.reset(new Frame(cam_, img.clone(), timestamp));
-  UpdateResult res = relocalizeFrame(T_f_kf, ref_keyframe);
-  if(res != RESULT_FAILURE) {
-    last_frame_ = new_frame_;
-    return true;
-  }
-  return false;
-}
-
-void FrameHandlerMono::resetAll()
-{
-  resetCommon();
-  last_frame_.reset();
-  new_frame_.reset();
-  core_kfs_.clear();
-  overlap_kfs_.clear();
-  depth_filter_->reset();
-}
-
-void FrameHandlerMono::setFirstFrame(const FramePtr& first_frame)
-{
-  resetAll();
-  last_frame_ = first_frame;
-  last_frame_->setKeyframe();
-  map_.addKeyframe(last_frame_);
-  stage_ = STAGE_DEFAULT_FRAME;
-}
-
-bool FrameHandlerMono::needNewKf(double scene_depth_mean)
-{
-  for(auto it=overlap_kfs_.begin(), ite=overlap_kfs_.end(); it!=ite; ++it)
-  {
-    Vector3d relpos = new_frame_->w2f(it->first->pos());
-    if(fabs(relpos.x())/scene_depth_mean < Config::kfSelectMinDist() &&
-       fabs(relpos.y())/scene_depth_mean < Config::kfSelectMinDist()*0.8 &&
-       fabs(relpos.z())/scene_depth_mean < Config::kfSelectMinDist()*1.3)
-      return false;
-  }
-  return true;
-}
-
-void FrameHandlerMono::setCoreKfs(size_t n_closest)
-{
-  size_t n = min(n_closest, overlap_kfs_.size()-1);
-  std::partial_sort(overlap_kfs_.begin(), overlap_kfs_.begin()+n, overlap_kfs_.end(),
-                    boost::bind(&pair<FramePtr, size_t>::second, _1) >
-                    boost::bind(&pair<FramePtr, size_t>::second, _2));
-  std::for_each(overlap_kfs_.begin(), overlap_kfs_.end(), [&](pair<FramePtr,size_t>& i){ core_kfs_.insert(i.first); });
-}
-
-} // namespace svo
diff --git a/CPU_version/svo/src/imu_integration.cpp b/CPU_version/svo/src/imu_integration.cpp
deleted file mode 100644
index a66223c..0000000
--- a/CPU_version/svo/src/imu_integration.cpp
+++ /dev/null
@@ -1,153 +0,0 @@
-//
-// Created by gfuse on 4/9/21.
-//
-//#define NDEBUG
-#include "svo/imu_integration.h"
-#include <memory>
-#include <utility>
-#include "svo/feature.h"
-#include "svo/point.h"
-#include "svo/svoVisionFactor.h"
-#include <gtsam/nonlinear/Marginals.h>
-#include <gtsam/geometry/Pose3.h>
-#include <vikit/params_helper.h>
-#include <svo/config.h>
-
-Imu_Integration::Imu_Integration(Sophus::SE3& SE_init){
-    graphPtr=std::make_shared<gtsam::NonlinearFactorGraph>();
-    valuesPtr=std::make_shared<gtsam::Values>();
-    gtsam::Vector4 g=SE_init.matrix()*gtsam::Vector4(0, 0, 9.8,1.0);
-    parameterPtr = boost::shared_ptr<gtsam::PreintegrationCombinedParams>(new gtsam::PreintegrationCombinedParams(gtsam::Vector3(g.x(),g.y(),g.z())));
-    parameterPtr->setBodyPSensor(gtsam::Pose3(SE_init.matrix()));// The pose of the sensor in the body frame
-    parameterPtr->accelerometerCovariance=gtsam::I_3x3 * svo::Config::ACC_Noise(); // acc white noise in continuous
-    parameterPtr->gyroscopeCovariance=gtsam::I_3x3 * svo::Config::GYO_Noise();// gyro white noise in continuous
-    parameterPtr->integrationCovariance=gtsam::I_3x3 * svo::Config::IUC(); // integration uncertainty continuous
-    parameterPtr->biasAccCovariance = gtsam::I_3x3 * svo::Config::ABC();   // acc bias in continuous
-    parameterPtr->biasOmegaCovariance = gtsam::I_3x3 * svo::Config::GBC();  // gyro bias in continuous
-    parameterPtr->biasAccOmegaInt = gtsam::I_6x6 * svo::Config::EBP();  // error in the bias used for preintegration
-    imu_biasPtr=std::make_shared<gtsam::imuBias::ConstantBias>(gtsam::Vector3(1e-8,1e-8,1e-8),gtsam::Vector3(1e-8,1e-8,1e-8));
-    preintegratedPtr = std::make_shared<gtsam::PreintegratedCombinedMeasurements>(parameterPtr,*imu_biasPtr);
-    ProjectNoisePtr = gtsam::noiseModel::Isotropic::Sigma(2, svo::Config::NRP()); // the noise used for projection
-    optimizerParamPtr=std::make_shared<gtsam::ISAM2Params>();
-    optimizerParamPtr->relinearizeThreshold = 0.1;
-    optimizerParamPtr->relinearizeSkip = 1;
-    //optimizerParamPtr->evaluateNonlinearError=true;
-    assert(preintegratedPtr);
-}
-Imu_Integration::~Imu_Integration(){
-
-}
-bool Imu_Integration::update(double* imu){
-    if(syn)return false;
-    if(imu_factor_id<1)return false;
-    auto in=std::chrono::steady_clock::now();
-    if(std::chrono::duration<double>(in-t_1).count()>20.0){
-        t_1=in;
-        preintegratedPtr->integrateMeasurement(Eigen::Vector3d(imu[0],imu[1],imu[2]),Eigen::Vector3d(imu[3],imu[4],imu[5]),0.005);
-    }else{
-        preintegratedPtr->integrateMeasurement(Eigen::Vector3d(imu[0],imu[1],imu[2]),Eigen::Vector3d(imu[3],imu[4],imu[5]),std::chrono::duration<double>(in-t_1).count());
-        t_1=in;
-        ++imu_n;
-    }
-    return true;
-
-}
-bool Imu_Integration::reset(gtsam::ISAM2& optimizer,boost::shared_ptr<svo::Frame>& new_frame){
-    gtsam::Values result = optimizer.calculateEstimate();
-    // Overwrite the beginning of the preintegration for the next step.
-    statePtr=std::make_shared<gtsam::NavState>(result.at<gtsam::Pose3>(P(imu_factor_id)), result.at<gtsam::Vector3>(V(imu_factor_id)));
-    imu_biasPtr=std::make_shared<gtsam::imuBias::ConstantBias>(result.at<gtsam::imuBias::ConstantBias>(B(imu_factor_id)));
-    preintegratedPtr->resetIntegrationAndSetBias(*imu_biasPtr);
-    ++imu_factor_id;
-    syn=false;
-    new_frame->T_f_w_=Sophus::SE3(statePtr->R(),statePtr->t());
-    new_frame->Cov_=optimizer.marginalCovariance(P(imu_factor_id-1));
-    graphPtr->resize(0);
-    valuesPtr->clear();
-    valuesPtr->insert(P(imu_factor_id-1),statePtr->pose());
-    valuesPtr->insert(V(imu_factor_id-1),statePtr->v());
-    valuesPtr->insert(B(imu_factor_id-1),*imu_biasPtr);
-    graphPtr->addPrior(P(imu_factor_id-1),statePtr->pose(),optimizer.marginalCovariance(P(imu_factor_id-1)));
-    graphPtr->addPrior(V(imu_factor_id-1),statePtr->v(),optimizer.marginalCovariance(V(imu_factor_id-1)));
-    graphPtr->addPrior(B(imu_factor_id-1),*imu_biasPtr,optimizer.marginalCovariance(B(imu_factor_id-1)));
-    return true;
-}
-bool Imu_Integration::reset(gtsam::LevenbergMarquardtOptimizer& optimizer,boost::shared_ptr<svo::Frame>& new_frame){
-    gtsam::Values result = optimizer.optimize();
-    // Overwrite the beginning of the preintegration for the next step.
-    statePtr=std::make_shared<gtsam::NavState>(result.at<gtsam::Pose3>(P(imu_factor_id)), result.at<gtsam::Vector3>(V(imu_factor_id)));
-    imu_biasPtr=std::make_shared<gtsam::imuBias::ConstantBias>(result.at<gtsam::imuBias::ConstantBias>(B(imu_factor_id)));
-    preintegratedPtr->resetIntegrationAndSetBias(*imu_biasPtr);
-    ++imu_factor_id;
-    syn=false;
-    gtsam::Marginals marginals(*graphPtr,result);
-    new_frame->T_f_w_=Sophus::SE3(statePtr->R(),statePtr->t());
-    new_frame->Cov_=marginals.marginalCovariance(P(imu_factor_id-1));
-    graphPtr->resize(0);
-    valuesPtr->clear();
-    valuesPtr->insert(P(imu_factor_id-1),statePtr->pose());
-    valuesPtr->insert(V(imu_factor_id-1),statePtr->v());
-    valuesPtr->insert(B(imu_factor_id-1),*imu_biasPtr);
-    graphPtr->addPrior(P(imu_factor_id-1),statePtr->pose(),marginals.marginalCovariance(P(imu_factor_id-1)));
-    graphPtr->addPrior(V(imu_factor_id-1),statePtr->v(),marginals.marginalCovariance(V(imu_factor_id-1)));
-    graphPtr->addPrior(B(imu_factor_id-1),*imu_biasPtr,marginals.marginalCovariance(B(imu_factor_id-1)));
-    return true;
-}
-bool Imu_Integration::predict(boost::shared_ptr<svo::Frame>& new_frame,std::size_t& num_obs,const double reproj_thresh){
-    usleep(5000);
-    syn=true;
-    if(imu_factor_id<1){
-        statePtr=std::make_shared<gtsam::NavState>(gtsam::Pose3(new_frame->T_f_w_.matrix()),
-                                                   gtsam::Vector3(1e-12,1e-12,1e-12));
-        valuesPtr->insert(P(0),statePtr->pose());
-        valuesPtr->insert(V(0),statePtr->v());
-        valuesPtr->insert(B(0),*imu_biasPtr);
-        graphPtr->addPrior(P(0),statePtr->pose(),gtsam::noiseModel::Diagonal::Sigmas((gtsam::Vector(6) << 1e-9, 1e-9, 1e-9, 1e-9, 1e-9, 1e-9).finished()));
-        graphPtr->addPrior(V(0),statePtr->v(),gtsam::noiseModel::Isotropic::Sigma(3, 1e-4));
-        graphPtr->addPrior(B(0),*imu_biasPtr,gtsam::noiseModel::Isotropic::Sigma(6, 1e-2));
-    }else{
-        if(imu_n<1)return false;
-        auto preint_imu_combined =dynamic_cast<const gtsam::PreintegratedCombinedMeasurements&>(*preintegratedPtr);
-        valuesPtr->insert(P(imu_factor_id), gtsam::Pose3(new_frame->T_f_w_.matrix()));
-        valuesPtr->insert(V(imu_factor_id), statePtr->v());
-        valuesPtr->insert(B(imu_factor_id), *imu_biasPtr);
-        gtsam::CombinedImuFactor imu_factor(P(imu_factor_id - 1), V(imu_factor_id - 1), P(imu_factor_id), V(imu_factor_id), B(imu_factor_id - 1), B(imu_factor_id),
-                                            preint_imu_combined);
-        graphPtr->emplace_shared<gtsam::CombinedImuFactor>(imu_factor);
-        imu_n=0;
-    }
-
-    num_obs=0;
-    for(auto&& f:new_frame->fts_){
-       if(f->point==NULL)continue;
-        graphPtr->emplace_shared<svo::VisionFactor>(f->f, f->point->pos_,f->level, ProjectNoisePtr,P(imu_factor_id));
-        ++num_obs;
-    }
-    // Now optimize.
-    //gtsam::ISAM2 optimizer(*optimizerParamPtr);
-    //optimizer.update(*graphPtr, *valuesPtr);
-    // Each call to iSAM2 update(*) performs one iteration of the iterative
-    // nonlinear solver. If accuracy is desired at the expense of time,
-    // update(*) can be called additional times to perform multiple optimizer
-    // iterations every step.
-    //optimizer.update();
-   // optimizer.print();
-    gtsam::LevenbergMarquardtOptimizer optimizer(*graphPtr, *valuesPtr);
-
-    reset(optimizer,new_frame);
-    // Remove Measurements with too large reprojection error
-    double reproj_thresh_scaled = reproj_thresh / new_frame->cam_->errorMultiplier2();
-    for(auto&& f:new_frame->fts_)
-    {
-        if(f->point == NULL)
-            continue;
-        Eigen::Vector2d e = (vk::project2d(f->f) - vk::project2d(new_frame->T_f_w_ * f->point->pos_))*1.0 / (1<<f->level);
-        if(e.norm() > reproj_thresh_scaled)
-        {
-            // we don't need to delete a reference in the point since it was not created yet
-            f->point = NULL;
-            --num_obs;
-        }
-    }
-    return true;
-}
diff --git a/CPU_version/svo/src/initialization.cpp b/CPU_version/svo/src/initialization.cpp
deleted file mode 100644
index 571a0bc..0000000
--- a/CPU_version/svo/src/initialization.cpp
+++ /dev/null
@@ -1,199 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#include <svo/config.h>
-#include <svo/frame.h>
-#include <svo/point.h>
-#include <svo/feature.h>
-#include <svo/initialization.h>
-#include <svo/feature_detection.h>
-#include <vikit/math_utils.h>
-#include <vikit/homography.h>
-
-namespace svo {
-namespace initialization {
-
-InitResult KltHomographyInit::addFirstFrame(FramePtr frame_ref)
-{
-  reset();
-  detectFeatures(frame_ref, px_ref_, f_ref_);
-  if(px_ref_.size() < 100)
-  {
-    SVO_WARN_STREAM_THROTTLE(2.0, "First image has less than 100 features. Retry in more textured environment.");
-    return FAILURE;
-  }
-  frame_ref_ = frame_ref;
-  px_cur_.insert(px_cur_.begin(), px_ref_.begin(), px_ref_.end());
-  return SUCCESS;
-}
-
-InitResult KltHomographyInit::addSecondFrame(FramePtr frame_cur)
-{
-  trackKlt(frame_ref_, frame_cur, px_ref_, px_cur_, f_ref_, f_cur_, disparities_);
-  SVO_INFO_STREAM("Init: KLT tracked "<< disparities_.size() <<" features");
-
-  if(disparities_.size() < Config::initMinTracked())
-    return FAILURE;
-
-  double disparity = vk::getMedian(disparities_);
-  SVO_INFO_STREAM("Init: KLT "<<disparity<<"px average disparity.");
-  if(disparity < Config::initMinDisparity())
-    return NO_KEYFRAME;
-
-  computeHomography(
-      f_ref_, f_cur_,
-      frame_ref_->cam_->errorMultiplier2(), Config::poseOptimThresh(),
-      inliers_, xyz_in_cur_, T_cur_from_ref_);
-  SVO_INFO_STREAM("Init: Homography RANSAC "<<inliers_.size()<<" inliers.");
-
-  if(inliers_.size() < Config::initMinInliers())
-  {
-    SVO_WARN_STREAM("Init WARNING: "<<Config::initMinInliers()<<" inliers minimum required.");
-    return FAILURE;
-  }
-
-  // Rescale the map such that the mean scene depth is equal to the specified scale
-  vector<double> depth_vec;
-  for(size_t i=0; i<xyz_in_cur_.size(); ++i)
-    depth_vec.push_back((xyz_in_cur_[i]).z());
-  double scene_depth_median = vk::getMedian(depth_vec);
-  double scale = Config::mapScale()/scene_depth_median;
-  frame_cur->T_f_w_ = T_cur_from_ref_ * frame_ref_->T_f_w_;
-  frame_cur->T_f_w_.translation() =
-      -frame_cur->T_f_w_.rotation_matrix()*(frame_ref_->pos() + scale*(frame_cur->pos() - frame_ref_->pos()));
-
-  // For each inlier create 3D point and add feature in both frames
-  SE3 T_world_cur = frame_cur->T_f_w_.inverse();
-  for(vector<int>::iterator it=inliers_.begin(); it!=inliers_.end(); ++it)
-  {
-    Vector2d px_cur(px_cur_[*it].x, px_cur_[*it].y);
-    Vector2d px_ref(px_ref_[*it].x, px_ref_[*it].y);
-    if(frame_ref_->cam_->isInFrame(px_cur.cast<int>(), 10) && frame_ref_->cam_->isInFrame(px_ref.cast<int>(), 10) && xyz_in_cur_[*it].z() > 0)
-    {
-      Vector3d pos = T_world_cur * (xyz_in_cur_[*it]*scale);
-      Point* new_point = new Point(pos);
-
-      Feature* ftr_cur(new Feature(frame_cur.get(), new_point, px_cur, f_cur_[*it], 0));
-      frame_cur->addFeature(ftr_cur);
-      new_point->addFrameRef(ftr_cur);
-
-      Feature* ftr_ref(new Feature(frame_ref_.get(), new_point, px_ref, f_ref_[*it], 0));
-      frame_ref_->addFeature(ftr_ref);
-      new_point->addFrameRef(ftr_ref);
-    }
-  }
-  return SUCCESS;
-}
-
-void KltHomographyInit::reset()
-{
-  px_cur_.clear();
-  frame_ref_.reset();
-}
-
-void detectFeatures(
-    FramePtr frame,
-    vector<cv::Point2f>& px_vec,
-    vector<Vector3d>& f_vec)
-{
-  Features new_features;
-  feature_detection::FastDetector detector(
-      frame->img().cols, frame->img().rows, Config::gridSize(), Config::nPyrLevels());
-  detector.detect(frame.get(), frame->img_pyr_, Config::triangMinCornerScore(), new_features);
-
-  // now for all maximum corners, initialize a new seed
-  px_vec.clear(); px_vec.reserve(new_features.size());
-  f_vec.clear(); f_vec.reserve(new_features.size());
-  std::for_each(new_features.begin(), new_features.end(), [&](Feature* ftr){
-    px_vec.push_back(cv::Point2f(ftr->px[0], ftr->px[1]));
-    f_vec.push_back(ftr->f);
-    delete ftr;
-  });
-}
-
-void trackKlt(
-    FramePtr frame_ref,
-    FramePtr frame_cur,
-    vector<cv::Point2f>& px_ref,
-    vector<cv::Point2f>& px_cur,
-    vector<Vector3d>& f_ref,
-    vector<Vector3d>& f_cur,
-    vector<double>& disparities)
-{
-  const double klt_win_size = 30.0;
-  const int klt_max_iter = 30;
-  const double klt_eps = 0.001;
-  vector<uchar> status;
-  vector<float> error;
-  vector<float> min_eig_vec;
-  cv::TermCriteria termcrit(cv::TermCriteria::COUNT+cv::TermCriteria::EPS, klt_max_iter, klt_eps);
-  cv::calcOpticalFlowPyrLK(frame_ref->img_pyr_[0], frame_cur->img_pyr_[0],
-                           px_ref, px_cur,
-                           status, error,
-                           cv::Size2i(klt_win_size, klt_win_size),
-                           4, termcrit, cv::OPTFLOW_USE_INITIAL_FLOW);
-
-  vector<cv::Point2f>::iterator px_ref_it = px_ref.begin();
-  vector<cv::Point2f>::iterator px_cur_it = px_cur.begin();
-  vector<Vector3d>::iterator f_ref_it = f_ref.begin();
-  f_cur.clear(); f_cur.reserve(px_cur.size());
-  disparities.clear(); disparities.reserve(px_cur.size());
-  for(size_t i=0; px_ref_it != px_ref.end(); ++i)
-  {
-    if(!status[i])
-    {
-      px_ref_it = px_ref.erase(px_ref_it);
-      px_cur_it = px_cur.erase(px_cur_it);
-      f_ref_it = f_ref.erase(f_ref_it);
-      continue;
-    }
-    f_cur.push_back(frame_cur->c2f(px_cur_it->x, px_cur_it->y));
-    disparities.push_back(Vector2d(px_ref_it->x - px_cur_it->x, px_ref_it->y - px_cur_it->y).norm());
-    ++px_ref_it;
-    ++px_cur_it;
-    ++f_ref_it;
-  }
-}
-
-void computeHomography(
-    const vector<Vector3d>& f_ref,
-    const vector<Vector3d>& f_cur,
-    double focal_length,
-    double reprojection_threshold,
-    vector<int>& inliers,
-    vector<Vector3d>& xyz_in_cur,
-    SE3& T_cur_from_ref)
-{
-  vector<Vector2d > uv_ref(f_ref.size());
-  vector<Vector2d > uv_cur(f_cur.size());
-  for(size_t i=0, i_max=f_ref.size(); i<i_max; ++i)
-  {
-    uv_ref[i] = vk::project2d(f_ref[i]);
-    uv_cur[i] = vk::project2d(f_cur[i]);
-  }
-  vk::Homography Homography(uv_ref, uv_cur, focal_length, reprojection_threshold);
-  Homography.computeSE3fromMatches();
-  vector<int> outliers;
-  vk::computeInliers(f_cur, f_ref,
-                     Homography.T_c2_from_c1.rotation_matrix(), Homography.T_c2_from_c1.translation(),
-                     reprojection_threshold, focal_length,
-                     xyz_in_cur, inliers, outliers);
-  T_cur_from_ref = Homography.T_c2_from_c1;
-}
-
-
-} // namespace initialization
-} // namespace svo
diff --git a/CPU_version/svo/src/map.cpp b/CPU_version/svo/src/map.cpp
deleted file mode 100644
index 2ecad1c..0000000
--- a/CPU_version/svo/src/map.cpp
+++ /dev/null
@@ -1,368 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#include <set>
-#include <svo/map.h>
-#include <svo/point.h>
-#include <svo/frame.h>
-#include <svo/feature.h>
-#include <boost/bind.hpp>
-
-namespace svo {
-
-Map::Map() {}
-
-Map::~Map()
-{
-  reset();
-  SVO_INFO_STREAM("Map destructed");
-}
-
-void Map::reset()
-{
-  keyframes_.clear();
-  point_candidates_.reset();
-  emptyTrash();
-}
-
-bool Map::safeDeleteFrame(FramePtr frame)
-{
-  bool found = false;
-  for(auto it=keyframes_.begin(), ite=keyframes_.end(); it!=ite; ++it)
-  {
-    if(*it == frame)
-    {
-      std::for_each((*it)->fts_.begin(), (*it)->fts_.end(), [&](Feature* ftr){
-        removePtFrameRef(it->get(), ftr);
-      });
-      keyframes_.erase(it);
-      found = true;
-      break;
-    }
-  }
-
-  point_candidates_.removeFrameCandidates(frame);
-
-  if(found)
-    return true;
-
-  SVO_ERROR_STREAM("Tried to delete Keyframe in map which was not there.");
-  return false;
-}
-
-void Map::removePtFrameRef(Frame* frame, Feature* ftr)
-{
-  if(ftr->point == NULL)
-    return; // mappoint may have been deleted in a previous ref. removal
-  Point* pt = ftr->point;
-  ftr->point = NULL;
-  if(pt->obs_.size() <= 2)
-  {
-    // If the references list of mappoint has only size=2, delete mappoint
-    safeDeletePoint(pt);
-    return;
-  }
-  pt->deleteFrameRef(frame);  // Remove reference from map_point
-  frame->removeKeyPoint(ftr); // Check if mp was keyMp in keyframe
-}
-
-void Map::safeDeletePoint(Point* pt)
-{
-  // Delete references to mappoints in all keyframes
-  std::for_each(pt->obs_.begin(), pt->obs_.end(), [&](Feature* ftr){
-    ftr->point=NULL;
-    ftr->frame->removeKeyPoint(ftr);
-  });
-  pt->obs_.clear();
-
-  // Delete mappoint
-  deletePoint(pt);
-}
-
-void Map::deletePoint(Point* pt)
-{
-  pt->type_ = Point::TYPE_DELETED;
-  trash_points_.push_back(pt);
-}
-
-void Map::addKeyframe(FramePtr new_keyframe)
-{
-  keyframes_.push_back(new_keyframe);
-}
-
-void Map::getCloseKeyframes(
-    const FramePtr& frame,
-    std::list< std::pair<FramePtr,double> >& close_kfs) const
-{
-  for(auto kf : keyframes_)
-  {
-    // check if kf has overlaping field of view with frame, use therefore KeyPoints
-    for(auto keypoint : kf->key_pts_)
-    {
-      if(keypoint == nullptr)
-        continue;
-
-      if(frame->isVisible(keypoint->point->pos_))
-      {
-        close_kfs.push_back(
-            std::make_pair(
-                kf, (frame->T_f_w_.translation()-kf->T_f_w_.translation()).norm()));
-        break; // this keyframe has an overlapping field of view -> add to close_kfs
-      }
-    }
-  }
-}
-
-FramePtr Map::getClosestKeyframe(const FramePtr& frame) const
-{
-  list< pair<FramePtr,double> > close_kfs;
-  getCloseKeyframes(frame, close_kfs);
-  if(close_kfs.empty())
-  {
-    return nullptr;
-  }
-
-
-  // Sort KFs with overlap according to their closeness
-  close_kfs.sort(boost::bind(&std::pair<FramePtr, double>::second, _1) <
-                 boost::bind(&std::pair<FramePtr, double>::second, _2));
-
-  if(close_kfs.front().first != frame)
-    return close_kfs.front().first;
-  close_kfs.pop_front();
-  return close_kfs.front().first;
-}
-
-FramePtr Map::getFurthestKeyframe(const Vector3d& pos) const
-{
-  FramePtr furthest_kf;
-  double maxdist = 0.0;
-  for(auto it=keyframes_.begin(), ite=keyframes_.end(); it!=ite; ++it)
-  {
-    double dist = ((*it)->pos()-pos).norm();
-    if(dist > maxdist) {
-      maxdist = dist;
-      furthest_kf = *it;
-    }
-  }
-  return furthest_kf;
-}
-
-bool Map::getKeyframeById(const int id, FramePtr& frame) const
-{
-  bool found = false;
-  for(auto it=keyframes_.begin(), ite=keyframes_.end(); it!=ite; ++it)
-    if((*it)->id_ == id) {
-      found = true;
-      frame = *it;
-      break;
-    }
-  return found;
-}
-
-void Map::transform(const Matrix3d& R, const Vector3d& t, const double& s)
-{
-  for(auto it=keyframes_.begin(), ite=keyframes_.end(); it!=ite; ++it)
-  {
-    Vector3d pos = s*R*(*it)->pos() + t;
-    Matrix3d rot = R*(*it)->T_f_w_.rotation_matrix().inverse();
-    (*it)->T_f_w_ = SE3(rot, pos).inverse();
-    for(auto ftr=(*it)->fts_.begin(); ftr!=(*it)->fts_.end(); ++ftr)
-    {
-      if((*ftr)->point == NULL)
-        continue;
-      if((*ftr)->point->last_published_ts_ == -1000)
-        continue;
-      (*ftr)->point->last_published_ts_ = -1000;
-      (*ftr)->point->pos_ = s*R*(*ftr)->point->pos_ + t;
-    }
-  }
-}
-
-void Map::emptyTrash()
-{
-  std::for_each(trash_points_.begin(), trash_points_.end(), [&](Point*& pt){
-    delete pt;
-    pt=NULL;
-  });
-  trash_points_.clear();
-  point_candidates_.emptyTrash();
-}
-
-MapPointCandidates::MapPointCandidates()
-{}
-
-MapPointCandidates::~MapPointCandidates()
-{
-  reset();
-}
-
-void MapPointCandidates::newCandidatePoint(Point* point, double depth_sigma2)
-{
-  point->type_ = Point::TYPE_CANDIDATE;
-  boost::unique_lock<boost::mutex> lock(mut_);
-  candidates_.push_back(PointCandidate(point, point->obs_.front()));
-}
-
-void MapPointCandidates::addCandidatePointToFrame(FramePtr frame)
-{
-  boost::unique_lock<boost::mutex> lock(mut_);
-  PointCandidateList::iterator it=candidates_.begin();
-  while(it != candidates_.end())
-  {
-    if(it->first->obs_.front()->frame == frame.get())
-    {
-      // insert feature in the frame
-      it->first->type_ = Point::TYPE_UNKNOWN;
-      it->first->n_failed_reproj_ = 0;
-      it->second->frame->addFeature(it->second);
-      it = candidates_.erase(it);
-    }
-    else
-      ++it;
-  }
-}
-
-bool MapPointCandidates::deleteCandidatePoint(Point* point)
-{
-  boost::unique_lock<boost::mutex> lock(mut_);
-  for(auto it=candidates_.begin(), ite=candidates_.end(); it!=ite; ++it)
-  {
-    if(it->first == point)
-    {
-      deleteCandidate(*it);
-      candidates_.erase(it);
-      return true;
-    }
-  }
-  return false;
-}
-
-void MapPointCandidates::removeFrameCandidates(FramePtr frame)
-{
-  boost::unique_lock<boost::mutex> lock(mut_);
-  auto it=candidates_.begin();
-  while(it!=candidates_.end())
-  {
-    if(it->second->frame == frame.get())
-    {
-      deleteCandidate(*it);
-      it = candidates_.erase(it);
-    }
-    else
-      ++it;
-  }
-}
-
-void MapPointCandidates::reset()
-{
-  boost::unique_lock<boost::mutex> lock(mut_);
-  std::for_each(candidates_.begin(), candidates_.end(), [&](PointCandidate& c){
-    delete c.first;
-    delete c.second;
-  });
-  candidates_.clear();
-}
-
-void MapPointCandidates::deleteCandidate(PointCandidate& c)
-{
-  // camera-rig: another frame might still be pointing to the candidate point
-  // therefore, we can't delete it right now.
-  delete c.second; c.second=NULL;
-  c.first->type_ = Point::TYPE_DELETED;
-  trash_points_.push_back(c.first);
-}
-
-void MapPointCandidates::emptyTrash()
-{
-  std::for_each(trash_points_.begin(), trash_points_.end(), [&](Point*& p){
-    delete p; p=NULL;
-  });
-  trash_points_.clear();
-}
-
-namespace map_debug {
-
-void mapValidation(Map* map, int id)
-{
-  for(auto it=map->keyframes_.begin(); it!=map->keyframes_.end(); ++it)
-    frameValidation(it->get(), id);
-}
-
-void frameValidation(Frame* frame, int id)
-{
-  for(auto it = frame->fts_.begin(); it!=frame->fts_.end(); ++it)
-  {
-    if((*it)->point==NULL)
-      continue;
-
-    if((*it)->point->type_ == Point::TYPE_DELETED)
-      printf("ERROR DataValidation %i: Referenced point was deleted.\n", id);
-
-    if(!(*it)->point->findFrameRef(frame))
-      printf("ERROR DataValidation %i: Frame has reference but point does not have a reference back.\n", id);
-
-    pointValidation((*it)->point, id);
-  }
-  for(auto it=frame->key_pts_.begin(); it!=frame->key_pts_.end(); ++it)
-    if(*it != NULL)
-      if((*it)->point == NULL)
-        printf("ERROR DataValidation %i: KeyPoints not correct!\n", id);
-}
-
-void pointValidation(Point* point, int id)
-{
-  for(auto it=point->obs_.begin(); it!=point->obs_.end(); ++it)
-  {
-    bool found=false;
-    for(auto it_ftr=(*it)->frame->fts_.begin(); it_ftr!=(*it)->frame->fts_.end(); ++it_ftr)
-     if((*it_ftr)->point == point) {
-       found=true; break;
-     }
-    if(!found)
-      printf("ERROR DataValidation %i: Point %i has inconsistent reference in frame %i, is candidate = %i\n", id, point->id_, (*it)->frame->id_, (int) point->type_);
-  }
-}
-
-void mapStatistics(Map* map)
-{
-  // compute average number of features which each frame observes
-  size_t n_pt_obs(0);
-  for(auto it=map->keyframes_.begin(); it!=map->keyframes_.end(); ++it)
-    n_pt_obs += (*it)->nObs();
-  printf("\n\nMap Statistics: Frame avg. point obs = %f\n", (float) n_pt_obs/map->size());
-
-  // compute average number of observations that each point has
-  size_t n_frame_obs(0);
-  size_t n_pts(0);
-  std::set<Point*> points;
-  for(auto it=map->keyframes_.begin(); it!=map->keyframes_.end(); ++it)
-  {
-    for(auto ftr=(*it)->fts_.begin(); ftr!=(*it)->fts_.end(); ++ftr)
-    {
-      if((*ftr)->point == NULL)
-        continue;
-      if(points.insert((*ftr)->point).second) {
-        ++n_pts;
-        n_frame_obs += (*ftr)->point->nRefs();
-      }
-    }
-  }
-  printf("Map Statistics: Point avg. frame obs = %f\n\n", (float) n_frame_obs/n_pts);
-}
-
-} // namespace map_debug
-} // namespace svo
diff --git a/CPU_version/svo/src/matcher.cpp b/CPU_version/svo/src/matcher.cpp
deleted file mode 100644
index 38a89fb..0000000
--- a/CPU_version/svo/src/matcher.cpp
+++ /dev/null
@@ -1,323 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#include <cstdlib>
-#include <vikit/abstract_camera.h>
-#include <vikit/vision.h>
-#include <vikit/math_utils.h>
-#include <vikit/patch_score.h>
-#include <svo/matcher.h>
-#include <svo/frame.h>
-#include <svo/feature.h>
-#include <svo/point.h>
-#include <svo/config.h>
-#include <svo/feature_alignment.h>
-
-namespace svo {
-
-namespace warp {
-
-void getWarpMatrixAffine(
-    const vk::AbstractCamera& cam_ref,
-    const vk::AbstractCamera& cam_cur,
-    const Vector2d& px_ref,
-    const Vector3d& f_ref,
-    const double depth_ref,
-    const SE3& T_cur_ref,
-    const int level_ref,
-    Matrix2d& A_cur_ref)
-{
-  // Compute affine warp matrix A_ref_cur
-  const int halfpatch_size = 5;
-  const Vector3d xyz_ref(f_ref*depth_ref);
-  Vector3d xyz_du_ref(cam_ref.cam2world(px_ref + Vector2d(halfpatch_size,0)*(1<<level_ref)));
-  Vector3d xyz_dv_ref(cam_ref.cam2world(px_ref + Vector2d(0,halfpatch_size)*(1<<level_ref)));
-  xyz_du_ref *= xyz_ref[2]/xyz_du_ref[2];
-  xyz_dv_ref *= xyz_ref[2]/xyz_dv_ref[2];
-  const Vector2d px_cur(cam_cur.world2cam(T_cur_ref*(xyz_ref)));
-  const Vector2d px_du(cam_cur.world2cam(T_cur_ref*(xyz_du_ref)));
-  const Vector2d px_dv(cam_cur.world2cam(T_cur_ref*(xyz_dv_ref)));
-  A_cur_ref.col(0) = (px_du - px_cur)/halfpatch_size;
-  A_cur_ref.col(1) = (px_dv - px_cur)/halfpatch_size;
-}
-
-int getBestSearchLevel(
-    const Matrix2d& A_cur_ref,
-    const int max_level)
-{
-  // Compute patch level in other image
-  int search_level = 0;
-  double D = A_cur_ref.determinant();
-  while(D > 3.0 && search_level < max_level)
-  {
-    search_level += 1;
-    D *= 0.25;
-  }
-  return search_level;
-}
-
-void warpAffine(
-    const Matrix2d& A_cur_ref,
-    const cv::Mat& img_ref,
-    const Vector2d& px_ref,
-    const int level_ref,
-    const int search_level,
-    const int halfpatch_size,
-    uint8_t* patch)
-{
-  const int patch_size = halfpatch_size*2 ;
-  const Matrix2f A_ref_cur = A_cur_ref.inverse().cast<float>();
-  if(isnan(A_ref_cur(0,0)))
-  {
-    printf("Affine warp is NaN, probably camera has no translation\n"); // TODO
-    return;
-  }
-
-  // Perform the warp on a larger patch.
-  uint8_t* patch_ptr = patch;
-  const Vector2f px_ref_pyr = px_ref.cast<float>() / (1<<level_ref);
-  for (int y=0; y<patch_size; ++y)
-  {
-    for (int x=0; x<patch_size; ++x, ++patch_ptr)
-    {
-      Vector2f px_patch(x-halfpatch_size, y-halfpatch_size);
-      px_patch *= (1<<search_level);
-      const Vector2f px(A_ref_cur*px_patch + px_ref_pyr);
-      if (px[0]<0 || px[1]<0 || px[0]>=img_ref.cols-1 || px[1]>=img_ref.rows-1)
-        *patch_ptr = 0;
-      else
-        *patch_ptr = (uint8_t) vk::interpolateMat_8u(img_ref, px[0], px[1]);
-    }
-  }
-}
-
-} // namespace warp
-
-bool depthFromTriangulation(
-    const SE3& T_search_ref,
-    const Vector3d& f_ref,
-    const Vector3d& f_cur,
-    double& depth)
-{
-  Matrix<double,3,2> A; A << T_search_ref.rotation_matrix() * f_ref, f_cur;
-  const Matrix2d AtA = A.transpose()*A;
-  if(AtA.determinant() < 0.000001)
-    return false;
-  const Vector2d depth2 = - AtA.inverse()*A.transpose()*T_search_ref.translation();
-  depth = fabs(depth2[0]);
-  return true;
-}
-
-void Matcher::createPatchFromPatchWithBorder()
-{
-  uint8_t* ref_patch_ptr = patch_;
-  for(int y=1; y<patch_size_+1; ++y, ref_patch_ptr += patch_size_)
-  {
-    uint8_t* ref_patch_border_ptr = patch_with_border_ + y*(patch_size_+2) + 1;
-    for(int x=0; x<patch_size_; ++x)
-      ref_patch_ptr[x] = ref_patch_border_ptr[x];
-  }
-}
-
-bool Matcher::findMatchDirect(
-    const Point& pt,
-    const Frame& cur_frame,
-    Vector2d& px_cur)
-{
-  if(!pt.getCloseViewObs(cur_frame.pos(), ref_ftr_))
-    return false;
-
-  if(!ref_ftr_->frame->cam_->isInFrame(
-      ref_ftr_->px.cast<int>()/(1<<ref_ftr_->level), halfpatch_size_+2, ref_ftr_->level))
-    return false;
-
-  // warp affine
-  warp::getWarpMatrixAffine(
-      *ref_ftr_->frame->cam_, *cur_frame.cam_, ref_ftr_->px, ref_ftr_->f,
-      (ref_ftr_->frame->pos() - pt.pos_).norm(),
-      cur_frame.T_f_w_ * ref_ftr_->frame->T_f_w_.inverse(), ref_ftr_->level, A_cur_ref_);
-  search_level_ = warp::getBestSearchLevel(A_cur_ref_, Config::nPyrLevels()-1);
-  warp::warpAffine(A_cur_ref_, ref_ftr_->frame->img_pyr_[ref_ftr_->level], ref_ftr_->px,
-                   ref_ftr_->level, search_level_, halfpatch_size_+1, patch_with_border_);
-  createPatchFromPatchWithBorder();
-
-  // px_cur should be set
-  Vector2d px_scaled(px_cur/(1<<search_level_));
-
-  bool success = false;
-  if(ref_ftr_->type == Feature::EDGELET)
-  {
-    Vector2d dir_cur(A_cur_ref_*ref_ftr_->grad);
-    dir_cur.normalize();
-    success = feature_alignment::align1D(
-          cur_frame.img_pyr_[search_level_], dir_cur.cast<float>(),
-          patch_with_border_, patch_, options_.align_max_iter, px_scaled, h_inv_);
-  }
-  else
-  {
-    success = feature_alignment::align2D(
-      cur_frame.img_pyr_[search_level_], patch_with_border_, patch_,
-      options_.align_max_iter, px_scaled);
-  }
-  px_cur = px_scaled * (1<<search_level_);
-  return success;
-}
-
-bool Matcher::findEpipolarMatchDirect(
-    const Frame& ref_frame,
-    const Frame& cur_frame,
-    const Feature& ref_ftr,
-    const double d_estimate,
-    const double d_min,
-    const double d_max,
-    double& depth)
-{
-  SE3 T_cur_ref = cur_frame.T_f_w_ * ref_frame.T_f_w_.inverse();
-  int zmssd_best = PatchScore::threshold();
-  Vector2d uv_best;
-
-  // Compute start and end of epipolar line in old_kf for match search, on unit plane!
-  Vector2d A = vk::project2d(T_cur_ref * (ref_ftr.f*d_min));
-  Vector2d B = vk::project2d(T_cur_ref * (ref_ftr.f*d_max));
-  epi_dir_ = A - B;
-
-  // Compute affine warp matrix
-  warp::getWarpMatrixAffine(
-      *ref_frame.cam_, *cur_frame.cam_, ref_ftr.px, ref_ftr.f,
-      d_estimate, T_cur_ref, ref_ftr.level, A_cur_ref_);
-
-  // feature pre-selection
-  reject_ = false;
-  if(ref_ftr.type == Feature::EDGELET && options_.epi_search_edgelet_filtering)
-  {
-    const Vector2d grad_cur = (A_cur_ref_ * ref_ftr.grad).normalized();
-    const double cosangle = fabs(grad_cur.dot(epi_dir_.normalized()));
-    if(cosangle < options_.epi_search_edgelet_max_angle) {
-      reject_ = true;
-      return false;
-    }
-  }
-
-  search_level_ = warp::getBestSearchLevel(A_cur_ref_, Config::nPyrLevels()-1);
-
-  // Find length of search range on epipolar line
-  Vector2d px_A(cur_frame.cam_->world2cam(A));
-  Vector2d px_B(cur_frame.cam_->world2cam(B));
-  epi_length_ = (px_A-px_B).norm() / (1<<search_level_);
-
-  // Warp reference patch at ref_level
-  warp::warpAffine(A_cur_ref_, ref_frame.img_pyr_[ref_ftr.level], ref_ftr.px,
-                   ref_ftr.level, search_level_, halfpatch_size_+1, patch_with_border_);
-  createPatchFromPatchWithBorder();
-
-  if(epi_length_ < 2.0)
-  {
-    px_cur_ = (px_A+px_B)/2.0;
-    Vector2d px_scaled(px_cur_/(1<<search_level_));
-    bool res;
-    if(options_.align_1d)
-      res = feature_alignment::align1D(
-          cur_frame.img_pyr_[search_level_], (px_A-px_B).cast<float>().normalized(),
-          patch_with_border_, patch_, options_.align_max_iter, px_scaled, h_inv_);
-    else
-      res = feature_alignment::align2D(
-          cur_frame.img_pyr_[search_level_], patch_with_border_, patch_,
-          options_.align_max_iter, px_scaled);
-    if(res)
-    {
-      px_cur_ = px_scaled*(1<<search_level_);
-      if(depthFromTriangulation(T_cur_ref, ref_ftr.f, cur_frame.cam_->cam2world(px_cur_), depth))
-        return true;
-    }
-    return false;
-  }
-
-  size_t n_steps = epi_length_/0.7; // one step per pixel
-  Vector2d step = epi_dir_/n_steps;
-
-  if(n_steps > options_.max_epi_search_steps)
-  {
-    printf("WARNING: skip epipolar search: %zu evaluations, px_lenght=%f, d_min=%f, d_max=%f.\n",
-           n_steps, epi_length_, d_min, d_max);
-    return false;
-  }
-
-  // for matching, precompute sum and sum2 of warped reference patch
-  int pixel_sum = 0;
-  int pixel_sum_square = 0;
-  PatchScore patch_score(patch_);
-
-  // now we sample along the epipolar line
-  Vector2d uv = B-step;
-  Vector2i last_checked_pxi(0,0);
-  ++n_steps;
-  for(size_t i=0; i<n_steps; ++i, uv+=step)
-  {
-    Vector2d px(cur_frame.cam_->world2cam(uv));
-    Vector2i pxi(px[0]/(1<<search_level_)+0.5,
-                 px[1]/(1<<search_level_)+0.5); // +0.5 to round to closest int
-
-    if(pxi == last_checked_pxi)
-      continue;
-    last_checked_pxi = pxi;
-
-    // check if the patch is full within the new frame
-    if(!cur_frame.cam_->isInFrame(pxi, patch_size_, search_level_))
-      continue;
-
-    // TODO interpolation would probably be a good idea
-    uint8_t* cur_patch_ptr = cur_frame.img_pyr_[search_level_].data
-                             + (pxi[1]-halfpatch_size_)*cur_frame.img_pyr_[search_level_].cols
-                             + (pxi[0]-halfpatch_size_);
-    int zmssd = patch_score.computeScore(cur_patch_ptr, cur_frame.img_pyr_[search_level_].cols);
-
-    if(zmssd < zmssd_best) {
-      zmssd_best = zmssd;
-      uv_best = uv;
-    }
-  }
-
-  if(zmssd_best < PatchScore::threshold())
-  {
-    if(options_.subpix_refinement)
-    {
-      px_cur_ = cur_frame.cam_->world2cam(uv_best);
-      Vector2d px_scaled(px_cur_/(1<<search_level_));
-      bool res;
-      if(options_.align_1d)
-        res = feature_alignment::align1D(
-            cur_frame.img_pyr_[search_level_], (px_A-px_B).cast<float>().normalized(),
-            patch_with_border_, patch_, options_.align_max_iter, px_scaled, h_inv_);
-      else
-        res = feature_alignment::align2D(
-            cur_frame.img_pyr_[search_level_], patch_with_border_, patch_,
-            options_.align_max_iter, px_scaled);
-      if(res)
-      {
-        px_cur_ = px_scaled*(1<<search_level_);
-        if(depthFromTriangulation(T_cur_ref, ref_ftr.f, cur_frame.cam_->cam2world(px_cur_), depth))
-          return true;
-      }
-      return false;
-    }
-    px_cur_ = cur_frame.cam_->world2cam(uv_best);
-    if(depthFromTriangulation(T_cur_ref, ref_ftr.f, vk::unproject2d(uv_best).normalized(), depth))
-      return true;
-  }
-  return false;
-}
-
-} // namespace svo
diff --git a/CPU_version/svo/src/point.cpp b/CPU_version/svo/src/point.cpp
deleted file mode 100644
index 2e45e06..0000000
--- a/CPU_version/svo/src/point.cpp
+++ /dev/null
@@ -1,179 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#include <stdexcept>
-#include <vikit/math_utils.h>
-#include <svo/point.h>
-#include <svo/frame.h>
-#include <svo/feature.h>
- 
-namespace svo {
-
-int Point::point_counter_ = 0;
-
-Point::Point(const Vector3d& pos) :
-  id_(point_counter_++),
-  pos_(pos),
-  normal_set_(false),
-  n_obs_(0),
-  v_pt_(NULL),
-  last_published_ts_(0),
-  last_projected_kf_id_(-1),
-  type_(TYPE_UNKNOWN),
-  n_failed_reproj_(0),
-  n_succeeded_reproj_(0),
-  last_structure_optim_(0)
-{}
-
-Point::Point(const Vector3d& pos, Feature* ftr) :
-  id_(point_counter_++),
-  pos_(pos),
-  normal_set_(false),
-  n_obs_(1),
-  v_pt_(NULL),
-  last_published_ts_(0),
-  last_projected_kf_id_(-1),
-  type_(TYPE_UNKNOWN),
-  n_failed_reproj_(0),
-  n_succeeded_reproj_(0),
-  last_structure_optim_(0)
-{
-  obs_.push_front(ftr);
-}
-
-Point::~Point()
-{}
-
-void Point::addFrameRef(Feature* ftr)
-{
-  obs_.push_front(ftr);
-  ++n_obs_;
-}
-
-Feature* Point::findFrameRef(Frame* frame)
-{
-  for(auto it=obs_.begin(), ite=obs_.end(); it!=ite; ++it)
-    if((*it)->frame == frame)
-      return *it;
-  return NULL;    // no keyframe found
-}
-
-bool Point::deleteFrameRef(Frame* frame)
-{
-  for(auto it=obs_.begin(), ite=obs_.end(); it!=ite; ++it)
-  {
-    if((*it)->frame == frame)
-    {
-      obs_.erase(it);
-      return true;
-    }
-  }
-  return false;
-}
-
-void Point::initNormal()
-{
-  assert(!obs_.empty());
-  const Feature* ftr = obs_.back();
-  assert(ftr->frame != NULL);
-  normal_ = ftr->frame->T_f_w_.rotation_matrix().transpose()*(-ftr->f);
-  normal_information_ = DiagonalMatrix<double,3,3>(pow(20/(pos_-ftr->frame->pos()).norm(),2), 1.0, 1.0);
-  normal_set_ = true;
-}
-
-bool Point::getCloseViewObs(const Vector3d& framepos, Feature*& ftr) const
-{
-  // TODO: get frame with same point of view AND same pyramid level!
-  Vector3d obs_dir(framepos - pos_); obs_dir.normalize();
-  auto min_it=obs_.begin();
-  double min_cos_angle = 0;
-  for(auto it=obs_.begin(), ite=obs_.end(); it!=ite; ++it)
-  {
-    Vector3d dir((*it)->frame->pos() - pos_); dir.normalize();
-    double cos_angle = obs_dir.dot(dir);
-    if(cos_angle > min_cos_angle)
-    {
-      min_cos_angle = cos_angle;
-      min_it = it;
-    }
-  }
-  ftr = *min_it;
-  if(min_cos_angle < 0.5) // assume that observations larger than 60° are useless
-    return false;
-  return true;
-}
-
-void Point::optimize(const size_t n_iter)
-{
-  Vector3d old_point = pos_;
-  double chi2 = 0.0;
-  Matrix3d A;
-  Vector3d b;
-
-  for(size_t i=0; i<n_iter; i++)
-  {
-    A.setZero();
-    b.setZero();
-    double new_chi2 = 0.0;
-
-    // compute residuals
-    for(auto it=obs_.begin(); it!=obs_.end(); ++it)
-    {
-      Matrix23d J;
-      const Vector3d p_in_f((*it)->frame->T_f_w_ * pos_);
-      Point::jacobian_xyz2uv(p_in_f, (*it)->frame->T_f_w_.rotation_matrix(), J);
-      const Vector2d e(vk::project2d((*it)->f) - vk::project2d(p_in_f));
-      new_chi2 += e.squaredNorm();
-      A.noalias() += J.transpose() * J;
-      b.noalias() -= J.transpose() * e;
-    }
-
-    // solve linear system
-    const Vector3d dp(A.ldlt().solve(b));
-
-    // check if error increased
-    if((i > 0 && new_chi2 > chi2) || (bool) std::isnan((double)dp[0]))
-    {
-#ifdef POINT_OPTIMIZER_DEBUG
-      cout << "it " << i
-           << "\t FAILURE \t new_chi2 = " << new_chi2 << endl;
-#endif
-      pos_ = old_point; // roll-back
-      break;
-    }
-
-    // update the model
-    Vector3d new_point = pos_ + dp;
-    old_point = pos_;
-    pos_ = new_point;
-    chi2 = new_chi2;
-#ifdef POINT_OPTIMIZER_DEBUG
-    cout << "it " << i
-         << "\t Success \t new_chi2 = " << new_chi2
-         << "\t norm(b) = " << vk::norm_max(b)
-         << endl;
-#endif
-
-    // stop when converged
-    if(vk::norm_max(dp) <= EPS)
-      break;
-  }
-#ifdef POINT_OPTIMIZER_DEBUG
-  cout << endl;
-#endif
-}
-
-} // namespace svo
diff --git a/CPU_version/svo/src/pose_optimizer.cpp b/CPU_version/svo/src/pose_optimizer.cpp
deleted file mode 100644
index 1c491b0..0000000
--- a/CPU_version/svo/src/pose_optimizer.cpp
+++ /dev/null
@@ -1,165 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#include <stdexcept>
-#include <svo/pose_optimizer.h>
-#include <svo/frame.h>
-#include <svo/feature.h>
-#include <svo/point.h>
-#include <vikit/robust_cost.h>
-#include <vikit/math_utils.h>
-
-namespace svo {
-namespace pose_optimizer {
-
-void optimizeGaussNewton(
-    const double reproj_thresh,
-    const size_t n_iter,
-    const bool verbose,
-    FramePtr& frame,
-    double& estimated_scale,
-    double& error_init,
-    double& error_final,
-    size_t& num_obs)
-{
-  // init
-  double chi2(0.0);
-  vector<double> chi2_vec_init, chi2_vec_final;
-  vk::robust_cost::TukeyWeightFunction weight_function;
-  SE3 T_old(frame->T_f_w_);
-  Matrix6d A;
-  Vector6d b;
-
-  // compute the scale of the error for robust estimation
-  std::vector<float> errors; errors.reserve(frame->fts_.size());
-  for(auto it=frame->fts_.begin(); it!=frame->fts_.end(); ++it)
-  {
-    if((*it)->point == NULL)
-      continue;
-    //Reprojection error
-    Vector2d e = vk::project2d((*it)->f)
-               - vk::project2d(frame->T_f_w_ * (*it)->point->pos_);
-    e *= 1.0 / (1<<(*it)->level);
-    errors.push_back(e.norm());
-  }
-  if(errors.empty())
-    return;
-  vk::robust_cost::MADScaleEstimator scale_estimator;
-  estimated_scale = scale_estimator.compute(errors);
-
-  num_obs = errors.size();
-  chi2_vec_init.reserve(num_obs);
-  chi2_vec_final.reserve(num_obs);
-  double scale = estimated_scale;
-  for(size_t iter=0; iter<n_iter; iter++)
-  {
-    // overwrite scale
-    if(iter == 5)
-      scale = 0.85/frame->cam_->errorMultiplier2();
-
-    b.setZero();
-    A.setZero();
-    double new_chi2(0.0);
-
-    // compute residual
-    for(auto it=frame->fts_.begin(); it!=frame->fts_.end(); ++it)
-    {
-      if((*it)->point == NULL)
-        continue;
-      Matrix26d J;
-      Vector3d xyz_f(frame->T_f_w_ * (*it)->point->pos_);
-      Frame::jacobian_xyz2uv(xyz_f, J);
-      Vector2d e = vk::project2d((*it)->f) - vk::project2d(xyz_f);
-      double sqrt_inv_cov = 1.0 / (1<<(*it)->level);
-      e *= sqrt_inv_cov;
-      if(iter == 0)
-        chi2_vec_init.push_back(e.squaredNorm()); // just for debug
-      J *= sqrt_inv_cov;
-      double weight = weight_function.value(e.norm()/scale);
-      A.noalias() += J.transpose()*J*weight;
-      b.noalias() -= J.transpose()*e*weight;
-      new_chi2 += e.squaredNorm()*weight;
-    }
-
-    // solve linear system
-    const Vector6d dT(A.ldlt().solve(b));
-
-    // check if error increased
-    if((iter > 0 && new_chi2 > chi2) || (bool) std::isnan((double)dT[0]))
-    {
-      if(verbose)
-        std::cout << "it " << iter
-                  << "\t FAILURE \t new_chi2 = " << new_chi2 << std::endl;
-      frame->T_f_w_ = T_old; // roll-back
-      break;
-    }
-
-    // update the model
-    SE3 T_new = SE3::exp(dT)*frame->T_f_w_;
-    T_old = frame->T_f_w_;
-    frame->T_f_w_ = T_new;
-    chi2 = new_chi2;
-    if(verbose)
-      std::cout << "it " << iter
-                << "\t Success \t new_chi2 = " << new_chi2
-                << "\t norm(dT) = " << vk::norm_max(dT) << std::endl;
-
-    // stop when converged
-    if(vk::norm_max(dT) <= EPS)
-      break;
-  }
-
-  // Set covariance as inverse information matrix. Optimistic estimator!
-  const double pixel_variance=1.0;
-  frame->Cov_ = pixel_variance*(A*std::pow(frame->cam_->errorMultiplier2(),2)).inverse();
-
-  // Remove Measurements with too large reprojection error
-  double reproj_thresh_scaled = reproj_thresh / frame->cam_->errorMultiplier2();
-  size_t n_deleted_refs = 0;
-  for(Features::iterator it=frame->fts_.begin(); it!=frame->fts_.end(); ++it)
-  {
-    if((*it)->point == NULL)
-      continue;
-    Vector2d e = vk::project2d((*it)->f) - vk::project2d(frame->T_f_w_ * (*it)->point->pos_);
-    double sqrt_inv_cov = 1.0 / (1<<(*it)->level);
-    e *= sqrt_inv_cov;
-    chi2_vec_final.push_back(e.squaredNorm());
-    if(e.norm() > reproj_thresh_scaled)
-    {
-      // we don't need to delete a reference in the point since it was not created yet
-      (*it)->point = NULL;
-      ++n_deleted_refs;
-    }
-  }
-
-  error_init=0.0;
-  error_final=0.0;
-  if(!chi2_vec_init.empty())
-    error_init = sqrt(vk::getMedian(chi2_vec_init))*frame->cam_->errorMultiplier2();
-  if(!chi2_vec_final.empty())
-    error_final = sqrt(vk::getMedian(chi2_vec_final))*frame->cam_->errorMultiplier2();
-
-  estimated_scale *= frame->cam_->errorMultiplier2();
-  if(verbose)
-    std::cout << "n deleted obs = " << n_deleted_refs
-              << "\t scale = " << estimated_scale
-              << "\t error init = " << error_init
-              << "\t error end = " << error_final << std::endl;
-  num_obs -= n_deleted_refs;
-}
-
-} // namespace pose_optimizer
-} // namespace svo
diff --git a/CPU_version/svo/src/reprojector.cpp b/CPU_version/svo/src/reprojector.cpp
deleted file mode 100644
index 81a7835..0000000
--- a/CPU_version/svo/src/reprojector.cpp
+++ /dev/null
@@ -1,219 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#include <algorithm>
-#include <stdexcept>
-#include <svo/reprojector.h>
-#include <svo/frame.h>
-#include <svo/point.h>
-#include <svo/feature.h>
-#include <svo/map.h>
-#include <svo/config.h>
-#include <boost/bind.hpp>
-#include <boost/thread.hpp>
-#include <vikit/abstract_camera.h>
-#include <vikit/math_utils.h>
-#include <vikit/timer.h>
-
-namespace svo {
-
-Reprojector::Reprojector(vk::AbstractCamera* cam, Map& map) :
-    map_(map)
-{
-  initializeGrid(cam);
-}
-
-Reprojector::~Reprojector()
-{
-  std::for_each(grid_.cells.begin(), grid_.cells.end(), [&](Cell* c){ delete c; });
-}
-
-void Reprojector::initializeGrid(vk::AbstractCamera* cam)
-{
-  grid_.cell_size = Config::gridSize();
-  grid_.grid_n_cols = ceil(static_cast<double>(cam->width())/grid_.cell_size);
-  grid_.grid_n_rows = ceil(static_cast<double>(cam->height())/grid_.cell_size);
-  grid_.cells.resize(grid_.grid_n_cols*grid_.grid_n_rows);
-  std::for_each(grid_.cells.begin(), grid_.cells.end(), [&](Cell*& c){ c = new Cell; });
-  grid_.cell_order.resize(grid_.cells.size());
-  for(size_t i=0; i<grid_.cells.size(); ++i)
-    grid_.cell_order[i] = i;
-  random_shuffle(grid_.cell_order.begin(), grid_.cell_order.end()); // maybe we should do it at every iteration!
-}
-
-void Reprojector::resetGrid()
-{
-  n_matches_ = 0;
-  n_trials_ = 0;
-  std::for_each(grid_.cells.begin(), grid_.cells.end(), [&](Cell* c){ c->clear(); });
-}
-
-void Reprojector::reprojectMap(
-    FramePtr frame,
-    std::vector< std::pair<FramePtr,std::size_t> >& overlap_kfs)
-{
-  resetGrid();
-
-  // Identify those Keyframes which share a common field of view.
-  SVO_START_TIMER("reproject_kfs");
-  list< pair<FramePtr,double> > close_kfs;
-  map_.getCloseKeyframes(frame, close_kfs);
-
-  // Sort KFs with overlap according to their closeness
-  close_kfs.sort(boost::bind(&std::pair<FramePtr, double>::second, _1) <
-                 boost::bind(&std::pair<FramePtr, double>::second, _2));
-
-  // Reproject all mappoints of the closest N kfs with overlap. We only store
-  // in which grid cell the points fall.
-  size_t n = 0;
-  overlap_kfs.reserve(options_.max_n_kfs);
-  for(auto it_frame=close_kfs.begin(), ite_frame=close_kfs.end();
-      it_frame!=ite_frame && n<options_.max_n_kfs; ++it_frame, ++n)
-  {
-    FramePtr ref_frame = it_frame->first;
-    overlap_kfs.push_back(pair<FramePtr,size_t>(ref_frame,0));
-
-    // Try to reproject each mappoint that the other KF observes
-    for(auto it_ftr=ref_frame->fts_.begin(), ite_ftr=ref_frame->fts_.end();
-        it_ftr!=ite_ftr; ++it_ftr)
-    {
-      // check if the feature has a mappoint assigned
-      if((*it_ftr)->point == NULL)
-        continue;
-
-      // make sure we project a point only once
-      if((*it_ftr)->point->last_projected_kf_id_ == frame->id_)
-        continue;
-      (*it_ftr)->point->last_projected_kf_id_ = frame->id_;
-      if(reprojectPoint(frame, (*it_ftr)->point))
-        overlap_kfs.back().second++;
-    }
-  }
-  SVO_STOP_TIMER("reproject_kfs");
-
-  // Now project all point candidates
-  SVO_START_TIMER("reproject_candidates");
-  {
-    boost::unique_lock<boost::mutex> lock(map_.point_candidates_.mut_);
-    auto it=map_.point_candidates_.candidates_.begin();
-    while(it!=map_.point_candidates_.candidates_.end())
-    {
-      if(!reprojectPoint(frame, it->first))
-      {
-        it->first->n_failed_reproj_ += 3;
-        if(it->first->n_failed_reproj_ > 30)
-        {
-          map_.point_candidates_.deleteCandidate(*it);
-          it = map_.point_candidates_.candidates_.erase(it);
-          continue;
-        }
-      }
-      ++it;
-    }
-  } // unlock the mutex when out of scope
-  SVO_STOP_TIMER("reproject_candidates");
-
-  // Now we go through each grid cell and select one point to match.
-  // At the end, we should have at maximum one reprojected point per cell.
-  SVO_START_TIMER("feature_align");
-  for(size_t i=0; i<grid_.cells.size(); ++i)
-  {
-    // we prefer good quality points over unkown quality (more likely to match)
-    // and unknown quality over candidates (position not optimized)
-    if(reprojectCell(*grid_.cells.at(grid_.cell_order[i]), frame))
-      ++n_matches_;
-    if(n_matches_ > (size_t) Config::maxFts())
-      break;
-  }
-  SVO_STOP_TIMER("feature_align");
-}
-
-bool Reprojector::pointQualityComparator(Candidate& lhs, Candidate& rhs)
-{
-  if(lhs.pt->type_ > rhs.pt->type_)
-    return true;
-  return false;
-}
-
-bool Reprojector::reprojectCell(Cell& cell, FramePtr frame)
-{
-  cell.sort(boost::bind(&Reprojector::pointQualityComparator, _1, _2));
-  Cell::iterator it=cell.begin();
-  while(it!=cell.end())
-  {
-    ++n_trials_;
-
-    if(it->pt->type_ == Point::TYPE_DELETED)
-    {
-      it = cell.erase(it);
-      continue;
-    }
-
-    bool found_match = true;
-    if(options_.find_match_direct)
-      found_match = matcher_.findMatchDirect(*it->pt, *frame, it->px);
-    if(!found_match)
-    {
-      it->pt->n_failed_reproj_++;
-      if(it->pt->type_ == Point::TYPE_UNKNOWN && it->pt->n_failed_reproj_ > 15)
-        map_.safeDeletePoint(it->pt);
-      if(it->pt->type_ == Point::TYPE_CANDIDATE  && it->pt->n_failed_reproj_ > 30)
-        map_.point_candidates_.deleteCandidatePoint(it->pt);
-      it = cell.erase(it);
-      continue;
-    }
-    it->pt->n_succeeded_reproj_++;
-    if(it->pt->type_ == Point::TYPE_UNKNOWN && it->pt->n_succeeded_reproj_ > 10)
-      it->pt->type_ = Point::TYPE_GOOD;
-
-    Feature* new_feature = new Feature(frame.get(), it->px, matcher_.search_level_);
-    frame->addFeature(new_feature);
-
-    // Here we add a reference in the feature to the 3D point, the other way
-    // round is only done if this frame is selected as keyframe.
-    new_feature->point = it->pt;
-
-    if(matcher_.ref_ftr_->type == Feature::EDGELET)
-    {
-      new_feature->type = Feature::EDGELET;
-      new_feature->grad = matcher_.A_cur_ref_*matcher_.ref_ftr_->grad;
-      new_feature->grad.normalize();
-    }
-
-    // If the keyframe is selected and we reproject the rest, we don't have to
-    // check this point anymore.
-    it = cell.erase(it);
-
-    // Maximum one point per cell.
-    return true;
-  }
-  return false;
-}
-
-bool Reprojector::reprojectPoint(FramePtr frame, Point* point)
-{
-  Vector2d px(frame->w2c(point->pos_));
-  if(frame->cam_->isInFrame(px.cast<int>(), 8)) // 8px is the patch size in the matcher
-  {
-    const int k = static_cast<int>(px[1]/grid_.cell_size)*grid_.grid_n_cols
-                + static_cast<int>(px[0]/grid_.cell_size);
-    grid_.cells.at(k)->push_back(Candidate(point, px));
-    return true;
-  }
-  return false;
-}
-
-} // namespace svo
diff --git a/CPU_version/svo/src/sparse_img_align.cpp b/CPU_version/svo/src/sparse_img_align.cpp
deleted file mode 100644
index ce1570b..0000000
--- a/CPU_version/svo/src/sparse_img_align.cpp
+++ /dev/null
@@ -1,274 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#include <algorithm>
-#include <svo/sparse_img_align.h>
-#include <svo/frame.h>
-#include <svo/feature.h>
-#include <svo/config.h>
-#include <svo/point.h>
-#include <vikit/abstract_camera.h>
-#include <vikit/vision.h>
-#include <vikit/math_utils.h>
-
-namespace svo {
-
-SparseImgAlign::SparseImgAlign(
-    int max_level, int min_level, int n_iter,
-    Method method, bool display, bool verbose) :
-        display_(display),
-        max_level_(max_level),
-        min_level_(min_level)
-{
-  n_iter_ = n_iter;
-  n_iter_init_ = n_iter_;
-  method_ = method;
-  verbose_ = verbose;
-  eps_ = 0.000001;
-}
-
-size_t SparseImgAlign::run(FramePtr ref_frame, FramePtr cur_frame)
-{
-  reset();
-
-  if(ref_frame->fts_.empty())
-  {
-    SVO_WARN_STREAM("SparseImgAlign: no features to track!");
-    return 0;
-  }
-
-  ref_frame_ = ref_frame;
-  cur_frame_ = cur_frame;
-  ref_patch_cache_ = cv::Mat(ref_frame_->fts_.size(), patch_area_, CV_32F);
-  jacobian_cache_.resize(Eigen::NoChange, ref_patch_cache_.rows*patch_area_);
-  visible_fts_.resize(ref_patch_cache_.rows, false); // TODO: should it be reset at each level?
-
-  SE3 T_cur_from_ref(cur_frame_->T_f_w_ * ref_frame_->T_f_w_.inverse());
-
-  for(level_=max_level_; level_>=min_level_; --level_)
-  {
-    mu_ = 0.1;
-    jacobian_cache_.setZero();
-    have_ref_patch_cache_ = false;
-    if(verbose_)
-      printf("\nPYRAMID LEVEL %i\n---------------\n", level_);
-    optimize(T_cur_from_ref);
-  }
-  cur_frame_->T_f_w_ = T_cur_from_ref * ref_frame_->T_f_w_;
-
-
-
-  return n_meas_/patch_area_;
-}
-
-Matrix<double, 6, 6> SparseImgAlign::getFisherInformation()
-{
-  double sigma_i_sq = 5e-4*255*255; // image noise
-  Matrix<double,6,6> I = H_/sigma_i_sq;
-  return I;
-}
-
-void SparseImgAlign::precomputeReferencePatches()
-{
-  const int border = patch_halfsize_+1;
-  const cv::Mat& ref_img = ref_frame_->img_pyr_.at(level_);
-  const int stride = ref_img.cols;
-  const float scale = 1.0f/(1<<level_);
-  const Vector3d ref_pos = ref_frame_->pos();
-  const double focal_length = ref_frame_->cam_->errorMultiplier2();
-  size_t feature_counter = 0;
-  std::vector<bool>::iterator visiblity_it = visible_fts_.begin();
-  for(auto it=ref_frame_->fts_.begin(), ite=ref_frame_->fts_.end();
-      it!=ite; ++it, ++feature_counter, ++visiblity_it)
-  {
-    // check if reference with patch size is within image
-    const float u_ref = (*it)->px[0]*scale;
-    const float v_ref = (*it)->px[1]*scale;
-    const int u_ref_i = floorf(u_ref);
-    const int v_ref_i = floorf(v_ref);
-    if((*it)->point == NULL || u_ref_i-border < 0 || v_ref_i-border < 0 || u_ref_i+border >= ref_img.cols || v_ref_i+border >= ref_img.rows)
-      continue;
-    *visiblity_it = true;
-
-    // cannot just take the 3d points coordinate because of the reprojection errors in the reference image!!!
-    const double depth(((*it)->point->pos_ - ref_pos).norm());
-    const Vector3d xyz_ref((*it)->f*depth);
-
-    // evaluate projection jacobian
-    Matrix<double,2,6> frame_jac;
-    Frame::jacobian_xyz2uv(xyz_ref, frame_jac);
-
-    // compute bilateral interpolation weights for reference image
-    const float subpix_u_ref = u_ref-u_ref_i;
-    const float subpix_v_ref = v_ref-v_ref_i;
-    const float w_ref_tl = (1.0-subpix_u_ref) * (1.0-subpix_v_ref);
-    const float w_ref_tr = subpix_u_ref * (1.0-subpix_v_ref);
-    const float w_ref_bl = (1.0-subpix_u_ref) * subpix_v_ref;
-    const float w_ref_br = subpix_u_ref * subpix_v_ref;
-    size_t pixel_counter = 0;
-    float* cache_ptr = reinterpret_cast<float*>(ref_patch_cache_.data) + patch_area_*feature_counter;
-    for(int y=0; y<patch_size_; ++y)
-    {
-      uint8_t* ref_img_ptr = (uint8_t*) ref_img.data + (v_ref_i+y-patch_halfsize_)*stride + (u_ref_i-patch_halfsize_);
-      for(int x=0; x<patch_size_; ++x, ++ref_img_ptr, ++cache_ptr, ++pixel_counter)
-      {
-        // precompute interpolated reference patch color
-        *cache_ptr = w_ref_tl*ref_img_ptr[0] + w_ref_tr*ref_img_ptr[1] + w_ref_bl*ref_img_ptr[stride] + w_ref_br*ref_img_ptr[stride+1];
-
-        // we use the inverse compositional: thereby we can take the gradient always at the same position
-        // get gradient of warped image (~gradient at warped position)
-        float dx = 0.5f * ((w_ref_tl*ref_img_ptr[1] + w_ref_tr*ref_img_ptr[2] + w_ref_bl*ref_img_ptr[stride+1] + w_ref_br*ref_img_ptr[stride+2])
-                          -(w_ref_tl*ref_img_ptr[-1] + w_ref_tr*ref_img_ptr[0] + w_ref_bl*ref_img_ptr[stride-1] + w_ref_br*ref_img_ptr[stride]));
-        float dy = 0.5f * ((w_ref_tl*ref_img_ptr[stride] + w_ref_tr*ref_img_ptr[1+stride] + w_ref_bl*ref_img_ptr[stride*2] + w_ref_br*ref_img_ptr[stride*2+1])
-                          -(w_ref_tl*ref_img_ptr[-stride] + w_ref_tr*ref_img_ptr[1-stride] + w_ref_bl*ref_img_ptr[0] + w_ref_br*ref_img_ptr[1]));
-
-        // cache the jacobian
-        jacobian_cache_.col(feature_counter*patch_area_ + pixel_counter) =
-            (dx*frame_jac.row(0) + dy*frame_jac.row(1))*(focal_length / (1<<level_));
-      }
-    }
-  }
-  have_ref_patch_cache_ = true;
-}
-
-double SparseImgAlign::computeResiduals(
-    const SE3& T_cur_from_ref,
-    bool linearize_system,
-    bool compute_weight_scale)
-{
-  // Warp the (cur)rent image such that it aligns with the (ref)erence image
-  const cv::Mat& cur_img = cur_frame_->img_pyr_.at(level_);
-
-  if(linearize_system && display_)
-    resimg_ = cv::Mat(cur_img.size(), CV_32F, cv::Scalar(0));
-
-  if(have_ref_patch_cache_ == false)
-    precomputeReferencePatches();
-
-  // compute the weights on the first iteration
-  std::vector<float> errors;
-  if(compute_weight_scale)
-    errors.reserve(visible_fts_.size());
-  const int stride = cur_img.cols;
-  const int border = patch_halfsize_+1;
-  const float scale = 1.0f/(1<<level_);
-  const Vector3d ref_pos(ref_frame_->pos());
-  float chi2 = 0.0;
-  size_t feature_counter = 0; // is used to compute the index of the cached jacobian
-  std::vector<bool>::iterator visiblity_it = visible_fts_.begin();
-  for(auto it=ref_frame_->fts_.begin(); it!=ref_frame_->fts_.end();
-      ++it, ++feature_counter, ++visiblity_it)
-  {
-    // check if feature is within image
-    if(!*visiblity_it)
-      continue;
-
-    // compute pixel location in cur img
-    const double depth = ((*it)->point->pos_ - ref_pos).norm();
-    const Vector3d xyz_ref((*it)->f*depth);
-    const Vector3d xyz_cur(T_cur_from_ref * xyz_ref);
-    const Vector2f uv_cur_pyr(cur_frame_->cam_->world2cam(xyz_cur).cast<float>() * scale);
-    const float u_cur = uv_cur_pyr[0];
-    const float v_cur = uv_cur_pyr[1];
-    const int u_cur_i = floorf(u_cur);
-    const int v_cur_i = floorf(v_cur);
-
-    // check if projection is within the image
-    if(u_cur_i < 0 || v_cur_i < 0 || u_cur_i-border < 0 || v_cur_i-border < 0 || u_cur_i+border >= cur_img.cols || v_cur_i+border >= cur_img.rows)
-      continue;
-
-    // compute bilateral interpolation weights for the current image
-    const float subpix_u_cur = u_cur-u_cur_i;
-    const float subpix_v_cur = v_cur-v_cur_i;
-    const float w_cur_tl = (1.0-subpix_u_cur) * (1.0-subpix_v_cur);
-    const float w_cur_tr = subpix_u_cur * (1.0-subpix_v_cur);
-    const float w_cur_bl = (1.0-subpix_u_cur) * subpix_v_cur;
-    const float w_cur_br = subpix_u_cur * subpix_v_cur;
-    float* ref_patch_cache_ptr = reinterpret_cast<float*>(ref_patch_cache_.data) + patch_area_*feature_counter;
-    size_t pixel_counter = 0; // is used to compute the index of the cached jacobian
-    for(int y=0; y<patch_size_; ++y)
-    {
-      uint8_t* cur_img_ptr = (uint8_t*) cur_img.data + (v_cur_i+y-patch_halfsize_)*stride + (u_cur_i-patch_halfsize_);
-
-      for(int x=0; x<patch_size_; ++x, ++pixel_counter, ++cur_img_ptr, ++ref_patch_cache_ptr)
-      {
-        // compute residual
-        const float intensity_cur = w_cur_tl*cur_img_ptr[0] + w_cur_tr*cur_img_ptr[1] + w_cur_bl*cur_img_ptr[stride] + w_cur_br*cur_img_ptr[stride+1];
-        const float res = intensity_cur - (*ref_patch_cache_ptr);
-
-        // used to compute scale for robust cost
-        if(compute_weight_scale)
-          errors.push_back(fabsf(res));
-
-        // robustification
-        float weight = 1.0;
-        if(use_weights_) {
-          weight = weight_function_->value(res/scale_);
-        }
-
-        chi2 += res*res*weight;
-        n_meas_++;
-
-        if(linearize_system)
-        {
-          // compute Jacobian, weighted Hessian and weighted "steepest descend images" (times error)
-          const Vector6d J(jacobian_cache_.col(feature_counter*patch_area_ + pixel_counter));
-          H_.noalias() += J*J.transpose()*weight;
-          Jres_.noalias() -= J*res*weight;
-          if(display_)
-            resimg_.at<float>((int) v_cur+y-patch_halfsize_, (int) u_cur+x-patch_halfsize_) = res/255.0;
-        }
-      }
-    }
-  }
-
-  // compute the weights on the first iteration
-  if(compute_weight_scale && iter_ == 0)
-    scale_ = scale_estimator_->compute(errors);
-
-  return chi2/n_meas_;
-}
-
-int SparseImgAlign::solve()
-{
-  x_ = H_.ldlt().solve(Jres_);
-  if((bool) std::isnan((double) x_[0]))
-    return 0;
-  return 1;
-}
-
-void SparseImgAlign::update(
-    const ModelType& T_curold_from_ref,
-    ModelType& T_curnew_from_ref)
-{
-  T_curnew_from_ref =  T_curold_from_ref * SE3::exp(-x_);
-}
-
-void SparseImgAlign::startIteration()
-{}
-
-void SparseImgAlign::finishIteration()
-{
-  if(display_)
-  {
-    cv::namedWindow("residuals", CV_WINDOW_AUTOSIZE);
-    cv::imshow("residuals", resimg_*10);
-    cv::waitKey(0);
-  }
-}
-
-} // namespace svo
-
diff --git a/CPU_version/svo/test/README.md b/CPU_version/svo/test/README.md
deleted file mode 100644
index c70f832..0000000
--- a/CPU_version/svo/test/README.md
+++ /dev/null
@@ -1,24 +0,0 @@
-#### Download Test Data
-
-Create a folder where you will store all datasets, e.g.:
-
-    mkdir Datasets
-
-In your `.bashrc` script, create a new environment variable pointing to the dataset folder:
-
-    export SVO_DATASET_DIR=${HOME}/Datasets
-
-Source your new `.bashrc` script, go to the new dataset folder and download the test data:
-
-    source ~/.bashrc
-    cd ${SVO_DATASET_DIR}
-    wget http://rpg.ifi.uzh.ch/datasets/sin2_tex2_h1_v8_d.tar.gz -O - | tar -xz
-
-You can then run the tests, e.g.:
-
-    rosrun svo test_pipeline
-
-or if you are not using ROS:
-
-    cd svo/bin
-    ./test_pipeline
diff --git a/CPU_version/svo/test/benchmark.csv b/CPU_version/svo/test/benchmark.csv
deleted file mode 100644
index a3831e4..0000000
--- a/CPU_version/svo/test/benchmark.csv
+++ /dev/null
@@ -1,307 +0,0 @@
-local_ba,point_optimizer,pose_optimizer,pyramid_creation,reproject,sparse_img_align,tot_time,dropout,img_align_n_tracked,loba_err_fin,loba_err_init,loba_n_erredges_fin,loba_n_erredges_init,n_candidates,repr_n_mps,repr_n_new_references,sfba_error_final,sfba_error_init,sfba_n_edges_final,sfba_thresh
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\ No newline at end of file
diff --git a/CPU_version/svo/test/data/.gitignore b/CPU_version/svo/test/data/.gitignore
deleted file mode 100644
index cf57c3b..0000000
--- a/CPU_version/svo/test/data/.gitignore
+++ /dev/null
@@ -1,2 +0,0 @@
-.gitignore
-!.gitignore
\ No newline at end of file
diff --git a/CPU_version/svo/test/results/.gitignore b/CPU_version/svo/test/results/.gitignore
deleted file mode 100644
index cf57c3b..0000000
--- a/CPU_version/svo/test/results/.gitignore
+++ /dev/null
@@ -1,2 +0,0 @@
-.gitignore
-!.gitignore
\ No newline at end of file
diff --git a/CPU_version/svo/test/test_depth_filter.cpp b/CPU_version/svo/test/test_depth_filter.cpp
deleted file mode 100644
index 4d22493..0000000
--- a/CPU_version/svo/test/test_depth_filter.cpp
+++ /dev/null
@@ -1,206 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#include <list>
-#include <vector>
-#include <string>
-#include <boost/bind.hpp>
-#include <boost/make_shared.hpp>
-#include <boost/shared_ptr.hpp>
-#include <vikit/pinhole_camera.h>
-#include <vikit/abstract_camera.h>
-#include <vikit/atan_camera.h>
-#include <vikit/math_utils.h>
-#include <vikit/file_reader.h>
-#include <vikit/blender_utils.h>
-#include <vikit/timer.h>
-#include <iostream>
-#include <svo/feature_detection.h>
-#include <svo/depth_filter.h>
-#include <svo/frame.h>
-#include <svo/feature.h>
-#include <svo/point.h>
-#include <svo/config.h>
-#include "test_utils.h"
-
-namespace {
-
-struct ConvergedSeed {
-  int x_, y_;
-  double depth_, error_;
-  ConvergedSeed(int x, int y, double depth, double error) :
-    x_(x), y_(y), depth_(depth), error_(error)
-  {}
-};
-
-/// DepthFilter Test-Fixture
-class DepthFilterTest {
- public:
-  DepthFilterTest();
-  virtual ~DepthFilterTest();
-  void depthFilterCb(svo::Point* point, double depth_sigma2);
-  void testReconstruction(std::string dataset_dir, std::string experiment_name);
-
-  std::list<ConvergedSeed> results_;
-  std::vector<double> errors_;
-  size_t n_converged_seeds_;
-  vk::PinholeCamera* cam_;
-  svo::DepthFilter* depth_filter_;
-  svo::FramePtr frame_ref_;
-  svo::FramePtr frame_cur_;
-  cv::Mat depth_ref_;
-};
-
-DepthFilterTest::DepthFilterTest() :
-    n_converged_seeds_(0),
-    cam_(new vk::PinholeCamera(752, 480, 315.5, 315.5, 376.0, 240.0)),
-    depth_filter_(NULL)
-{
-  errors_.reserve(1000);
-}
-
-DepthFilterTest::~DepthFilterTest()
-{
-  delete cam_;
-}
-
-void DepthFilterTest::depthFilterCb(svo::Point* point, double depth_sigma2)
-{
-  double depth = (frame_ref_->pos() - point->pos_).norm();
-  double error = fabs(depth - depth_ref_.at<float>(point->obs_.front()->px[1],
-                                                   point->obs_.front()->px[0]));
-  results_.push_back(ConvergedSeed(
-      point->obs_.front()->px[0], point->obs_.front()->px[1], depth, error));
-  errors_.push_back(error);
-  delete point->obs_.front();
-  delete point;
-  ++n_converged_seeds_;
-}
-
-void DepthFilterTest::testReconstruction(
-    std::string dataset_dir,
-    std::string experiment_name)
-{
-  vk::FileReader<vk::blender_utils::file_format::ImageNameAndPose> sequence_file_reader(dataset_dir+"/trajectory.txt");
-  std::vector<vk::blender_utils::file_format::ImageNameAndPose> sequence;
-  sequence_file_reader.skipComments();
-  if(!sequence_file_reader.next())
-    std::runtime_error("Failed to open sequence file");
-  sequence_file_reader.readAllEntries(sequence);
-  std::cout << "RUN EXPERIMENT: read " << sequence.size() << " dataset entries." << std::endl;
-  std::vector<vk::blender_utils::file_format::ImageNameAndPose>::iterator it = sequence.begin();
-  vk::Timer t;
-  std::list<size_t> n_converged_per_iteration;
-
-  svo::feature_detection::DetectorPtr feature_detector(
-      new svo::feature_detection::FastDetector(
-          cam_->width(), cam_->height(), svo::Config::gridSize(), svo::Config::nPyrLevels()));
-  svo::DepthFilter::callback_t depth_filter_cb = boost::bind(&DepthFilterTest::depthFilterCb, this, _1, _2);
-  depth_filter_ = new svo::DepthFilter(feature_detector, depth_filter_cb);
-  depth_filter_->options_.verbose = true;
-
-  for(int i=0; it != sequence.end() && i<20; ++it, ++i)
-  {
-    std::string img_name(dataset_dir+"/img/" + (*it).image_name_ + "_0.png");
-    printf("reading image: '%s'\n", img_name.c_str());
-    cv::Mat img(cv::imread(img_name, 0));
-    assert(!img.empty());
-
-    Sophus::SE3 T_w_f(it->q_, it->t_);
-    if(i == 0)
-    {
-      // create reference frame and load ground truth depthmap
-      frame_ref_ = boost::make_shared<svo::Frame>(cam_, img, 0.0);
-      frame_ref_->T_f_w_ = T_w_f.inverse();
-      depth_filter_->addKeyframe(frame_ref_, 2, 0.5);
-      vk::blender_utils::loadBlenderDepthmap(dataset_dir+"/depth/" + (*it).image_name_ + "_0.depth", *cam_, depth_ref_);
-      continue;
-    }
-
-    n_converged_seeds_ = 0;
-    frame_cur_ = boost::make_shared<svo::Frame>(cam_, img, 0.0);
-    frame_cur_->T_f_w_ = T_w_f.inverse();
-    depth_filter_->addFrame(frame_cur_);
-    n_converged_per_iteration.push_back(n_converged_seeds_);
-  }
-  printf("Experiment '%s' took %f ms\n", experiment_name.c_str(), t.stop()*1000);
-
-  // compute mean, median and variance of error in converged area
-  {
-    printf("# converged:  \t %zu (ref: 287)\n", errors_.size());
-    double sum_error = 0;
-    std::for_each(errors_.begin(), errors_.end(), [&](double& e){sum_error+=e;});
-    printf("mean error:   \t %f cm (ref: 0.080357)\n", sum_error*100/errors_.size());
-    std::vector<double>::iterator it = errors_.begin()+0.5*errors_.size();
-    std::nth_element(errors_.begin(), it, errors_.end());
-    printf("50-percentile: \t %f cm (ref: 0.062042)\n", *it*100);
-    it = errors_.begin()+0.8*errors_.size();
-    std::nth_element(errors_.begin(), it, errors_.end());
-    printf("80-percentile: \t %f cm (ref: 0.124526)\n", *it*100);
-    it = errors_.begin()+0.95*errors_.size();
-    std::nth_element(errors_.begin(), it, errors_.end());
-    printf("95-percentile: \t %f cm (ref: 0.200417)\n", *it*100);
-  }
-
-  // trace error
-  std::string trace_dir(svo::test_utils::getTraceDir());
-  std::string trace_name(trace_dir + "/depth_filter_" + experiment_name + ".txt");
-  std::ofstream ofs(trace_name.c_str());
-  for(std::list<ConvergedSeed>::iterator i=results_.begin(); i!=results_.end(); ++i)
-    ofs << i->x_ << ", " << i->y_ << ", " << fabs(i->error_) << std::endl;
-  ofs.close();
-  
-  // trace convergence rate
-  trace_name = trace_dir + "/depth_filter_" + experiment_name + "_convergence.txt";
-  ofs.open(trace_name.c_str());
-  for(std::list<size_t>::iterator it=n_converged_per_iteration.begin();
-      it!=n_converged_per_iteration.end(); ++it)
-    ofs << *it << std::endl;
-  ofs.close();
-
-  // write ply file for pointcloud visualization in Meshlab
-  trace_name = trace_dir + "/depth_filter_" + experiment_name + ".ply";
-  ofs.open(trace_name.c_str());
-  ofs << "ply" << std::endl
-      << "format ascii 1.0" << std::endl
-	  << "element vertex " << results_.size() << std::endl
-	  << "property float x" << std::endl
-	  << "property float y" << std::endl
-	  << "property float z" << std::endl
-	  << "property uchar blue" << std::endl
-	  << "property uchar green" << std::endl
-	  << "property uchar red" << std::endl
-	  << "end_header" << std::endl;
-
-  for(std::list<ConvergedSeed>::iterator i=results_.begin(); i!=results_.end(); ++i)
-  {
-	cv::Vec3b c = frame_ref_->img_pyr_[0].at<cv::Vec3b>(i->y_, i->x_);
-	Eigen::Vector3d p = cam_->cam2world(i->x_, i->y_)*i->depth_;
-	ofs << p[0] << " " << p[1] << " " << p[2] << " "
-	    << (int) c[0] << " " << (int) c[1] << " " << (int) c[2] << std::endl;
-  }
-}
-
-}  // namespace
-
-int main(int argc, char** argv)
-{
-  DepthFilterTest test;
-  std::string dataset_dir(svo::test_utils::getDatasetDir() + "/sin2_tex2_h1_v8_d");
-  std::string experiment_name("sin2_tex2_h1_v8_d");
-  test.testReconstruction(dataset_dir, experiment_name);
-  return 0;
-}
diff --git a/CPU_version/svo/test/test_feature_alignment.cpp b/CPU_version/svo/test/test_feature_alignment.cpp
deleted file mode 100644
index dac8911..0000000
--- a/CPU_version/svo/test/test_feature_alignment.cpp
+++ /dev/null
@@ -1,124 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#include <string.h>
-#include <svo/global.h>
-#include <svo/feature_alignment.h>
-#include <vikit/timer.h>
-#include <vikit/aligned_mem.h>
-#include "test_utils.h"
-#if __ARM_NEON__
-#include <arm_neon.h>
-#endif
-
-using namespace Eigen;
-
-void generateRefPatchNoWarpInterpolate(const cv::Mat& img, const Vector2d& px,
-                                       cv::Mat& ref_patch_with_border)
-{
-  // compute interpolation weights
-  const int u_r = floor(px[0]);
-  const int v_r = floor(px[1]);
-  const float subpix_u = px[0]-u_r;
-  const float subpix_v = px[1]-v_r;
-  const float wTL = (1.0-subpix_u)*(1.0-subpix_v);
-  const float wTR = subpix_u * (1.0-subpix_v);
-  const float wBL = (1.0-subpix_u)*subpix_v;
-  const float wBR = subpix_u * subpix_v;
-
-  // loop through search_patch, interpolate
-  ref_patch_with_border = cv::Mat(10, 10, CV_8UC1);
-  uint8_t* patch_ptr = ref_patch_with_border.data;
-  const int stride = img.step.p[0];
-  for(int y=0; y<10; ++y)
-  {
-    uint8_t* img_ptr = (uint8_t*) img.data  + (v_r+y-4-1)*stride + u_r-4-1;
-    for(int x=0; x<10; ++x, ++patch_ptr, ++img_ptr)
-      *patch_ptr = wTL*img_ptr[0] + wTR*img_ptr[1] + wBL*img_ptr[stride] + wBR*img_ptr[stride+1];
-  }
-}
-
-int main(int argc, char **argv)
-{
-
-  std::string img_name(svo::test_utils::getDatasetDir() + "/sin2_tex2_h1_v8_d/img/frame_000002_0.png");
-  printf("Loading image '%s'\n", img_name.c_str());
-  cv::Mat img(cv::imread(img_name, 0));
-  assert(img.type() == CV_8UC1);
-
-  // TODO: test on corner/gradient features!
-  Vector2d px_true(130.2,120.3);
-
-  // create reference patch with border
-  cv::Mat ref_patch_with_border;
-  generateRefPatchNoWarpInterpolate(img, px_true, ref_patch_with_border);
-
-  // create reference patch, aligned
-  uint8_t* ref_patch = vk::aligned_mem::aligned_alloc<uint8_t>(64, 16);
-  uint8_t* ref_patch_ptr = ref_patch;
-  for(int y=1; y<9; ++y)
-  {
-    uint8_t* ref_patch_border_ptr = ref_patch_with_border.data + y*10 + 1;
-    for(int x=0; x<8; ++x, ++ref_patch_border_ptr, ++ref_patch_ptr)
-      *ref_patch_ptr = *ref_patch_border_ptr;
-  }
-
-  Vector2d px_est, px_error(-1.1, -0.8);
-  double h_inv;
-  vk::Timer t;
-  for(int i=0; i<1000; ++i)
-  {
-    px_est = px_true-px_error;
-    Vector2f dir = px_error.normalized().cast<float>();
-    svo::feature_alignment::align1D(img, dir, ref_patch_with_border.data, ref_patch, 3, px_est, h_inv);
-  }
-  Vector2d e = px_est-px_true;
-  printf("1000Xalign 1D took %fms, error = %fpx \t (ref i7-W520: 1.982000ms, 0.000033px) \n", t.stop()*1000, e.norm());
-
-  t.start();
-  for(int i=0; i<1000; ++i)
-  {
-    px_est = px_true-px_error;
-    svo::feature_alignment::align2D(img, ref_patch_with_border.data, ref_patch, 3, px_est, true);
-  }
-  e = px_est-px_true;
-  printf("1000Xalign 2D took %fms, error = %fpx \t (ref i7-W520: 2.306000ms, 0.015102px)\n", t.stop()*1000, e.norm());
-
-#ifdef __SSE2__
-  // Note, this KLT implementation is not invariant to illuminatino changes!
-  t.start();
-  for(int i=0; i<1000; ++i)
-  {
-    px_est = px_true-px_error;
-    svo::feature_alignment::align2D_SSE2(img, ref_patch_with_border.data, ref_patch, 3, px_est);
-  }
-  e = px_est-px_true;
-  printf("1000Xalign 2D SSE2 %fms, error = %fpx \t (ref i7-W520: 0.460000ms, 0.021881px)\n", t.stop()*1000, e.norm());
-#endif
-
-#ifdef __ARM_NEON__
-  t.start();
-  for(int i=0; i<1000; ++i)
-  {
-    px_est = px_true-px_error;
-    svo::feature_alignment::align2D_NEON(img, ref_patch_with_border.data, ref_patch, 3, px_est);
-  }
-  e = px_est-px_true;
-  printf("1000Xalign 2D NEON %fms, error = %fpx \t (ref Odroid-U2: ?, ?)\n", t.stop()*1000, e.norm());
-#endif
- 
-  return 0;
-}
diff --git a/CPU_version/svo/test/test_feature_detection.cpp b/CPU_version/svo/test/test_feature_detection.cpp
deleted file mode 100644
index 3ba2b2f..0000000
--- a/CPU_version/svo/test/test_feature_detection.cpp
+++ /dev/null
@@ -1,74 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#include <string.h>
-#include <svo/global.h>
-#include <svo/config.h>
-#include <svo/frame.h>
-#include <svo/feature_detection.h>
-#include <svo/depth_filter.h>
-#include <svo/feature.h>
-#include <vikit/timer.h>
-#include <vikit/vision.h>
-#include <vikit/abstract_camera.h>
-#include <vikit/atan_camera.h>
-#include "test_utils.h"
-
-namespace {
-
-using namespace Eigen;
-using namespace std;
-
-void testCornerDetector()
-{
-  std::string img_name(svo::test_utils::getDatasetDir() + "/sin2_tex2_h1_v8_d/img/frame_000002_0.png");
-  printf("Loading image '%s'\n", img_name.c_str());
-  cv::Mat img(cv::imread(img_name, 0));
-  assert(img.type() == CV_8UC1 && !img.empty());
-
-  vk::AbstractCamera* cam = new vk::ATANCamera(752, 480, 0.511496, 0.802603, 0.530199, 0.496011, 0.934092);
-  svo::FramePtr frame(new svo::Frame(cam, img, 0.0));
-
-  // Corner detection
-  vk::Timer t;
-  svo::Features fts;
-  svo::feature_detection::FastDetector fast_detector(
-      img.cols, img.rows, svo::Config::gridSize(), svo::Config::nPyrLevels());
-  for(int i=0; i<100; ++i)
-  {
-    fast_detector.detect(frame.get(), frame->img_pyr_, svo::Config::triangMinCornerScore(), fts);
-  }
-  printf("Fast corner detection took %f ms, %zu corners detected (ref i7-W520: 7.166360ms, 40000)\n", t.stop()*10, fts.size());
-  printf("Note, in this case, feature detection also contains the cam2world projection of the feature.\n");
-  cv::Mat img_rgb = cv::Mat(img.size(), CV_8UC3);
-  cv::cvtColor(img, img_rgb, CV_GRAY2RGB);
-  std::for_each(fts.begin(), fts.end(), [&](svo::Feature* i){
-    cv::circle(img_rgb, cv::Point2f(i->px[0], i->px[1]), 4*(i->level+1), cv::Scalar(0,255,0), 1);
-  });
-  cv::imshow("ref_img", img_rgb);
-  cv::waitKey(0);
-
-  std::for_each(fts.begin(), fts.end(), [&](svo::Feature* i){ delete i; });
-}
-
-} // namespace
-
-
-int main(int argc, char **argv)
-{
-  testCornerDetector();
-  return 0;
-}
diff --git a/CPU_version/svo/test/test_matcher.cpp b/CPU_version/svo/test/test_matcher.cpp
deleted file mode 100644
index 0b65cb9..0000000
--- a/CPU_version/svo/test/test_matcher.cpp
+++ /dev/null
@@ -1,200 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#include <algorithm>
-#include <vikit/pinhole_camera.h>
-#include <vikit/math_utils.h>
-#include <vikit/blender_utils.h>
-#include <svo/matcher.h>
-#include <svo/frame.h>
-#include <svo/config.h>
-#include <svo/feature.h>
-#include "test_utils.h"
-
-namespace {
-
-/// Matcher Test-Fixture
-class MatcherTest {
- public:
-  MatcherTest()
-  {
-    cam_ = new vk::PinholeCamera(752, 480, 315.5, 315.5, 376.0, 240.0);
-
-    // load images
-    std::string dataset_dir(svo::test_utils::getDatasetDir() + "/sin2_tex2_h1_v8_d");
-    std::string img_name(dataset_dir+"/img/frame_000002_0.png");
-    printf("Loading image '%s'\n", img_name.c_str());
-    cv::Mat img_ref(cv::imread(img_name, 0));
-    img_name = std::string(dataset_dir+"/img/frame_000006_0.png");
-    printf("Loading image '%s'\n", img_name.c_str());
-    cv::Mat img_cur(cv::imread(img_name, 0));
-    assert(!img_ref.empty() && !img_cur.empty());
-
-    // create frame
-    frame_ref_ = new svo::Frame(cam_, img_ref, 1.0);
-    frame_cur_ = new svo::Frame(cam_, img_cur, 2.0);
-    ref_ftr_ = new svo::Feature(frame_ref_, Eigen::Vector2d(300, 260), 0);
-
-    // set poses
-    Eigen::Vector3d t_w_ref(0.1131, 0.1131, 2.0000);
-    Eigen::Vector3d t_w_cur(0.5673, 0.5641, 2.0000);
-    Eigen::Quaterniond q_w_ref(0.0, 0.8227, 0.2149, 0.0);
-    Eigen::Quaterniond q_w_cur(0.0, 0.8235, 0.2130, 0.0);
-    frame_ref_->T_f_w_ = Sophus::SE3(q_w_ref, t_w_ref).inverse();
-    frame_cur_->T_f_w_ = Sophus::SE3(q_w_cur, t_w_cur).inverse();
-
-    // load ground-truth depth
-    vk::blender_utils::loadBlenderDepthmap(dataset_dir+"/depth/frame_000002_0.depth", *cam_, depth_ref_);
-  }
-
-  virtual ~MatcherTest()
-  {
-    delete cam_;
-    delete frame_ref_;
-    delete frame_cur_;
-    delete ref_ftr_;
-  }
-
-  // Individual tests
-  void testEpipolarSearchFullImg();
-  void testWarpAffine();
-
-  // Objects declared here can be used by all tests
-  vk::PinholeCamera* cam_;
-  svo::Frame* frame_ref_;
-  svo::Frame* frame_cur_;
-  svo::Feature* ref_ftr_;
-  cv::Mat depth_ref_;
-};
-
-void MatcherTest::testEpipolarSearchFullImg()
-{
-  svo::Matcher matcher;
-  cv::Mat depthmap(frame_ref_->cam_->height(), frame_ref_->cam_->width(), CV_32FC1, cv::Scalar(0));
-  cv::Mat error_map(depthmap.rows, depthmap.cols, CV_32FC1, cv::Scalar(0));
-  cv::Mat mask(depthmap.rows, depthmap.cols, CV_8UC1, cv::Scalar(1));
-  double depth_range = 0.8;
-  size_t n_converged = 0;
-  double sum_error = 0;
-  std::vector<double> errors; errors.reserve(depthmap.cols*depthmap.rows);
-  for(int y=4; y<depthmap.rows-4; ++y)
-  {
-    for(int x=4; x<depthmap.cols-4; ++x)
-    {
-      svo::Feature ftr(frame_ref_, Eigen::Vector2d(x,y), 0);
-      double depth_gt = depth_ref_.at<float>(y, x);
-      double depth_estimate;
-      int res = matcher.findEpipolarMatchDirect(
-          *frame_ref_, *frame_cur_, ftr, depth_gt, fmax(depth_gt-depth_range,0.0),
-          depth_gt+depth_range, depth_estimate);
-      if(res)
-      {
-        depthmap.at<float>(y,x) = depth_estimate;
-        error_map.at<float>(y,x) = fabsf(depth_estimate-depth_gt);
-        ++n_converged;
-        sum_error += error_map.at<float>(y,x);
-        errors.push_back(error_map.at<float>(y,x));
-      }
-      else
-        mask.at<uint8_t>(y,x) = 0;
-    }
-  }
-
-  // compute mean, median and variance of error in converged area
-  printf("n converged:  \t %zu mm (ref: 216114)\n", n_converged);
-  printf("mean error:   \t %f mm (ref: 0.410084)\n", sum_error*100/n_converged);
-  std::vector<double>::iterator it = errors.begin()+0.5*errors.size();
-  std::nth_element(errors.begin(), it, errors.end());
-  printf("50-percentile: \t %f mm (ref: 0.083203)\n", *it*100);
-  it = errors.begin()+0.8*errors.size();
-  std::nth_element(errors.begin(), it, errors.end());
-  printf("80-percentile: \t %f mm (ref: 0.161824)\n", *it*100);
-  it = errors.begin()+0.95*errors.size();
-  std::nth_element(errors.begin(), it, errors.end());
-  printf("95-percentile: \t %f mm (ref: 0.263539)\n", *it*100);
-
-  // save results to file
-  std::ofstream output_stream;
-  std::string trace_dir(svo::test_utils::getTraceDir());
-  std::string output_filename(trace_dir + "/depthmap.bin");
-  output_stream.open(output_filename.c_str(), std::ios::out | std::ios::binary | std::ios::trunc);
-  output_stream.write((const char *)depthmap.data, depthmap.rows*depthmap.cols*sizeof(float));
-  output_stream.close();
-
-  output_filename.assign(trace_dir + "/depthmap_error.bin");
-  output_stream.open(output_filename.c_str(), std::ios::out | std::ios::binary | std::ios::trunc);
-  output_stream.write((const char *)error_map.data, error_map.rows*error_map.cols*sizeof(float));
-  output_stream.close();
-
-  output_filename.assign(trace_dir + "/depthmap_mask.bin");
-  output_stream.open(output_filename.c_str(), std::ios::out | std::ios::binary | std::ios::trunc);
-  output_stream.write((const char *)mask.data, mask.rows*mask.cols*sizeof(uint8_t));
-  output_stream.close();
-}
-
-void MatcherTest::testWarpAffine()
-{
-  const int halfpatch_size = 15;
-  const int patch_size=halfpatch_size*2;
-  svo::Matcher matcher;
-  double depth = 1.0;
-
-  Sophus::SE3 T_cur_ref(frame_cur_->T_f_w_*frame_ref_->T_f_w_.inverse());
-  Eigen::Vector2d px_cur(frame_cur_->cam_->world2cam(T_cur_ref*(ref_ftr_->f*depth)));
-
-  // compute reference patch
-  cv::Mat ref_patch(matcher.halfpatch_size_+1, matcher.halfpatch_size_+1,
-                    CV_8U, matcher.patch_with_border_);
-
-  Eigen::Matrix2d A_cur_ref;
-  svo::warp::getWarpMatrixAffine(
-      *cam_, *cam_, ref_ftr_->px, ref_ftr_->f, 1.0, T_cur_ref, ref_ftr_->level, A_cur_ref);
-  int level_cur = svo::warp::getBestSearchLevel(A_cur_ref, svo::Config::nPyrLevels()-1);
-  svo::warp::warpAffine(
-      A_cur_ref, ref_ftr_->frame->img_pyr_[ref_ftr_->level], ref_ftr_->px,
-      ref_ftr_->level, level_cur, matcher.halfpatch_size_+1, matcher.patch_with_border_);
-
-  // copy current patch
-  Eigen::Vector2i pxi(px_cur[0]/(1<<level_cur)+0.5, px_cur[1]/(1<<level_cur)+0.5);
-  cv::Mat cur_patch(patch_size, patch_size, CV_8U);
-  frame_cur_->img_pyr_.at(level_cur)(cv::Range(pxi[1]-halfpatch_size,
-                                               pxi[1]+halfpatch_size),
-                                     cv::Range(pxi[0]-halfpatch_size,
-                                               pxi[0]+halfpatch_size)).copyTo(cur_patch);
-
-  // display results
-  cv::circle(frame_cur_->img_pyr_[level_cur],
-             cv::Point2f(pxi[0], pxi[1]),
-             patch_size, cv::Scalar(255), 2);
-  cv::circle(frame_ref_->img_pyr_[ref_ftr_->level],
-              cv::Point2f(ref_ftr_->px[0]/(1<<ref_ftr_->level), ref_ftr_->px[1]/(1<<ref_ftr_->level)),
-              patch_size, cv::Scalar(255), 2);
-  cv::imshow("cur_patch", cur_patch);
-  cv::imshow("ref_patch", ref_patch);
-  cv::imshow("ref_img", frame_ref_->img_pyr_[ref_ftr_->level]);
-  cv::imshow("cur_img", frame_cur_->img_pyr_[level_cur]);
-  cv::waitKey(0);
-}
-
-}  // namespace
-
-int main(int argc, char** argv)
-{
-  MatcherTest test;
-  test.testEpipolarSearchFullImg();
-//  test.testWarpAffine();
-  return 0;
-}
diff --git a/CPU_version/svo/test/test_pipeline.cpp b/CPU_version/svo/test/test_pipeline.cpp
deleted file mode 100644
index ede3b25..0000000
--- a/CPU_version/svo/test/test_pipeline.cpp
+++ /dev/null
@@ -1,98 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#include <svo/config.h>
-#include <svo/frame_handler_mono.h>
-#include <svo/map.h>
-#include <svo/frame.h>
-#include <vector>
-#include <string>
-#include <vikit/math_utils.h>
-#include <vikit/vision.h>
-#include <vikit/abstract_camera.h>
-#include <vikit/atan_camera.h>
-#include <vikit/pinhole_camera.h>
-#include <opencv2/opencv.hpp>
-#include <sophus/se3.h>
-#include <iostream>
-#include "test_utils.h"
-
-namespace svo {
-
-class BenchmarkNode
-{
-  vk::AbstractCamera* cam_;
-  svo::FrameHandlerMono* vo_;
-
-public:
-  BenchmarkNode();
-  ~BenchmarkNode();
-  void runFromFolder();
-};
-
-BenchmarkNode::BenchmarkNode()
-{
-  cam_ = new vk::PinholeCamera(752, 480, 315.5, 315.5, 376.0, 240.0);
-  vo_ = new svo::FrameHandlerMono(cam_);
-  vo_->start();
-}
-
-BenchmarkNode::~BenchmarkNode()
-{
-  delete vo_;
-  delete cam_;
-}
-
-void BenchmarkNode::runFromFolder()
-{
-  for(int img_id = 2; img_id < 188; ++img_id)
-  {
-    // load image
-    std::stringstream ss;
-    ss << svo::test_utils::getDatasetDir() << "/sin2_tex2_h1_v8_d/img/frame_"
-       << std::setw( 6 ) << std::setfill( '0' ) << img_id << "_0.png";
-    if(img_id == 2)
-      std::cout << "reading image " << ss.str() << std::endl;
-    cv::Mat img(cv::imread(ss.str().c_str(), 0));
-    assert(!img.empty());
-
-    // process frame
-    vo_->addImage(img, 0.01*img_id);
-
-    // display tracking quality
-    if(vo_->lastFrame() != NULL)
-    {
-    	std::cout << "Frame-Id: " << vo_->lastFrame()->id_ << " \t"
-                  << "#Features: " << vo_->lastNumObservations() << " \t"
-                  << "Proc. Time: " << vo_->lastProcessingTime()*1000 << "ms \n";
-
-    	// access the pose of the camera via vo_->lastFrame()->T_f_w_.
-    }
-  }
-}
-
-} // namespace svo
-
-int main(int argc, char** argv)
-{
-  {
-    svo::BenchmarkNode benchmark;
-    benchmark.runFromFolder();
-  }
-  printf("BenchmarkNode finished.\n");
-  return 0;
-}
-
diff --git a/CPU_version/svo/test/test_pose_optimizer.cpp b/CPU_version/svo/test/test_pose_optimizer.cpp
deleted file mode 100644
index 59e0b46..0000000
--- a/CPU_version/svo/test/test_pose_optimizer.cpp
+++ /dev/null
@@ -1,110 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#include <algorithm>
-#include <vikit/pinhole_camera.h>
-#include <vikit/math_utils.h>
-#include <vikit/sample.h>
-#include <vikit/blender_utils.h>
-#include <svo/frame.h>
-#include <svo/point.h>
-#include <svo/feature.h>
-#include <svo/config.h>
-#include <svo/feature_detection.h>
-#include <svo/pose_optimizer.h>
-#include "test_utils.h"
-
-namespace {
-
-using namespace svo;
-using namespace Eigen;
-
-/// Pose Optimizer Test-Fixture
-class PoseOptimizerTest {
- public:
-  PoseOptimizerTest()
-  {
-    cam_ = new vk::PinholeCamera(752, 480, 315.5, 315.5, 376.0, 240.0);
-
-    // load image
-    std::string dataset_dir(svo::test_utils::getDatasetDir() + "/sin2_tex2_h1_v8_d");
-    std::string img_name(dataset_dir+"/img/frame_000002_0.png");
-    printf("Loading image '%s'\n", img_name.c_str());
-    cv::Mat img(cv::imread(img_name, 0));
-    assert(!img.empty());
-
-    // create frame
-    frame_.reset(new svo::Frame(cam_, img, 1.0));
-
-    // set pose
-    Eigen::Vector3d t_w_ref(0.1131, 0.1131, 2.0000);
-    Eigen::Quaterniond q_w_ref(0.0, 0.8227, 0.2149, 0.0);
-    frame_->T_f_w_ = Sophus::SE3(q_w_ref, t_w_ref).inverse();
-
-    // load ground-truth depth
-    vk::blender_utils::loadBlenderDepthmap(dataset_dir + "/depth/frame_000002_0.depth", *cam_, depthmap_);
-
-    // detect features
-    feature_detection::FastDetector detector(
-        cam_->width(), cam_->height(), Config::gridSize(), Config::nPyrLevels());
-    detector.detect(frame_.get(), frame_->img_pyr_, Config::triangMinCornerScore(), frame_->fts_);
-    size_t n_fts = 0;
-    std::for_each(frame_->fts_.begin(), frame_->fts_.end(), [&](Feature* i){
-      Point* point(new Point(frame_->f2w(i->f*depthmap_.at<float>(i->px[1], i->px[0])), i));
-      i->point = point;
-      ++n_fts;
-    });
-    printf("Added %zu features to frame.\n", n_fts);
-  }
-
-  virtual ~PoseOptimizerTest()
-  {
-    delete cam_;
-  }
-
-  // Individual tests
-  void test(const Vector3d& pose_disturbance, double pixel_sigma2);
-
-  // Objects declared here can be used by all tests
-  vk::PinholeCamera* cam_;
-  FramePtr frame_;
-  cv::Mat depthmap_;
-};
-
-void PoseOptimizerTest::test(const Vector3d& pose_disturbance, double pixel_sigma2)
-{
-  printf("Add %f px noise to each observation\n", pixel_sigma2);
-  for(Features::iterator it=frame_->fts_.begin(); it!=frame_->fts_.end(); ++it)
-  {
-    (*it)->px += Vector2d(vk::Sample::gaussian(pixel_sigma2), vk::Sample::gaussian(pixel_sigma2));
-    (*it)->f = frame_->c2f((*it)->px);
-  }
-  frame_->T_f_w_ = frame_->T_f_w_*SE3(Matrix3d::Identity(), pose_disturbance);
-  double estimated_scale, error_init, error_final;
-  size_t num_obs;
-  pose_optimizer::optimizeGaussNewton(
-      Config::reprojThresh(), 10, true, frame_,
-      estimated_scale, error_init, error_final, num_obs);
-}
-
-}  // namespace
-
-int main(int argc, char** argv)
-{
-  PoseOptimizerTest test;
-  test.test(Eigen::Vector3d(0.2, 0.2, 0.2), 1.0);
-  return 0;
-}
diff --git a/CPU_version/svo/test/test_sparse_img_align.cpp b/CPU_version/svo/test/test_sparse_img_align.cpp
deleted file mode 100644
index 1312da0..0000000
--- a/CPU_version/svo/test/test_sparse_img_align.cpp
+++ /dev/null
@@ -1,163 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#include <vikit/pinhole_camera.h>
-#include <vikit/math_utils.h>
-#include <vikit/file_reader.h>
-#include <vikit/timer.h>
-#include <vikit/blender_utils.h>
-#include <iostream>
-#include <svo/feature_detection.h>
-#include <svo/sparse_img_align.h>
-#include <svo/frame.h>
-#include <svo/point.h>
-#include <svo/feature.h>
-#include <svo/config.h>
-#include "test_utils.h"
-
-namespace {
-
-/// SparseImgAlign Test-Fixture
-class SparseImgAlignTest {
- public:
-
-  SparseImgAlignTest();
-  virtual ~SparseImgAlignTest();
-  void testSequence(
-      const std::string& dataset_dir,
-      const std::string& experiment_name,
-      svo::feature_detection::AbstractDetector* feature_detector);
-
-  vk::PinholeCamera* cam_;
-  svo::FramePtr frame_ref_;
-  svo::FramePtr frame_cur_;
-};
-
-SparseImgAlignTest::SparseImgAlignTest() :
-    cam_(new vk::PinholeCamera(752, 480, 315.5, 315.5, 376.0, 240.0))
-{}
-
-SparseImgAlignTest::~SparseImgAlignTest()
-{}
-
-void SparseImgAlignTest::testSequence(
-    const std::string& dataset_dir,
-    const std::string& experiment_name,
-    svo::feature_detection::AbstractDetector* feature_detector)
-{
-  vk::FileReader<vk::blender_utils::file_format::ImageNameAndPose> sequence_file_reader(dataset_dir+"/trajectory.txt");
-  std::vector<vk::blender_utils::file_format::ImageNameAndPose> sequence;
-  sequence_file_reader.skipComments();
-  if(!sequence_file_reader.next())
-    std::runtime_error("Failed to open sequence file");
-  sequence_file_reader.readAllEntries(sequence);
-  printf("RUN EXPERIMENT: read %zu dataset entries.\n", sequence.size());
-  std::vector<vk::blender_utils::file_format::ImageNameAndPose>::iterator iter = sequence.begin();
-  std::list<double> translation_error;
-
-  Sophus::SE3 T_prev_w, T_prevgt_w;
-  std::string trace_dir(svo::test_utils::getTraceDir());
-  std::string trace_name(trace_dir + "/sparse_img_align_" + experiment_name + "_trans_estimate.txt");
-  std::ofstream ofs(trace_name.c_str());
-  for(int i=0; iter != sequence.end() && i<30; ++iter, ++i)
-  {
-    // load img
-    // IMPORTANT: We need to flip the image because the Povray dataset has a
-    // negative focal length in y direction which we didn't set.
-    std::string img_name(dataset_dir+"/img/" + iter->image_name_ + "_0.png");
-    cv::Mat img(cv::imread(img_name, 0));
-    assert(!img.empty());
-
-    // load pose
-    Sophus::SE3 T_w_gt(iter->q_, iter->t_);
-    Sophus::SE3 T_gt_w = T_w_gt.inverse(); // ground-truth
-
-    if(i==0)
-    {
-      // set reference frame
-      frame_ref_.reset(new svo::Frame(cam_, img, 0.0));
-      frame_ref_->T_f_w_ = T_gt_w;
-
-      // load ground-truth depth
-      cv::Mat depthmap;
-      vk::blender_utils::loadBlenderDepthmap(
-          dataset_dir+"/depth/"+iter->image_name_+"_0.depth", *cam_, depthmap);
-
-      // extract features, generate features with 3D points
-      feature_detector->detect(
-          frame_ref_.get(), frame_ref_->img_pyr_, svo::Config::triangMinCornerScore(), frame_ref_->fts_);
-      std::for_each(frame_ref_->fts_.begin(), frame_ref_->fts_.end(), [&](svo::Feature* i) {
-        Eigen::Vector3d pt_pos_cur = i->f*depthmap.at<float>(i->px[1], i->px[0]);
-        Eigen::Vector3d pt_pos_w = frame_ref_->T_f_w_.inverse()*pt_pos_cur;
-        svo::Point* pt = new svo::Point(pt_pos_w, i);
-        i->point = pt;
-      });
-
-      printf("Added %zu 3d pts to the reference frame.\n", frame_ref_->nObs());
-      T_prev_w = frame_ref_->T_f_w_;
-      T_prevgt_w = T_gt_w;
-      continue;
-    }
-
-    frame_cur_.reset(new svo::Frame(cam_, img, 0.0));
-    //frame_cur_->T_f_w_ = frame_ref_->T_f_w_; // start at reference frame
-    frame_cur_->T_f_w_ = T_prev_w; // start at last frame
-
-    // run image align
-    vk::Timer t;
-    svo::SparseImgAlign img_align(svo::Config::kltMaxLevel(), svo::Config::kltMinLevel(),
-                                    30, svo::SparseImgAlign::GaussNewton, false, false);
-    img_align.run(frame_ref_, frame_cur_);
-
-    // compute error
-    Sophus::SE3 T_f_gt = frame_cur_->T_f_w_ * T_gt_w.inverse();
-    translation_error.push_back(T_f_gt.translation().norm());
-    printf("[%3.i] time = %f ms \t |t| = %f \t translation error = %f\n",
-           i, t.stop()*1000, (frame_ref_->T_f_w_*T_gt_w.inverse()).translation().norm(),
-           translation_error.back());
-
-    // save old pose for next iteration
-    T_prev_w = frame_cur_->T_f_w_;
-    T_prevgt_w = T_gt_w;
-
-    ofs << frame_cur_->T_f_w_.inverse().translation().transpose() << " "
-        << T_gt_w.inverse().translation().transpose() << std::endl;
-  }
-  ofs.close();
-
-  // trace error
-  trace_name = trace_dir + "/sparse_img_align_" + experiment_name + "_trans_error.txt";
-  ofs.open(trace_name.c_str());
-  for(std::list<double>::iterator it=translation_error.begin(); it!=translation_error.end(); ++it)
-    ofs << *it << std::endl;
-  ofs.close();
-}
-
-}  // namespace
-
-
-int main(int argc, char** argv)
-{
-  std::string experiment_name("flying_room_1_rig_1_fast_minlev0");
-  std::string dataset_dir(svo::test_utils::getDatasetDir() + "/sin2_tex2_h1_v8_d");
-  svo::Config::triangMinCornerScore() = 20;
-  svo::Config::kltMinLevel() = 0;
-  SparseImgAlignTest test;
-  svo::feature_detection::FastDetector detector(
-      test.cam_->width(), test.cam_->height(), svo::Config::gridSize(), svo::Config::nPyrLevels());
-  test.testSequence(dataset_dir, experiment_name, &detector);
-  return 0;
-}
diff --git a/CPU_version/svo/test/test_utils.h b/CPU_version/svo/test/test_utils.h
deleted file mode 100644
index 2759fe0..0000000
--- a/CPU_version/svo/test/test_utils.h
+++ /dev/null
@@ -1,57 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#ifndef TEST_UTILS_H_
-#define TEST_UTILS_H_
-
-#include <string.h>
-#include <cstdlib> // for getenv
-#ifdef SVO_USE_ROS
-# include <ros/package.h>
-# include <vikit/params_helper.h>
-#endif
-
-namespace svo {
-namespace test_utils {
-
-std::string getDatasetDir()
-{
-  const char* env_dir = std::getenv("SVO_DATASET_DIR");
-#ifdef SVO_USE_ROS
-  std::string dataset_dir(ros::package::getPath("svo")+"/test/data");
-  if(env_dir != NULL)
-    dataset_dir = std::string(env_dir);
-  return dataset_dir;
-#else
-  return std::string(env_dir);
-#endif
-}
-
-std::string getTraceDir()
-{
-#ifdef SVO_USE_ROS
-  std::string default_dir(ros::package::getPath("svo")+"/test/results");
-  return vk::getParam<std::string>("svo/trace_dir", default_dir);
-#else
-  return "/tmp";
-#endif
-}
-
-} // namespace test_utils
-} // namespace svo
-
-
-#endif // TEST_UTILS_H_
diff --git a/CPU_version/svo_analysis/.gitignore b/CPU_version/svo_analysis/.gitignore
deleted file mode 100644
index 7e99e36..0000000
--- a/CPU_version/svo_analysis/.gitignore
+++ /dev/null
@@ -1 +0,0 @@
-*.pyc
\ No newline at end of file
diff --git a/CPU_version/svo_analysis/CMakeLists.txt b/CPU_version/svo_analysis/CMakeLists.txt
deleted file mode 100644
index 53ea7dc..0000000
--- a/CPU_version/svo_analysis/CMakeLists.txt
+++ /dev/null
@@ -1,8 +0,0 @@
-cmake_minimum_required(VERSION 2.8.3)
-project(svo_analysis)
-
-find_package(catkin REQUIRED COMPONENTS rospy)
-include_directories(${catkin_INCLUDE_DIRS})
-
-catkin_python_setup()
-#catkin_package(CATKIN_DEPENDS sensor_msgs)
\ No newline at end of file
diff --git a/CPU_version/svo_analysis/README.md b/CPU_version/svo_analysis/README.md
deleted file mode 100644
index b3201b1..0000000
--- a/CPU_version/svo_analysis/README.md
+++ /dev/null
@@ -1,27 +0,0 @@
-## SVO Analysis
-
-#### Download Test Data
-
-Create a folder where you will store all datasets, e.g.:
-
-    mkdir Datasets
-
-In your `.bashrc` script, create a new environment variable pointing to the dataset folder:
-
-    export SVO_DATASET_DIR=${HOME}/Datasets
-
-Source your new `.bashrc` script, go to the new dataset folder and download the test data:
-
-    source ~/.bashrc
-    cd ${SVO_DATASET_DIR}
-    wget http://rpg.ifi.uzh.ch/datasets/sin2_tex2_h1_v8_d.tar.gz -O - | tar -xz
-
-#### Run Benchmark
-
-In the _CMakeLists.txt_ of SVO you need to set the `TRACE` flag to `TRUE` and recompile SVO.
-Afterwards run
-
-    rosrun svo_analysis benchmark.py sin2_tex2_h1_v8_d
-
-The script will create a new folder in `svo_analysis/results/`, run svo on the dataset and save the tracefile in this folder and at the end it will run some scripts to generate plots from the tracefile.
-  
diff --git a/CPU_version/svo_analysis/__init__.py b/CPU_version/svo_analysis/__init__.py
deleted file mode 100644
index e69de29..0000000
diff --git a/CPU_version/svo_analysis/comparisons/speed.yaml b/CPU_version/svo_analysis/comparisons/speed.yaml
deleted file mode 100644
index 2f706d4..0000000
--- a/CPU_version/svo_analysis/comparisons/speed.yaml
+++ /dev/null
@@ -1,14 +0,0 @@
-comparison_name: speed
-experiment_sets:
-- label: 'old'
-  experiments:
-  - 20140415_1028_svo_ros_synthetic_speed_1404150920_plane_straight_speed4
-  - 20140415_1028_svo_ros_synthetic_speed_1404150928_plane_straight_speed5
-  - 20140415_1028_svo_ros_synthetic_speed_1404150935_plane_straight_speed6
-  - 20140415_1028_svo_ros_synthetic_speed_1404150940_plane_straight_speed7
-- label: 'new'
-  experiments:
-  - 20140513_0949_svo_ros_synthetic_speed_1404150920_plane_straight_speed4
-  - 20140513_0949_svo_ros_synthetic_speed_1404150928_plane_straight_speed5
-  - 20140513_0949_svo_ros_synthetic_speed_1404150935_plane_straight_speed6
-  - 20140513_0949_svo_ros_synthetic_speed_1404150940_plane_straight_speed7
\ No newline at end of file
diff --git a/CPU_version/svo_analysis/comparisons/textures.yaml b/CPU_version/svo_analysis/comparisons/textures.yaml
deleted file mode 100644
index 7279f6e..0000000
--- a/CPU_version/svo_analysis/comparisons/textures.yaml
+++ /dev/null
@@ -1,22 +0,0 @@
-comparison_name: textures
-experiment_sets:
-- label: 'T1'
-  experiments:
-  - 20140516_1449_svo_ros_synthetic_all_str_tex1_h1_v6_d
-  - 20140516_1449_svo_ros_synthetic_all_str_tex1_h1_v9_d
-  - 20140516_1449_svo_ros_synthetic_all_str_tex1_h1_v12_d
-- label: 'T2'
-  experiments:
-  - 20140516_1449_svo_ros_synthetic_all_str_tex2_h1_v6_d
-  - 20140516_1449_svo_ros_synthetic_all_str_tex2_h1_v9_d
-  - 20140516_1449_svo_ros_synthetic_all_str_tex2_h1_v12_d
-- label: 'T3'
-  experiments:
-  - 20140516_1449_svo_ros_synthetic_all_str_tex3_h1_v6_d
-  - 20140516_1449_svo_ros_synthetic_all_str_tex3_h1_v9_d
-  - 20140516_1449_svo_ros_synthetic_all_str_tex3_h1_v12_d
-# - label: 'T4'
-#   experiments:
-#   - 20140516_1449_svo_ros_synthetic_all_str_tex4_h1_v6_d
-#   - 20140516_1449_svo_ros_synthetic_all_str_tex4_h1_v9_d
-#   - 20140516_1449_svo_ros_synthetic_all_str_tex4_h1_v12_d
\ No newline at end of file
diff --git a/CPU_version/svo_analysis/experiments/.gitignore b/CPU_version/svo_analysis/experiments/.gitignore
deleted file mode 100644
index 5b74354..0000000
--- a/CPU_version/svo_analysis/experiments/.gitignore
+++ /dev/null
@@ -1,2 +0,0 @@
-*.yaml
-!.gitignore
diff --git a/CPU_version/svo_analysis/package.xml b/CPU_version/svo_analysis/package.xml
deleted file mode 100644
index dcc5a62..0000000
--- a/CPU_version/svo_analysis/package.xml
+++ /dev/null
@@ -1,19 +0,0 @@
-<package>
-
-  <name>svo_analysis</name>
-  <version>0.0.1</version>
-  <description>
-    Python scripts to analyse performance of SVO.
-  </description>
-  <maintainer email="forster@ifi.uzh.ch">Christian Forster</maintainer>
-  <author>Christian Forster</author>
-  <license>BSD</license>
-  <buildtool_depend>catkin</buildtool_depend>
-
-  <build_depend>rospy</build_depend>
-
-  <run_depend>python-rospkg</run_depend>
-  <run_depend>python-yaml</run_depend>
-  <run_depend>rospy</run_depend>
-
-</package>
\ No newline at end of file
diff --git a/CPU_version/svo_analysis/results/.gitignore b/CPU_version/svo_analysis/results/.gitignore
deleted file mode 100644
index c1aefd2..0000000
--- a/CPU_version/svo_analysis/results/.gitignore
+++ /dev/null
@@ -1,2 +0,0 @@
-.gitignore
-!.gitignore
diff --git a/CPU_version/svo_analysis/scripts/__init__.py b/CPU_version/svo_analysis/scripts/__init__.py
deleted file mode 100644
index e69de29..0000000
diff --git a/CPU_version/svo_analysis/scripts/benchmark.py b/CPU_version/svo_analysis/scripts/benchmark.py
deleted file mode 100755
index a3733ea..0000000
--- a/CPU_version/svo_analysis/scripts/benchmark.py
+++ /dev/null
@@ -1,111 +0,0 @@
-#!/usr/bin/python
-"""
-Created on Sat Aug 10 18:21:47 2013
-
-@author: Christian Forster
-"""
-
-import os
-import yaml
-import rospkg
-import argparse
-import time
-import vikit_py.cpu_info as cpu_info
-import vikit_py.ros_node as ros_node
-import evaluate
-import shutil
-
-def run_experiment(dataset, params):
-    # load dataset parameters
-    params['dataset_directory'] = os.path.join(os.environ['SVO_DATASET_DIR'], dataset)
-    if not os.path.exists(params['dataset_directory']):
-        raise Exception("Provided dataset folder does not exist.")
-    dataset_params_file = os.path.join(params['dataset_directory'], 'dataset_params.yaml')
-    dataset_params = yaml.load(open(dataset_params_file,'r'))
-      
-    # load algorithm parameters
-    algo_params_file = os.path.join(rospkg.RosPack().get_path('svo_ros'), 
-                                   'param', params['param_settings']+'.yaml')
-    algo_params = yaml.load(open(algo_params_file,'r'))
-    
-    # combine all parameters
-    if 'rig_size' not in dataset_params or dataset_params['rig_size'] == 1:
-        params = dict(params.items() + algo_params.items() + dataset_params['cam0'].items())
-    else:
-        params = dict(params.items() + algo_params.items() + dataset_params.items())
-    if 'dataset_is_blender' in dataset_params:
-        params['dataset_is_blender'] = dataset_params['dataset_is_blender']
-    else:
-        params['dataset_is_blender'] = False
-    if 'dataset_first_frame' in dataset_params:
-        params['dataset_first_frame'] = dataset_params['dataset_first_frame']
-    else:
-        params['dataset_first_frame'] = 0
-    
-    # dump experiment params to file and copy the other parameter files:
-    params_dump_file = os.path.join(params['trace_dir'],'params.yaml')
-    with open(params_dump_file,'w') as outfile:
-        outfile.write(yaml.dump(params, default_flow_style=False))
-    shutil.copyfile(dataset_params_file,
-                    os.path.join(params['trace_dir'], 'dataset_params.yaml'))
-    
-    # copy the groundtruth trajectory to the trace dir for later evaluation
-    if params['dataset_is_blender']:
-        shutil.copyfile(os.path.join(params['dataset_directory'], 'trajectory_nominal.txt'),
-                        os.path.join(params['trace_dir'], 'groundtruth_matched.txt'))
-    else:
-        shutil.copyfile(os.path.join(params['dataset_directory'], 'groundtruth_matched.txt'),
-                        os.path.join(params['trace_dir'], 'groundtruth_matched.txt'))
-    
-    # execute ros node
-    node = ros_node.RosNode(args.version, args.executable)
-    node.run(params)
-    
-if __name__=="__main__":
-  
-    # parse command line
-    parser = argparse.ArgumentParser(description='''
-    Runs SVO with the dataset and parameters specified in the provided experiment file.
-    ''')
-    parser.add_argument('experiment_file', help='experiment file in svo_analysis/experiments folder')
-    parser.add_argument('--evaluate', help='evaluate tracefile after running SVO', action='store_true')
-    parser.add_argument('--version', help='version of svo to evaluate', default='svo_ros')
-    parser.add_argument('--executable', help='the executable to be called', default='benchmark')
-    args = parser.parse_args()
-    
-    # load experiment parameters
-    args.experiment_file = args.experiment_file.replace('.yaml','')
-    experiment_params_file = os.path.join(rospkg.RosPack().get_path('svo_analysis'), 
-                               'experiments', args.experiment_file+'.yaml')
-    if os.path.exists(experiment_params_file):
-        experiment_params = yaml.load(open(experiment_params_file, 'r'))
-    else:
-        print('experiment file does not exist. run with default setttings')
-        experiment_params = dict({'experiment_label':'default','param_settings':'vo_fast',
-                                  'datasets':list([args.experiment_file])})
-    params = dict()
-    params['experiment_label'] = experiment_params['experiment_label']
-    params['param_settings'] = experiment_params['param_settings']
-    params['time'] = time.strftime("%Y%m%d_%H%M", time.localtime())
-    params['platform'] = cpu_info.get_cpu_info()
-    params['trace_name'] = 'trace'
-    
-    trace_dirs = list()
-    for dataset in experiment_params['datasets']:
-        params['experiment_name'] = params['time']+'_'+args.version+'_'+args.experiment_file+'_'+dataset
-        params['trace_dir'] = os.path.join(rospkg.RosPack().get_path('svo_analysis'),
-                                           'results', params['experiment_name'])
-        if not os.path.exists(params['trace_dir']):
-            os.makedirs(params['trace_dir'])
-        trace_dirs.append(params['trace_dir'])
-        run_experiment(dataset, params)
-        
-    # TODO: check if it is a synthetic dataset 
-    for trace in trace_dirs:
-        evaluate.evaluate_dataset(trace)
-      
-      
-  
-  
-  
-  
diff --git a/CPU_version/svo_analysis/scripts/compare_results.py b/CPU_version/svo_analysis/scripts/compare_results.py
deleted file mode 100755
index 5605fe3..0000000
--- a/CPU_version/svo_analysis/scripts/compare_results.py
+++ /dev/null
@@ -1,150 +0,0 @@
-#!/usr/bin/python
-
-import os
-import sys
-import time
-import rospkg
-import numpy as np
-import matplotlib.pyplot as plt
-import yaml
-import argparse
-from matplotlib import rc
-
-# tell matplotlib to use latex font
-rc('font',**{'family':'serif','serif':['Cardo']})
-rc('text', usetex=True)    
-  
-from mpl_toolkits.axes_grid1.inset_locator import zoomed_inset_axes
-from mpl_toolkits.axes_grid1.inset_locator import mark_inset
-
-def plot_trajectory(ax, filename, label, color, linewidth):
-  file = open(filename)
-  data = file.read()
-  lines = data.replace(","," ").replace("\t"," ").split("\n")
-  trajectory = np.array([[v.strip() for v in line.split(" ") if v.strip()!=""] for line in lines if len(line)>0 and line[0]!="#"], dtype=np.float64)
-  ax.plot(trajectory[:,1], trajectory[:,2], label=label, color=color, linewidth=linewidth)
-
-def compare_results(experiments, results_dir, comparison_dir, 
-                    plot_scale_drift = False):
-  
-  # ------------------------------------------------------------------------------
-  # position error 
-  fig_poserr = plt.figure(figsize=(8,6))
-  ax_poserr_x = fig_poserr.add_subplot(311, ylabel='x-error [m]')
-  ax_poserr_y = fig_poserr.add_subplot(312, ylabel='y-error [m]')
-  ax_poserr_z = fig_poserr.add_subplot(313, ylabel='z-error [m]', xlabel='time [s]')
-  
-  for exp in experiments:
-    
-    # load dataset parameters
-    params_stream = open(os.path.join(results_dir, exp, 'params.yaml'))
-    params = yaml.load(params_stream)
-  
-    # plot translation error
-    trans_error = np.loadtxt(os.path.join(results_dir, exp, 'translation_error.txt'))
-    trans_error[:,0] = trans_error[:,0]-trans_error[0,0]
-    ax_poserr_x.plot(trans_error[:,0], trans_error[:,1], label=params['experiment_label'])
-    ax_poserr_y.plot(trans_error[:,0], trans_error[:,2])
-    ax_poserr_z.plot(trans_error[:,0], trans_error[:,3])
-    
-  ax_poserr_x.set_xlim([0, trans_error[-1,0]+4])
-  ax_poserr_y.set_xlim([0, trans_error[-1,0]+4]) 
-  ax_poserr_z.set_xlim([0, trans_error[-1,0]+4])
-  ax_poserr_x.legend(bbox_to_anchor=[0, 0], loc='lower left', ncol=3)
-  ax_poserr_x.grid()
-  ax_poserr_y.grid()
-  ax_poserr_z.grid()
-  fig_poserr.tight_layout()
-  fig_poserr.savefig(os.path.join(comparison_dir, 'translation_error.pdf'))
-  
-  # ------------------------------------------------------------------------------
-  # orientation error 
-  fig_roterr = plt.figure(figsize=(8,6))
-  ax_roterr_r = fig_roterr.add_subplot(311, ylabel='roll-error [rad]')
-  ax_roterr_p = fig_roterr.add_subplot(312, ylabel='pitch-error [rad]')
-  ax_roterr_y = fig_roterr.add_subplot(313, ylabel='yaw-error [rad]', xlabel='time [s]')
-  
-  for exp in experiments:
-    
-    # load dataset parameters
-    params_stream = open(os.path.join(results_dir, exp, 'params.yaml'))
-    params = yaml.load(params_stream)
-  
-    # plot translation error
-    rot_error = np.loadtxt(os.path.join(results_dir, exp, 'orientation_error.txt'))
-    rot_error[:,0] = rot_error[:,0]-rot_error[0,0]
-    ax_roterr_r.plot(rot_error[:,0], rot_error[:,3], label=params['experiment_label'])
-    ax_roterr_p.plot(rot_error[:,0], rot_error[:,2])
-    ax_roterr_y.plot(rot_error[:,0], rot_error[:,1])
-    
-  ax_roterr_r.set_xlim([0, rot_error[-1,0]+4])
-  ax_roterr_p.set_xlim([0, rot_error[-1,0]+4])
-  ax_roterr_y.set_xlim([0, rot_error[-1,0]+4])
-  ax_roterr_r.legend(bbox_to_anchor=[0, 1], loc='upper left', ncol=3)
-  ax_roterr_r.grid()
-  ax_roterr_p.grid()
-  ax_roterr_y.grid()
-  fig_roterr.tight_layout()
-  fig_roterr.savefig(os.path.join(comparison_dir, 'orientation_error.pdf'))
-  
-  # ------------------------------------------------------------------------------
-  # scale error 
-  if plot_scale_drift:
-    fig_scale = plt.figure(figsize=(8,2.5))
-    ax_scale = fig_scale.add_subplot(111, xlabel='time [s]', ylabel='scale change [\%]')
-    
-    for exp in experiments:
-      
-      # load dataset parameters
-      params = yaml.load(open(os.path.join(results_dir, exp, 'params.yaml')))
-    
-      # plot translation error
-      scale_drift = open(os.path.join(results_dir, exp, 'scale_drift.txt'))
-      scale_drift[:,0] = scale_drift[:,0]-scale_drift[0,0]
-      ax_scale.plot(scale_drift[:,0], scale_drift[:,1], label=params['experiment_label'])
-  
-    ax_scale.set_xlim([0, rot_error[-1,0]+4])
-    ax_scale.legend(bbox_to_anchor=[0, 1], loc='upper left', ncol=3)
-    ax_scale.grid()
-    fig_scale.tight_layout()
-    fig_scale.savefig(os.path.join(comparison_dir, 'scale_drift.pdf'))
-  
-  # ------------------------------------------------------------------------------
-  # trajectory
-  
-#   fig_traj = plt.figure(figsize=(8,4.8))
-#   ax_traj = fig_traj.add_subplot(111, xlabel='x [m]', ylabel='y [m]', aspect='equal', xlim=[-3.1, 4], ylim=[-1.5, 2.6])
-# 
-#   plotTrajectory(ax_traj, '/home/cforster/Datasets/asl_vicon_d2/groundtruth_filtered.txt', 'Groundtruth', 'k', 1.5)
-#   plotTrajectory(ax_traj, results_dir+'/20130911_2229_nslam_i7_asl2_fast/traj_estimate_rotated.txt', 'Fast', 'g', 1)
-#   plotTrajectory(ax_traj, results_dir+'/20130906_2149_ptam_i7_asl2/traj_estimate_rotated.txt', 'PTAM', 'r', 1)
-# 
-#   mark_inset(ax_traj, axins, loc1=2, loc2=4, fc="none", ec='b')
-#   plt.draw()
-#   plt.show() 
-#   ax_traj.legend(bbox_to_anchor=[1, 0], loc='lower right', ncol=3)
-#   ax_traj.grid()
-#   fig_traj.tight_layout()
-#   fig_traj.savefig('../results/trajectory_asl.pdf')
-  
-  
-if __name__ == '__main__':
-  
-  default_name = time.strftime("%Y%m%d_%H%M", time.localtime())+'_comparison'
-  parser = argparse.ArgumentParser(description='Compare results.')
-  parser.add_argument('result_directories', nargs='+', help='list of result directories to compare')
-  parser.add_argument('--name', help='name of the comparison', default=default_name)
-  args = parser.parse_args()
- 
-  # create folder for comparison results
-  results_dir = os.path.join(rospkg.RosPack().get_path('svo_analysis'), 'results')
-  comparison_dir = os.path.join(results_dir, args.name)
-  if not os.path.exists(comparison_dir):
-    os.makedirs(comparison_dir)
-    
-  # run comparison
-  compare_results(args.result_directories, results_dir, comparison_dir) 
-  
- 
-                 
-           
diff --git a/CPU_version/svo_analysis/scripts/comparison.py b/CPU_version/svo_analysis/scripts/comparison.py
deleted file mode 100755
index a502ad1..0000000
--- a/CPU_version/svo_analysis/scripts/comparison.py
+++ /dev/null
@@ -1,159 +0,0 @@
-#!/usr/bin/python
-
-import os
-import sys
-import time
-import rospkg
-import numpy as np
-import matplotlib.pyplot as plt
-import yaml
-import argparse
-import svo_analysis.analyse_depth as analyse_depth
-from matplotlib import rc
-
-# tell matplotlib to use latex font
-rc('font',**{'family':'serif','serif':['Cardo']})
-rc('text', usetex=True)    
-  
-from mpl_toolkits.axes_grid1.inset_locator import zoomed_inset_axes
-from mpl_toolkits.axes_grid1.inset_locator import mark_inset
-
-def plot_trajectory(ax, filename, label, color, linewidth):
-    file = open(filename)
-    data = file.read()
-    lines = data.replace(","," ").replace("\t"," ").split("\n")
-    trajectory = np.array([[v.strip() for v in line.split(" ") if v.strip()!=""] for line in lines if len(line)>0 and line[0]!="#"], dtype=np.float64)
-    ax.plot(trajectory[:,1], trajectory[:,2], label=label, color=color, linewidth=linewidth)
-
-def save_figure(fig, name, directory):
-    fig.tight_layout()
-    fig.savefig(os.path.join(directory, name+'.pdf'), bbox_inches="tight")
-
-def distances_along_trajectory(traj):
-    keys = traj.keys()
-    keys.sort()
-    motion = [ominus(traj[keys[i+1]],traj[keys[i]]) for i in range(len(keys)-1)]
-    distances = [0]
-    sum = 0
-    for t in motion:
-        sum += compute_distance(t)
-        distances.append(sum)
-    return distances
-    
-def get_distance_from_start(gt):
-    distances = np.diff(gt[:,1:4],axis=0)
-    distances = np.sqrt(np.sum(np.multiply(distances,distances),1))
-    distances = np.cumsum(distances)
-    distances = np.concatenate(([0], distances))
-    return distances
-    
-def compare_results(comp_params, results_dir, comparison_dir):
-    print('run comparison: '+comp_params['comparison_name'])
-           
-    line_styles = ['-','--',':']
-    line_colors = ['b','g','r','m','c']
-    
-    # -------------------------------------------------------------------------
-    # plot trajectory:
-    fig = plt.figure(figsize=(6,2))
-    ax = fig.add_subplot(111, xlabel='x [m]', ylabel='y [m]')
-    for exp_set in comp_params['experiment_sets']:
-        print('processing experiment set: ' + exp_set['label'])
-        
-        for i, exp in enumerate(exp_set['experiments']):
-            data = np.loadtxt(os.path.join(results_dir, exp, 'traj_estimate.txt'))
-            if i == 0:
-                base_plot, = ax.plot(data[:,1], data[:,2], label=exp_set['label'], linestyle=line_styles[np.mod(i, len(line_styles))])
-            else:
-                ax.plot(data[:,1], data[:,2], color=base_plot.get_color(), linestyle= line_styles[np.mod(i, len(line_styles))])
-    ax.legend(loc='upper left', ncol=3)
-    save_figure(fig, 'trajectory', comparison_dir)
-    
-    # -------------------------------------------------------------------------
-    # plot translation error:
-    fig = plt.figure(figsize=(6,2))
-    ax = fig.add_subplot(111, xlabel='distance [m]', ylabel='translation drift [mm]')
-    for exp_set in comp_params['experiment_sets']:
-        print('processing experiment set: ' + exp_set['label'])
-        
-        for i, exp in enumerate(exp_set['experiments']):
-            gt = np.loadtxt(os.path.join(results_dir, exp, 'groundtruth_matched.txt'))
-            distances = get_distance_from_start(gt)
-            data = np.loadtxt(os.path.join(results_dir, exp, 'translation_error.txt'))
-            e = np.sqrt(np.sum(np.multiply(data[:,1:4],data[:,1:4]),1))
-            
-            if np.shape(e)[0] > np.shape(distances)[0]:
-                print('WARNING: estimate has more measurement than groundtruth: '
-                      +str(np.shape(e)[0]-np.shape(distances)[0]))
-                e = e[0:np.shape(distances)[0]]
-                
-            distances = distances[0:np.shape(e)[0]]
-            
-            print '--'
-            print np.shape(e)
-            print np.shape(distances)
-            
-            if i == 0:
-                base_plot, = ax.plot(distances, e*1000, label=exp_set['label'], linestyle= line_styles[np.mod(i, len(line_styles))])
-            else:
-                ax.plot(distances, e*1000, color=base_plot.get_color(), linestyle= line_styles[np.mod(i, len(line_styles))])
-                
-    ax.legend(loc='upper left', ncol=3)
-    save_figure(fig, 'translation_error', comparison_dir)
-    
-    # -------------------------------------------------------------------------
-    # plot depth estimation error:
-    fig = plt.figure(figsize=(6,5))
-    ax = fig.add_subplot(111, xlabel='Travelled distance [m]', ylabel='Error [m]')
-    for k, exp_set in enumerate(comp_params['experiment_sets']):
-        print('plot depth error for experiment: ' + exp)
-        exp = exp_set['experiments'][0]
-        gt = np.loadtxt(os.path.join(results_dir, exp, 'groundtruth_matched.txt'))
-        x_axis_data = get_distance_from_start(gt)
-        analyse_depth.plot_depth_over_time(os.path.join(results_dir, exp), ax,
-                                           x_axis_data[1:], line_colors[k], exp_set['label'])
-        ax.legend(loc='upper left', ncol=3)
-    save_figure(fig, 'depth_error_textures', comparison_dir)
-    
-    fig = plt.figure(figsize=(6,5))
-    ax = fig.add_subplot(111, xlabel='Travelled distance [m]', ylabel='Error [m]')
-    exp_set = comp_params['experiment_sets'][0]
-    for i, exp in enumerate(exp_set['experiments']):
-        print('plot depth error for speed: ' + exp)
-        gt = np.loadtxt(os.path.join(results_dir, exp, 'groundtruth_matched.txt'))
-        x_axis_data = get_distance_from_start(gt)
-        params = yaml.load(open(os.path.join(results_dir, exp, 'dataset_params.yaml')))
-        analyse_depth.plot_depth_over_time(os.path.join(results_dir, exp), ax,
-                                           x_axis_data[1:], line_colors[i],
-                                           str(params['trajectory_modifiers']['speed'])+' m/s')
-    ax.legend(loc='upper left', ncol=3)
-    save_figure(fig, 'depth_error_speed', comparison_dir)
-  
-if __name__ == '__main__':
-  
-    parser = argparse.ArgumentParser(description='Compare results of a VO pipeline.')
-    parser.add_argument('comparison_file', help='A YAML file that contains the details of the comparison')
-    args = parser.parse_args()
-     
-    # load comparison file
-    args.experiment_file = args.comparison_file.replace('.yaml','')
-    comparison_params_file = os.path.join(rospkg.RosPack().get_path('svo_analysis'), 
-                                          'comparisons', args.comparison_file+'.yaml')
-    if os.path.exists(comparison_params_file):
-        comp_params = yaml.load(open(comparison_params_file, 'r'))
-    else:
-        raise Exception("Provided comparison file does not exist.")
-        
-    # create folder for comparison results
-    comparison_dir = os.path.join(rospkg.RosPack().get_path('svo_analysis'), 
-                                  'comparisons', comp_params['comparison_name'])
-    if not os.path.exists(comparison_dir):
-        os.makedirs(comparison_dir)
-
-    # folder where the results of previous experiments are saved    
-    results_dir = os.path.join(rospkg.RosPack().get_path('svo_analysis'), 'results')
-    
-    # run comparison
-    compare_results(comp_params, results_dir, comparison_dir) 
-                
-           
diff --git a/CPU_version/svo_analysis/scripts/evaluate.py b/CPU_version/svo_analysis/scripts/evaluate.py
deleted file mode 100755
index 726544c..0000000
--- a/CPU_version/svo_analysis/scripts/evaluate.py
+++ /dev/null
@@ -1,58 +0,0 @@
-#!/usr/bin/python
-"""
-Created on Sat Aug 10 18:21:47 2013
-
-@author: Christian Forster
-"""
-
-import os
-import csv
-import numpy as np
-import rospkg
-import argparse
-import yaml
-import svo_analysis.analyse_logs as analyse_logs
-import svo_analysis.analyse_timing as analyse_timing
-import svo_analysis.analyse_trajectory as analyse_trajectory
-import svo_analysis.analyse_depth as analyse_depth
-
-def evaluate_dataset(trace_dir):
-  
-    # read tracefile
-    data = csv.reader(open(os.path.join(trace_dir, 'trace.csv')))
-    fields = data.next()
-    D = dict()
-    for field in fields:
-        D[field] = list()
-
-    # fill dictionary with column values
-    for row in data:
-        for (field, value) in zip(fields, row):
-          D[field].append(float(value))
-
-    # change dictionary values from list to numpy array for easier manipulation
-    for field, value in D.items():
-        D[field] = np.array(D[field])
-
-    # generate plots
-    analyse_logs.analyse_logs(D, trace_dir)
-    analyse_timing.analyse_timing(D, trace_dir)
-    analyse_trajectory.analyse_trajectory(trace_dir)
-
-    param = yaml.load(open(os.path.join(trace_dir, 'dataset_params.yaml'), 'r'))
-    if param['dataset_is_blender']:
-        analyse_depth.analyse_depth(trace_dir)
-        analyse_depth.analyse_depth_over_time(trace_dir)
-
-
-if __name__=="__main__":
-    parser = argparse.ArgumentParser(description='''
-    Evaluates tracefiles of SVO and generates the plots.
-    ''')
-    parser.add_argument('experiment_name', help='directory name of the tracefiles')
-    args = parser.parse_args()
-
-    trace_dir = os.path.join(rospkg.RosPack().get_path('svo_analysis'), 
-                             'results',
-                             args.experiment_name)
-    evaluate_dataset(trace_dir)
\ No newline at end of file
diff --git a/CPU_version/svo_analysis/setup.py b/CPU_version/svo_analysis/setup.py
deleted file mode 100644
index 0d94673..0000000
--- a/CPU_version/svo_analysis/setup.py
+++ /dev/null
@@ -1,12 +0,0 @@
-#!/usr/bin/env python
-
-from distutils.core import setup
-from catkin_pkg.python_setup import generate_distutils_setup
-
-d = generate_distutils_setup(
-    packages=['svo_analysis'],
-    package_dir={'': 'src'},
-    install_requires=['rospkg', 'yaml'],
-    )
-
-setup(**d)
\ No newline at end of file
diff --git a/CPU_version/svo_analysis/src/__init__.py b/CPU_version/svo_analysis/src/__init__.py
deleted file mode 100644
index e69de29..0000000
diff --git a/CPU_version/svo_analysis/src/svo_analysis/__init__.py b/CPU_version/svo_analysis/src/svo_analysis/__init__.py
deleted file mode 100644
index e69de29..0000000
diff --git a/CPU_version/svo_analysis/src/svo_analysis/analyse_dataset.py b/CPU_version/svo_analysis/src/svo_analysis/analyse_dataset.py
deleted file mode 100644
index 53a2501..0000000
--- a/CPU_version/svo_analysis/src/svo_analysis/analyse_dataset.py
+++ /dev/null
@@ -1,41 +0,0 @@
-# -*- coding: utf-8 -*-
-
-import associate
-import numpy as np
-import matplotlib.pyplot as plt
-import yaml
-
-def loadDataset(filename):
-  file = open(filename)
-  data = file.read()
-  lines = data.replace(","," ").replace("\t"," ").split("\n")
-  D = np.array([[v.strip() for v in line.split(" ") if v.strip()!=""] for line in lines if len(line)>0 and line[0]!="#"], dtype=np.float64)
-  return D
-  
-dataset_dir = '/home/cforster/Datasets/SlamBenchmark/px4_r2'
-trajectory_data = dataset_dir+'/groundtruth.txt'
-stepsize = 10
-
-# load dataset
-data = loadDataset(trajectory_data)
-n = data.shape[0]
-steps = np.arange(0,n,stepsize)
-
-# compute trajectory length
-last_pos = data[0,1:4]
-trajectory_length = 0
-
-for i in steps[1:]:
-  new_pos = data[i,1:4]
-  trajectory_length += np.linalg.norm(new_pos-last_pos)
-  last_pos = new_pos
-  
-
-print 'trajectory lenght = ' + str(trajectory_length) + 'm'
-print 'height mean = ' + str(np.mean(data[:,3])) + 'm'
-print 'height median = ' + str(np.median(data[:,3])) + 'm'
-print 'height std = ' + str(np.std(data[:,3])) + 'm'
-print 'duration = ' + str(data[-1,0]-data[0,0]) + 's'
-print 'speed = ' + str(trajectory_length/(data[-1,0]-data[0,0])) + 'm/s'
-
-  
diff --git a/CPU_version/svo_analysis/src/svo_analysis/analyse_depth.py b/CPU_version/svo_analysis/src/svo_analysis/analyse_depth.py
deleted file mode 100755
index 8a21b53..0000000
--- a/CPU_version/svo_analysis/src/svo_analysis/analyse_depth.py
+++ /dev/null
@@ -1,66 +0,0 @@
-#!/usr/bin/python
-
-import os
-import argparse
-import numpy as np
-import matplotlib.pyplot as plt
-from matplotlib import rc
-
-rc('font',**{'family':'serif','serif':['Cardo']})
-rc('text', usetex=True)
-
-def precision_plot(ax, errors, max_error, color, linestyle):
-    number_of_error_ranges = 500
-    error_step = max_error / number_of_error_ranges
-    precision_array = np.zeros(number_of_error_ranges)
-    error_array = np.zeros(number_of_error_ranges)
-    n_measurements = len(errors)
-    for error_ind in range(0, number_of_error_ranges):
-        precision_array[error_ind] = np.sum(errors < error_step*error_ind) / float(n_measurements) * 100.0
-        error_array[error_ind] = error_step*error_ind
-    plot_obj, = ax.plot(error_array, precision_array, label='error', linestyle=linestyle, color=color)
-    return plot_obj
-    
-def analyse_depth(results_dir):
-    D = np.loadtxt(os.path.join(results_dir, 'depth_error.txt'), delimiter=' ')
-    D = D[D[:,0] > 1,:]
-
-    fig = plt.figure(figsize=(6,5))
-    ax = fig.add_subplot(111, xlabel='depth error [m]', ylabel='Precision [\%]')
-    errors = np.abs(D[:,1])
-    precision_plot(ax, errors, 0.05, 'r', '-')    
-    fig.tight_layout()
-    fig.savefig(os.path.join(results_dir,'depth_error.pdf'), bbox_inches="tight")
-    
-
-def plot_depth_over_time(results_dir, ax, x_axis_data, color, label=''):
-    D = np.loadtxt(os.path.join(results_dir, 'depth_error.txt'), delimiter=' ')
-    D = D[D[:,0] > 1,:]
-    idxs = np.unique(D[:,0])
-    percentile_10 = np.zeros(len(idxs))
-    percentile_50 = np.zeros(len(idxs))
-    percentile_90 = np.zeros(len(idxs))
-    for i in range(len(idxs)):
-        errors = np.abs(D[D[:,0]==idxs[i],1])
-        percentile_10[i] = np.percentile(errors, 10)
-        percentile_50[i] = np.percentile(errors, 50)
-        percentile_90[i] = np.percentile(errors, 90)
-    if len(x_axis_data) == 0:
-        x_axis_data = idxs
-    print np.shape(x_axis_data)
-    print np.shape(idxs)
-    print '--'
-    ax.plot(x_axis_data, percentile_50, linewidth=2, color=color, label=label)
-    ax.plot(x_axis_data, percentile_10, linewidth=0.5, color=color, alpha=0.5)
-    ax.plot(x_axis_data, percentile_90, linewidth=0.5, color=color, alpha=0.5)
-    ax.fill_between(x_axis_data, percentile_10, percentile_90, color=color, alpha=0.1)
-     
-if __name__ == '__main__':
-    parser = argparse.ArgumentParser(description='Analyse depth estimate')
-    parser.add_argument('results_dir', help='folder with the results')
-    args = parser.parse_args()
-    analyse_depth(args.results_dir)
-    
-    fig = plt.figure(figsize=(6,5))
-    ax = fig.add_subplot(111, xlabel='Measurement', ylabel='Scale-Drift')
-    plot_depth_over_time(args.results_dir, [], ax)
\ No newline at end of file
diff --git a/CPU_version/svo_analysis/src/svo_analysis/analyse_logs.py b/CPU_version/svo_analysis/src/svo_analysis/analyse_logs.py
deleted file mode 100755
index 7dc2acc..0000000
--- a/CPU_version/svo_analysis/src/svo_analysis/analyse_logs.py
+++ /dev/null
@@ -1,74 +0,0 @@
-#!/usr/bin/python
-
-import os
-import yaml
-import numpy as np
-import matplotlib.pyplot as plt
-  
-def analyse_logs(D, trace_dir):
-
-  # identify measurements which result from normal frames and which from keyframes
-  is_kf = np.argwhere( (D['dropout'] == 1) & (D['repr_n_mps'] >= 0))
-  is_frame = np.argwhere(D['repr_n_mps'] >= 0)
-  is_nokf = np.argwhere( (D['dropout'] == 0) & (D['repr_n_mps'] >= 0))
-   
-  # set initial time to zero
-  D['timestamp'] = D['timestamp'] - D['timestamp'][0]
-  
-  # ----------------------------------------------------------------------------
-  # plot number of reprojected points
-  mean_n_reproj_points = np.mean(D['repr_n_mps'][is_frame]);
-  mean_n_reproj_matches = np.mean(D['repr_n_new_references'][is_frame]);
-  mean_n_edges_final = np.mean(D['sfba_n_edges_final'][is_frame]);
-
-  fig = plt.figure(figsize=(8,3))
-  ax = fig.add_subplot(111, xlabel='time [s]')
-  ax.plot(D['timestamp'][is_frame], D['repr_n_mps'][is_frame], 'r-',
-          label='Reprojected Points, avg = %.2f'%mean_n_reproj_points)
-  ax.plot(D['timestamp'][is_frame], D['repr_n_new_references'][is_frame], 'b-', 
-          label='Feature Matches, avg = %.2f'%mean_n_reproj_matches)
-  ax.plot(D['timestamp'][is_frame], D['sfba_n_edges_final'][is_frame], 'g-', 
-          label='Points after Optimization, avg = %.2f'%mean_n_edges_final)
-  ax.set_ylim(bottom=0)
-  ax.legend(loc='lower right')
-  fig.tight_layout()
-  fig.savefig(os.path.join(trace_dir,'num_reprojected.pdf'), bbox_inches="tight")
-
-  # ----------------------------------------------------------------------------
-  # plot median error before and after pose-optimzation and bundle adjustment
-  init_error_avg = np.mean(D['sfba_error_init'][is_frame])
-  opt1_avg = np.mean(D['sfba_error_final'][is_frame])
-
-  fig = plt.figure(figsize=(8,2))
-  ax = fig.add_subplot(111, xlabel='time [s]', ylabel='error [px]')
-  ax.plot(D['timestamp'][is_frame], D['sfba_error_init'][is_frame], 'r-', label='Initial error')
-  ax.plot(D['timestamp'][is_frame], D['sfba_error_final'][is_frame], 'b-', label='Final error')
-  ax.legend(ncol=2)  
-  fig.tight_layout()
-  fig.savefig(os.path.join(trace_dir,'reprojection_error.pdf'), bbox_inches="tight")
-  print 'average reprojection error improvement: ' + str(init_error_avg - opt1_avg)
-
-  # ----------------------------------------------------------------------------
-  # plot number of candidate points
-  fig = plt.figure(figsize=(8,3))
-  ax = fig.add_subplot(111, xlabel='time [s]')
-  ax.plot(D['timestamp'][is_frame], D['n_candidates'][is_frame], 'r-', label='Candidate Points')
-  fig.tight_layout()
-  fig.savefig(os.path.join(trace_dir,'candidate_points.pdf'), bbox_inches="tight")
-  
-  # ----------------------------------------------------------------------------
-  # plot number of candidate points
-  fig = plt.figure(figsize=(8,2))
-  ax = fig.add_subplot(111, xlabel='time [s]', ylabel='px')
-  ax.plot(D['timestamp'][is_frame], D['sfba_thresh'][is_frame], 'r-', label='Threshold')
-  fig.tight_layout()
-  fig.savefig(os.path.join(trace_dir,'optimization_thresh.pdf'), bbox_inches="tight")
-  
-  # ----------------------------------------------------------------------------
-  # write other statistics to file
-  stat = {'num_frames': len(is_frame), 
-          'num_kfs': len(is_kf),
-          'reproj_error_avg_improvement': float(init_error_avg - opt1_avg)}
-  with open(os.path.join(trace_dir,'dataset_stats.yaml'),'w') as outfile:          
-    outfile.write(yaml.dump(stat, default_flow_style=False))
-
diff --git a/CPU_version/svo_analysis/src/svo_analysis/analyse_timing.py b/CPU_version/svo_analysis/src/svo_analysis/analyse_timing.py
deleted file mode 100755
index 0dfc1bc..0000000
--- a/CPU_version/svo_analysis/src/svo_analysis/analyse_timing.py
+++ /dev/null
@@ -1,68 +0,0 @@
-#!/usr/bin/python
-
-import os
-import numpy as np
-import matplotlib.pyplot as plt
-
-def analyse_timing(D, trace_dir):
-
-  # identify measurements which result from normal frames and which from keyframes
-  is_frame = np.argwhere(D['repr_n_mps'] >= 0)
-  n_frames = len(is_frame)
-  
-  # set initial time to zero
-  D['timestamp'] = D['timestamp'] - D['timestamp'][0]
-
-  # ----------------------------------------------------------------------------
-  # plot total time for frame processing
-  avg_time = np.mean(D['tot_time'][is_frame])*1000;
-  fig = plt.figure(figsize=(8, 3))
-  ax = fig.add_subplot(111, ylabel='processing time [ms]', xlabel='time [s]')
-  ax.plot(D['timestamp'][is_frame], D['tot_time'][is_frame]*1000, 'g-', label='total time [ms]')
-  ax.plot(D['timestamp'][is_frame], np.ones(n_frames)*avg_time, 'b--', label=str('%(time).1fms mean time' % {'time': avg_time}))
-  ax.legend()
-  fig.tight_layout()
-  fig.savefig(os.path.join(trace_dir,'timing.pdf'), bbox_inches="tight")
-  
-  # ----------------------------------------------------------------------------
-  # plot boxplot
-  fig = plt.figure(figsize=(6,2))
-  ax = fig.add_subplot(111, xlabel='Processing time [ms]')
-  ax.boxplot([ 
-                D['tot_time'][is_frame]*1000,
-#                D['t_local_ba'][is_kf]*1000,
-                D['pose_optimizer'][is_frame]*1000 + D['point_optimizer'][is_frame]*1000,
-                D['reproject'][is_frame]*1000,
-                D['sparse_img_align'][is_frame]*1000,
-                D['pyramid_creation'][is_frame]*1000
-              ], 0,'', vert=0) 
-               
-  boxplot_labels = [
-                    r'\textbf{Total Motion Estimation: %2.2fms}' % np.median(D['tot_time'][is_frame]*1000),
-#                    'Local BA (KF only): %.2fms ' % np.median(D['local_ba'][is_kf]*1000),
-                    'Refinement: %2.2fms' % np.median(D['pose_optimizer'][is_frame]*1000 + D['point_optimizer'][is_frame]*1000),
-                    'Feature Alignment: %2.2fms' % np.median(D['reproject'][is_frame]*1000),
-                    'Sparse Image Alignment: %2.2fms' % np.median(D['sparse_img_align'][is_frame]*1000),
-                    'Pyramid Creation: %2.2fms' % np.median(D['pyramid_creation'][is_frame]*1000) ]
-                   
-  ax.set_yticks(np.arange(len(boxplot_labels))+1)
-  ax.set_yticklabels(boxplot_labels)
-  fig.tight_layout()
-  fig.savefig(os.path.join(trace_dir,'timing_boxplot.pdf'), bbox_inches="tight")
-  
-  # ----------------------------------------------------------------------------
-  # plot boxplot reprojection
-  fig = plt.figure(figsize=(6,2))
-  ax = fig.add_subplot(111, xlabel='Processing time [ms]')
-  ax.boxplot([ D['reproject'][is_frame]*1000,
-               D['feature_align'][is_frame]*1000,
-               D['reproject_candidates'][is_frame]*1000,
-               D['reproject_kfs'][is_frame]*1000 ], 0, '', vert=0) 
-  boxplot_labels = [r'\textbf{Total Reprojection: %2.2fms}' % np.median(D['reproject'][is_frame]*1000),
-                     'Feature Alignment: %2.2fms' % np.median(D['feature_align'][is_frame]*1000),
-                     'Reproject Candidates: %2.2fms' % np.median(D['reproject_candidates'][is_frame]*1000),
-                     'Reproject Keyframes: %2.2fms' % np.median(D['reproject_kfs'][is_frame]*1000) ]             
-  ax.set_yticks(np.arange(len(boxplot_labels))+1)
-  ax.set_yticklabels(boxplot_labels)
-  fig.tight_layout()
-  fig.savefig(os.path.join(trace_dir,'timing_reprojection.pdf'), bbox_inches="tight")
\ No newline at end of file
diff --git a/CPU_version/svo_analysis/src/svo_analysis/analyse_trajectory.py b/CPU_version/svo_analysis/src/svo_analysis/analyse_trajectory.py
deleted file mode 100755
index c2c93de..0000000
--- a/CPU_version/svo_analysis/src/svo_analysis/analyse_trajectory.py
+++ /dev/null
@@ -1,185 +0,0 @@
-#!/usr/bin/python
-
-import os
-import yaml
-import argparse
-import numpy as np
-import matplotlib.pyplot as plt
-import svo_analysis.tum_benchmark_tools.associate as associate
-import vikit_py.transformations as transformations
-import vikit_py.align_trajectory as align_trajectory
-from matplotlib import rc
-rc('font',**{'family':'serif','serif':['Cardo']})
-rc('text', usetex=True)
-
-def plot_translation_error(timestamps, translation_error, results_dir):
-    fig = plt.figure(figsize=(8, 2.5))
-    ax = fig.add_subplot(111, xlabel='time [s]', ylabel='position drift [mm]', xlim=[0,timestamps[-1]-timestamps[0]+4])
-    ax.plot(timestamps-timestamps[0], translation_error[:,0]*1000, 'r-', label='x')
-    ax.plot(timestamps-timestamps[0], translation_error[:,1]*1000, 'g-', label='y')
-    ax.plot(timestamps-timestamps[0], translation_error[:,2]*1000, 'b-', label='z')
-    ax.legend()
-    fig.tight_layout()
-    fig.savefig(results_dir+'/translation_error.pdf')
-
-def plot_rotation_error(timestamps, rotation_error, results_dir):
-    fig = plt.figure(figsize=(8, 2.5))
-    ax = fig.add_subplot(111, xlabel='time [s]', ylabel='orientation drift [rad]', xlim=[0,timestamps[-1]-timestamps[0]+4])
-    ax.plot(timestamps-timestamps[0], rotation_error[:,0], 'r-', label='yaw')
-    ax.plot(timestamps-timestamps[0], rotation_error[:,1], 'g-', label='pitch')
-    ax.plot(timestamps-timestamps[0], rotation_error[:,2], 'b-', label='roll')
-    ax.legend()
-    fig.tight_layout()
-    fig.savefig(results_dir+'/orientation_error.pdf')
-
-def analyse_synthetic_trajectory(results_dir):
-    data = np.loadtxt(os.path.join(results_dir, 'translation_error.txt'))
-    timestamps = data[:,0]
-    translation_error = data[:,1:4]
-    plot_translation_error(timestamps, translation_error, results_dir)
-      
-    # plot orientation error
-    data = np.loadtxt(os.path.join(results_dir, 'orientation_error.txt'))
-    timestamps = data[:,0]
-    orientation_error = data[:,1:4]
-    plot_rotation_error(timestamps, orientation_error, results_dir)
-    
-def analyse_optitrack_trajectory_with_hand_eye_calib(results_dir, params, n_align_frames = 200):
-    print('loading hand-eye-calib')
-    T_cm_quat = np.array([params['hand_eye_calib']['Tcm_qx'],
-                          params['hand_eye_calib']['Tcm_qy'],
-                          params['hand_eye_calib']['Tcm_qz'],
-                          params['hand_eye_calib']['Tcm_qw']])
-    T_cm_tran = np.array([params['hand_eye_calib']['Tcm_tx'],
-                          params['hand_eye_calib']['Tcm_ty'],
-                          params['hand_eye_calib']['Tcm_tz']])
-    T_cm = get_rigid_body_trafo(T_cm_quat, T_cm_tran)
-    T_mc = transformations.inverse_matrix(T_cm)
-
-    t_es, p_es, q_es, t_gt, p_gt, q_gt = load_dataset(results_dir, params['cam_delay'])
-    
-    # align Sim3 to get scale
-    print('align Sim3 using '+str(n_align_frames)+' first frames.')
-    scale,rot,trans = align_trajectory.align_sim3(p_gt[0:n_align_frames,:], p_es[0:n_align_frames,:])
-    print 'scale = '+str(scale)
-  
-    # get trafo between (v)ision and (o)ptitrack frame
-    print q_gt[0,:]
-    print p_gt[0,:]
-    T_om = get_rigid_body_trafo(q_gt[0,:], p_gt[0,:])
-    T_vc = get_rigid_body_trafo(q_es[0,:], scale*p_es[0,:])
-    T_cv = transformations.inverse_matrix(T_vc)
-    T_ov = np.dot(T_om, np.dot(T_mc, T_cv))
-    print 'T_ov = ' + str(T_ov)
-  
-    # apply transformation to estimated trajectory
-    q_es_aligned = np.zeros(np.shape(q_es))
-    rpy_es_aligned = np.zeros(np.shape(p_es))
-    rpy_gt = np.zeros(np.shape(p_es))
-    p_es_aligned = np.zeros(np.shape(p_es))
-    for i in range(np.shape(p_es)[0]):
-        T_vc = get_rigid_body_trafo(q_es[i,:],p_es[i,:])
-        T_vc[0:3,3] *= scale
-        T_om = np.dot(T_ov, np.dot(T_vc, T_cm))
-        p_es_aligned[i,:] = T_om[0:3,3]
-        q_es_aligned[i,:] = transformations.quaternion_from_matrix(T_om)
-        rpy_es_aligned[i,:] = transformations.euler_from_quaternion(q_es_aligned[i,:], 'rzyx')
-        rpy_gt[i,:] = transformations.euler_from_quaternion(q_gt[i,:], 'rzyx') 
-  
-    # plot position error (drift)
-    translation_error = (p_gt-p_es_aligned)
-    plot_translation_error(t_es, translation_error, results_dir)
-  
-    # plot orientation error (drift)
-    orientation_error = (rpy_gt - rpy_es_aligned)
-    plot_rotation_error(t_es, orientation_error, results_dir)
-
-    # plot scale drift
-    motion_gt = np.diff(p_gt, 0)
-    motion_es = np.diff(p_es_aligned, 0)
-    dist_gt = np.sqrt(np.sum(np.multiply(motion_gt,motion_gt),1))
-    dist_es = np.sqrt(np.sum(np.multiply(motion_es,motion_es),1))
-    fig = plt.figure(figsize=(8,2.5))
-    ax = fig.add_subplot(111, xlabel='time [s]', ylabel='scale change [\%]', xlim=[0,t_es[-1]+4])
-    scale_drift = np.divide(dist_es,dist_gt)*100-100
-    ax.plot(t_es, scale_drift, 'b-')
-    fig.tight_layout()
-    fig.savefig(results_dir+'/scale_drift.pdf')
-    
-    # plot trajectory
-    fig = plt.figure()
-    ax = fig.add_subplot(111, title='trajectory', aspect='equal', xlabel='x [m]', ylabel='y [m]')
-    ax.plot(p_es_aligned[:,0], p_es_aligned[:,1], 'b-', label='estimate')
-    ax.plot(p_gt[:,0], p_gt[:,1], 'r-', label='groundtruth')
-    ax.plot(p_es_aligned[0:n_align_frames,0], p_es_aligned[0:n_align_frames,1], 'g-', linewidth=2, label='aligned')
-    ax.legend()
-    fig.tight_layout()
-    fig.savefig(results_dir+'/trajectory.pdf')
-    
-def analyse_trajectory(results_dir, n_align_frames = 200, use_hand_eye_calib = True):
-    params = yaml.load(open(os.path.join(results_dir, 'dataset_params.yaml'),'r'))
-    if params['dataset_is_blender']:
-        analyse_synthetic_trajectory(results_dir)
-    elif use_hand_eye_calib:
-        analyse_optitrack_trajectory_with_hand_eye_calib(results_dir, params, n_align_frames)
-    else:
-        t_es, p_es, q_es, t_gt, p_gt, q_gt = load_dataset(results_dir, params['cam_delay'])
-        scale,rot,trans = align_trajectory.align_sim3(p_gt[0:n_align_frames,:], p_es[0:n_align_frames,:])
-        p_es_aligned = np.zeros(np.shape(p_es))
-        for i in range(np.shape(p_es)[0]):
-            p_es_aligned[i,:] = scale*rot.dot(p_es[i,:]) + trans
-        # plot position error (drift)
-        translation_error = (p_gt-p_es_aligned)
-        plot_translation_error(t_es, translation_error, results_dir)
-        
-def get_rigid_body_trafo(quat,trans):
-    T = transformations.quaternion_matrix(quat)
-    T[0:3,3] = trans
-    return T
-     
-def load_dataset(results_dir, cam_delay):
-    print('loading dataset in '+results_dir)   
-    print('cam_delay = '+str(cam_delay))
-
-    data_gt = open(os.path.join(results_dir, 'groundtruth.txt')).read()
-    lines = data_gt.replace(","," ").replace("\t"," ").split("\n") 
-    data_gt = np.array([[np.float(v.strip()) for i,v in enumerate(line.split(" ")) if v.strip()!=""] for line in lines if len(line)>0 and line[0]!="#"])
-    #data_gt = np.array([[np.float(v.strip()) for i,v in enumerate(line.split(" ")) if i != 1 and v.strip()!=""] for line in lines if len(line)>0 and line[0]!="#"])
-    data_gt = [(float(l[0]),l[1:]) for l in data_gt]
-    data_gt = dict(data_gt)    
-    
-    data_es = open(os.path.join(results_dir, 'traj_estimate.txt')).read()
-    lines = data_es.replace(","," ").replace("\t"," ").split("\n") 
-    data_es = np.array([[np.float(v.strip()) for v in line.split(" ") if v.strip()!=""] for line in lines if len(line)>0 and line[0]!="#"])
-    data_es = [(float(l[0]),l[1:]) for l in data_es]
-    data_es = dict(data_es)
-    
-    matches = associate.associate(data_gt, data_es, -cam_delay, 0.02)
-    p_gt = np.array([[np.float(value) for value in data_gt[a][0:3]] for a,b in matches])
-    q_gt = np.array([[np.float(value) for value in data_gt[a][3:7]] for a,b in matches])
-    p_es = np.array([[np.float(value) for value in data_es[b][0:3]] for a,b in matches])
-    q_es = np.array([[np.float(value) for value in data_es[b][3:7]] for a,b in matches])
-    t_gt = np.array([np.float(a) for a,b in matches])
-    t_es = np.array([np.float(b) for a,b in matches])
-  
-    # set start time to zero
-    start_time = min(t_es[0], t_gt[0])
-    t_es -= start_time
-    t_gt -= start_time
-    return t_es, p_es, q_es, t_gt, p_gt, q_gt
-  
-if __name__ == '__main__':
-  
-    # parse command line
-    parser = argparse.ArgumentParser(description='''
-    Analyse trajectory
-    ''')
-    parser.add_argument('results_dir', help='folder with the results')
-    parser.add_argument('--use_hand_eye_calib', help='', action='store_true')
-    parser.add_argument('--n_align_frames', help='', default=200)
-    args = parser.parse_args()
-    
-    print('analyse trajectory for dataset: '+str(args.results_dir))
-    analyse_trajectory(args.results_dir,
-                       n_align_frames = int(args.n_align_frames),
-                       use_hand_eye_calib = args.use_hand_eye_calib)
\ No newline at end of file
diff --git a/CPU_version/svo_analysis/src/svo_analysis/filter_groundtruth_smooth.py b/CPU_version/svo_analysis/src/svo_analysis/filter_groundtruth_smooth.py
deleted file mode 100644
index d0cc240..0000000
--- a/CPU_version/svo_analysis/src/svo_analysis/filter_groundtruth_smooth.py
+++ /dev/null
@@ -1,60 +0,0 @@
-#!/usr/bin/python
-
-
-import numpy as np
-import matplotlib.pyplot as plt
-import transformations
-from scipy import signal
-
-save = True
-data_filename = '/home/cforster/Datasets/SlamBenchmark/asl_vicon_d2/groundtruth.txt'
-filtered_data_filename = '/home/cforster/Datasets/SlamBenchmark/asl_vicon_d2/groundtruth_filtered.txt'
-file = open(data_filename)
-data = file.read()
-lines = data.replace(","," ").replace("\t"," ").split("\n")
-D = np.array([[v.strip() for v in line.split(" ") if v.strip()!=""] for line in lines if len(line)>0 and line[0]!="#"], dtype=np.float64)
-
-n = np.shape(D)[0]
-rpy = np.empty([n,3])
-for i in range(n):
-  quat = D[i,4:8]
-  rpy[i,:] = transformations.euler_from_quaternion(quat, axes='sxyz')
-
-# filter rpy
-f_sensor = 200.0; # sampling frequency in hz
-f_cut = 15.0; # cutoff frequency in hz
-b,a = signal.butter(5,f_cut/(f_sensor/2));
-print a
-print b
-
-rpy_filt = np.empty([n,3])
-rpy_filt[:,0] = signal.filtfilt(b, a, rpy[:,0])
-rpy_filt[:,1] = signal.filtfilt(b, a, rpy[:,1])
-rpy_filt[:,2] = signal.filtfilt(b, a, rpy[:,2])
-
-fig = plt.figure()
-ax = fig.add_subplot(111, title='orientation filtered')
-ax.plot(rpy[:,0], 'r-')
-ax.plot(rpy[:,1], 'g-')
-ax.plot(rpy[:,2], 'b-')
-ax.plot(rpy_filt[:,0], 'k-', linewidth=2)
-ax.plot(rpy_filt[:,1], 'k-', linewidth=2)
-ax.plot(rpy_filt[:,2], 'k-', linewidth=2)
-
-fig = plt.figure()
-ax = fig.add_subplot(111, title='position')
-ax.plot(D[:,1], 'r')
-ax.plot(D[:,2], 'g')
-ax.plot(D[:,3], 'b')
-
-fig = plt.figure()
-ax = fig.add_subplot(111, title='trajectory from top')
-ax.plot(D[:,1], D[:,2])
-
-if save:
-  f = open(filtered_data_filename,'w')
-  for i in range(np.shape(D)[0]):
-    quat = transformations.quaternion_from_euler(rpy_filt[i,0], rpy_filt[i,1], rpy_filt[i,2], axes='sxyz')
-    f.write('%.7f %.5f %.5f %.5f %.5f %.5f %.5f %.5f\n' % (D[i,0], D[i,1], D[i,2], D[i,3], quat[0], quat[1], quat[2], quat[3]))
-  
-  f.close()
diff --git a/CPU_version/svo_analysis/src/svo_analysis/hand_eye_calib.py b/CPU_version/svo_analysis/src/svo_analysis/hand_eye_calib.py
deleted file mode 100644
index a54b4f8..0000000
--- a/CPU_version/svo_analysis/src/svo_analysis/hand_eye_calib.py
+++ /dev/null
@@ -1,227 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-Created on Sun Aug  4 15:47:55 2013
-
-@author: cforster
-"""
-import os
-import yaml
-import numpy as np
-import svo_analysis.tum_benchmark_tools.associate as associate
-import vikit_py.align_trajectory as align_trajectory
-import vikit_py.transformations as transformations
-import matplotlib.pyplot as plt
-
-# user config
-display = True
-dataset_dir = '/home/cforster/catkin_ws/src/rpg_svo/svo_analysis/results/rpg_circle_1'
-n_measurements = 400
-n_align_sim3 = 600
-delta = 50
-
-# load dataset parameters
-params = yaml.load(open(os.path.join(dataset_dir, 'dataset_params.yaml')))
-
-# set trajectory groundtruth and estimate file
-traj_groundtruth = os.path.join(dataset_dir, 'groundtruth.txt')
-traj_estimate = os.path.join(dataset_dir,'traj_estimate.txt')
-
-# load data
-data_gt = associate.read_file_list(traj_groundtruth)
-data_es = associate.read_file_list(traj_estimate)
-
-# select matches
-offset = -params['cam_delay']
-print ('offset = '+str(offset))
-matches = associate.associate(data_gt, data_es, offset, 0.02)
-#matches = matches[500:]
-p_gt = np.array([[float(value) for value in data_gt[a][0:3]] for a,b in matches])
-q_gt = np.array([[float(value) for value in data_gt[a][3:7]] for a,b in matches])
-p_es = np.array([[float(value) for value in data_es[b][0:3]] for a,b in matches])
-q_es = np.array([[float(value) for value in data_es[b][3:7]] for a,b in matches])
-
-# --------------------------------------------------------------------------------
-# align Sim3 to get scale
-scale,rot,trans = align_trajectory.align_sim3(p_gt[0:n_align_sim3,:], p_es[0:n_align_sim3,:])
-
-#model_aligned = s * R * model + t
-#alignment_error = model_aligned - data
-#t_error = np.sqrt(np.sum(np.multiply(alignment_error,alignment_error),0)).A[0]
-  
-p_es_aligned = np.transpose(scale*np.dot(rot,np.transpose(p_es)))+trans
-p_es = scale*p_es
-
-             
-print 's='+str(scale)
-print 't='+str(trans)
-print 'R='+str(rot)
-
-# plot sim3 aligned trajectory
-fig = plt.figure()
-ax = fig.add_subplot(111, aspect='equal')
-ax.plot(p_es_aligned[:,0], p_es_aligned[:,1], 'r-', label='estimate', alpha=0.2)
-ax.plot(p_gt[:,0], p_gt[:,1], 'b-', label='groundtruth', alpha=0.2)
-ax.plot(p_es_aligned[:n_align_sim3,0], p_es_aligned[:n_align_sim3,1], 'g-', label='aligned', linewidth=2)
-ax.plot(p_gt[:n_align_sim3,0], p_gt[:n_align_sim3,1], 'm-', label='aligned', linewidth=2)  
-ax.legend()
-for (x1,y1,z1),(x2,y2,z2) in zip(p_es_aligned[:n_align_sim3:10],p_gt[:n_align_sim3:10]):
-    ax.plot([x1,x2],[y1,y2],'-',color="red")
-    
-fig = plt.figure()
-ax = fig.add_subplot(111)
-ax.plot(p_gt[:,0], 'r-')
-ax.plot(p_gt[:,1], 'g-')
-ax.plot(p_gt[:,2], 'b-')
-ax.plot(p_es_aligned[:,0], 'r--')
-ax.plot(p_es_aligned[:,1], 'g--')
-ax.plot(p_es_aligned[:,2], 'b--') 
-            
-
-# --------------------------------------------------------------------------------
-# hand-eye-calib
-
-# select random measurements
-I = np.array(np.random.rand(n_measurements,1)*(np.shape(matches)[0]-delta), dtype=int)[:,0]
-R,b = align_trajectory.hand_eye_calib(q_gt, q_es, p_gt, p_es, I, delta, True)
-
-print 'quat = ' + str(transformations.quaternion_from_matrix(transformations.convert_3x3_to_4x4(R)))
-print 'b = ' + str(b)
-
-rpy_es = np.zeros([q_es.shape[0]-1, 3])
-rpy_gt = np.zeros([q_gt.shape[0]-1, 3])
-t_gt = np.zeros([q_es.shape[0]-1,3])
-t_es = np.zeros([q_es.shape[0]-1,3])
-
-for i in range(delta,np.shape(q_es)[0]):
-  A1 = transformations.quaternion_matrix(q_es[i-delta,:])[:3,:3]
-  A2 = transformations.quaternion_matrix(q_es[i,:])[:3,:3]
-  A  = np.dot(A1.transpose(), A2)
-  B1 = transformations.quaternion_matrix(q_gt[i-delta,:])[:3,:3]
-  B2 = transformations.quaternion_matrix(q_gt[i,:])[:3,:3]
-  B  = np.dot(B1.transpose(), B2)
-  B_es  = np.dot(np.transpose(R), np.dot(A, R))
-  rpy_gt[i-delta,:] = transformations.euler_from_matrix(B, 'rzyx')
-  rpy_es[i-delta,:] = transformations.euler_from_matrix(B_es, 'rzyx')
-  t_B = np.dot(np.transpose(B1),(p_gt[i,:]-p_gt[i-delta,:]))
-  t_A = np.dot(np.transpose(A1),(p_es[i,:]-p_es[i-delta,:]))
-  t_gt[i-delta,:] = t_B
-  t_es[i-delta,:] = np.dot(np.transpose(R), np.dot(A,b[:,0]) + t_A - b[:,0])
-
-alignment_error = (t_gt-t_es)
-error = np.sqrt(np.sum(np.multiply(alignment_error,alignment_error),1))
-I_accurate = np.argwhere(error < np.percentile(error, 90))[:,0]
-
-if display:
-  plt.figure()
-  plt.plot(rpy_es[:,0], 'r-', label='es roll')
-  plt.plot(rpy_es[:,1], 'g-', label='es pitch')
-  plt.plot(rpy_es[:,2], 'b-', label='es yaw')
-  plt.plot(rpy_gt[:,0], 'r--', label='gt roll')
-  plt.plot(rpy_gt[:,1], 'g--', label='gt pitch')
-  plt.plot(rpy_gt[:,2], 'b--', label='gt yaw')
-  plt.legend()
-  plt.figure()
-  plt.plot(t_gt[:,0], 'r-', label='gt x')
-  plt.plot(t_gt[:,1], 'g-', label='gt y')
-  plt.plot(t_gt[:,2], 'b-', label='gt z')
-  plt.plot(t_es[:,0], 'r--', label='es x')
-  plt.plot(t_es[:,1], 'g--', label='es y')
-  plt.plot(t_es[:,2], 'b--', label='es z')
-  plt.legend()
-  plt.figure()
-  plt.plot(error,'-g')
-
-
-print 'e_rms = ' + str(np.sqrt(np.dot(error,error) / len(error)))
-print 'e_mean = ' + str(np.mean(error))
-print 'e_median = ' + str(np.median(error))
-print 'e_std = ' + str(np.std(error))
-
-
-# now sample again from the filtered list:
-N = 10
-display = False
-n_acc_meas = I_accurate.size
-n_measurements = 500
-
-#for i in range(5):
-#  print '-------------------------------------'
-#  i0 = np.array(rand(n_measurements,1)*np.shape(I_accurate)[0], dtype=int)[:,0]
-#  i1 = np.minimum(i0+N, n_acc_meas-1)
-#  I = np.empty(i0.size*2, dtype=int)
-#  I[0::2] = I_accurate[i0]
-#  I[1::2] = I_accurate[i1]
-#  R,b = handEyeCalib(q_gt[I,:], q_es[I,:], p_gt[I,:], p_es[I,:], True)
-#  print 'quat = ' + str(ru.dcm2quat(R))
-#  print 'b = ' + str(b)
-#  rpy_es = np.zeros([q_es.shape[0]-1, 3])
-#  rpy_gt = np.zeros([q_gt.shape[0]-1, 3])
-#  t_gt = np.zeros([q_es.shape[0]-1,3])
-#  t_es = np.zeros([q_es.shape[0]-1,3])
-#
-#  delta = 10
-#  for i in range(delta,np.shape(q_es)[0]):
-#    A1 = ru.quat2dcm(q_es[i-delta,:])
-#    A2 = ru.quat2dcm(q_es[i,:])
-#    A  = np.dot(A1.transpose(), A2)
-#    B1 = ru.quat2dcm(q_gt[i-delta,:])
-#    B2 = ru.quat2dcm(q_gt[i,:])
-#    B  = np.dot(B1.transpose(), B2)
-#    B_es  = np.dot(np.transpose(R), np.dot(A, R))
-#    rpy_gt[i-delta,:] = ru.dcm2rpy(B)
-#    rpy_es[i-delta,:] = ru.dcm2rpy(B_es)
-#    t_B = np.dot(np.transpose(B1),(p_gt[i,:]-p_gt[i-delta,:]))
-#    t_A = np.dot(np.transpose(A1),(p_es[i,:]-p_es[i-delta,:]))
-#    t_gt[i-delta,:] = t_B
-#    t_es[i-delta,:] = np.dot(np.transpose(R), np.dot(A,b[:,0]) + t_A - b[:,0])
-#  alignment_error = (t_gt-t_es)
-#  error = np.sqrt(np.sum(np.multiply(alignment_error,alignment_error),1))
-#
-#  if display:
-#    plt.figure()
-#    plt.plot(rpy_es[:,0], 'r-', label='es roll')
-#    plt.plot(rpy_es[:,1], 'g-', label='es pitch')
-#    plt.plot(rpy_es[:,2], 'b-', label='es yaw')
-#    plt.plot(rpy_gt[:,0], 'r--', label='gt roll')
-#    plt.plot(rpy_gt[:,1], 'g--', label='gt pitch')
-#    plt.plot(rpy_gt[:,2], 'b--', label='gt yaw')
-#    plt.legend()
-#    plt.figure()
-#    plt.plot(t_gt[:,0], 'r-', label='es x')
-#    plt.plot(t_gt[:,1], 'g-', label='es y')
-#    plt.plot(t_gt[:,2], 'b-', label='es z')
-#    plt.plot(t_es[:,0], 'r--', label='gt x')
-#    plt.plot(t_es[:,1], 'g--', label='gt y')
-#    plt.plot(t_es[:,2], 'b--', label='gt z')
-#    plt.legend()
-#    plt.figure()
-#    plt.plot(error,'-g')
-#
-#  print 'e_rms = ' + str(np.sqrt(np.dot(error,error) / len(error)))
-#  print 'e_mean = ' + str(np.mean(error))
-#  print 'e_median = ' + str(np.median(error))
-#  print 'e_std = ' + str(np.std(error))
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
diff --git a/CPU_version/svo_analysis/src/svo_analysis/tum_benchmark_tools/__init__.py b/CPU_version/svo_analysis/src/svo_analysis/tum_benchmark_tools/__init__.py
deleted file mode 100644
index 633f866..0000000
--- a/CPU_version/svo_analysis/src/svo_analysis/tum_benchmark_tools/__init__.py
+++ /dev/null
@@ -1,2 +0,0 @@
-# -*- coding: utf-8 -*-
-
diff --git a/CPU_version/svo_analysis/src/svo_analysis/tum_benchmark_tools/associate.py b/CPU_version/svo_analysis/src/svo_analysis/tum_benchmark_tools/associate.py
deleted file mode 100755
index 361cdd5..0000000
--- a/CPU_version/svo_analysis/src/svo_analysis/tum_benchmark_tools/associate.py
+++ /dev/null
@@ -1,130 +0,0 @@
-#!/usr/bin/python
-# Software License Agreement (BSD License)
-#
-# Copyright (c) 2013, Juergen Sturm, TUM
-# All rights reserved.
-#
-# Redistribution and use in source and binary forms, with or without
-# modification, are permitted provided that the following conditions
-# are met:
-#
-#  * Redistributions of source code must retain the above copyright
-#    notice, this list of conditions and the following disclaimer.
-#  * Redistributions in binary form must reproduce the above
-#    copyright notice, this list of conditions and the following
-#    disclaimer in the documentation and/or other materials provided
-#    with the distribution.
-#  * Neither the name of TUM nor the names of its
-#    contributors may be used to endorse or promote products derived
-#    from this software without specific prior written permission.
-#
-# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
-# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
-# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
-# FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
-# COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
-# INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
-# BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
-# LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
-# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
-# LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
-# ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
-# POSSIBILITY OF SUCH DAMAGE.
-#
-# Requirements: 
-# sudo apt-get install python-argparse
-
-"""
-The Kinect provides the color and depth images in an un-synchronized way. This means that the set of time stamps from the color images do not intersect with those of the depth images. Therefore, we need some way of associating color images to depth images.
-
-For this purpose, you can use the ''associate.py'' script. It reads the time stamps from the rgb.txt file and the depth.txt file, and joins them by finding the best matches.
-"""
-
-import argparse
-import sys
-import os
-import numpy
-
-
-def read_file_list(filename):
-    """
-    Reads a trajectory from a text file. 
-    
-    File format:
-    The file format is "stamp d1 d2 d3 ...", where stamp denotes the time stamp (to be matched)
-    and "d1 d2 d3.." is arbitary data (e.g., a 3D position and 3D orientation) associated to this timestamp. 
-    
-    Input:
-    filename -- File name
-    
-    Output:
-    dict -- dictionary of (stamp,data) tuples
-    
-    """
-    file = open(filename)
-    data = file.read()
-    lines = data.replace(","," ").replace("\t"," ").split("\n") 
-    list = [[v.strip() for v in line.split(" ") if v.strip()!=""] for line in lines if len(line)>0 and line[0]!="#"]
-    list = [(float(l[0]),l[1:]) for l in list if len(l)>1]
-    return dict(list)
-
-def associate(first_list, second_list,offset,max_difference):
-    """
-    Associate two dictionaries of (stamp,data). As the time stamps never match exactly, we aim 
-    to find the closest match for every input tuple.
-    
-    Input:
-    first_list -- first dictionary of (stamp,data) tuples
-    second_list -- second dictionary of (stamp,data) tuples
-    offset -- time offset between both dictionaries (e.g., to model the delay between the sensors)
-    max_difference -- search radius for candidate generation
-
-    Output:
-    matches -- list of matched tuples ((stamp1,data1),(stamp2,data2))
-    
-    """
-    first_keys = first_list.keys()
-    second_keys = second_list.keys()
-    potential_matches = [(abs(a - (b + offset)), a, b) 
-                         for a in first_keys 
-                         for b in second_keys 
-                         if abs(a - (b + offset)) < max_difference]
-    potential_matches.sort()
-    matches = []
-    for diff, a, b in potential_matches:
-        if a in first_keys and b in second_keys:
-            first_keys.remove(a)
-            second_keys.remove(b)
-            matches.append((a, b))
-    
-    matches.sort()
-    return matches
-
-if __name__ == '__main__':
-    
-    # parse command line
-    parser = argparse.ArgumentParser(description='''
-    This script takes two data files with timestamps and associates them   
-    ''')
-    parser.add_argument('first_file', help='estimated trajectory (format: timestamp data)')
-    parser.add_argument('second_file', help='groundtruth (format: timestamp data)')
-    parser.add_argument('--offset', help='time offset added to the timestamps of the second file (default: 0.0)',default=0.0)
-    parser.add_argument('--max_difference', help='maximally allowed time difference for matching entries (default: 0.02)',default=0.02)
-    args = parser.parse_args()
-
-    first_list = read_file_list(args.first_file)
-    second_list = read_file_list(args.second_file)
-
-    matches = associate(first_list, second_list,float(args.offset),float(args.max_difference))    
-    
-    filename = 'groundtruth_matched.txt' 
-    associates_file = open(filename, 'w')                             
-    for a,b in matches:
-      img = first_list[a]
-      pos = second_list[b]
-      associates_file.write('%.6f %s %s %s %s %s %s %s %s\n' %
-                           (a, img[0],
-                            pos[0], pos[1], pos[2],
-                            pos[3], pos[4], pos[5], pos[6])) 
-    print('Wrote matches to file: ' + filename)
-        
diff --git a/CPU_version/svo_analysis/src/svo_analysis/tum_benchmark_tools/evaluate_ate.py b/CPU_version/svo_analysis/src/svo_analysis/tum_benchmark_tools/evaluate_ate.py
deleted file mode 100755
index a8b2ca9..0000000
--- a/CPU_version/svo_analysis/src/svo_analysis/tum_benchmark_tools/evaluate_ate.py
+++ /dev/null
@@ -1,194 +0,0 @@
-#!/usr/bin/python
-# Software License Agreement (BSD License)
-#
-# Copyright (c) 2013, Juergen Sturm, TUM
-# All rights reserved.
-#
-# Redistribution and use in source and binary forms, with or without
-# modification, are permitted provided that the following conditions
-# are met:
-#
-#  * Redistributions of source code must retain the above copyright
-#    notice, this list of conditions and the following disclaimer.
-#  * Redistributions in binary form must reproduce the above
-#    copyright notice, this list of conditions and the following
-#    disclaimer in the documentation and/or other materials provided
-#    with the distribution.
-#  * Neither the name of TUM nor the names of its
-#    contributors may be used to endorse or promote products derived
-#    from this software without specific prior written permission.
-#
-# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
-# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
-# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
-# FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
-# COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
-# INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
-# BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
-# LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
-# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
-# LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
-# ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
-# POSSIBILITY OF SUCH DAMAGE.
-#
-# Requirements: 
-# sudo apt-get install python-argparse
-
-"""
-This script computes the absolute trajectory error from the ground truth
-trajectory and the estimated trajectory.
-"""
-
-import sys
-import numpy
-import argparse
-import associate
-
-def align(model,data):
-    """Align two trajectories using the method of Horn (closed-form).
-    
-    Input:
-    model -- first trajectory (3xn)
-    data -- second trajectory (3xn)
-    
-    Output:
-    rot -- rotation matrix (3x3)
-    trans -- translation vector (3x1)
-    trans_error -- translational error per point (1xn)
-    
-    """
-    numpy.set_printoptions(precision=3,suppress=True)
-    model_zerocentered = model - model.mean(1)
-    data_zerocentered = data - data.mean(1)
-    
-    W = numpy.zeros( (3,3) )
-    for column in range(model.shape[1]):
-        W += numpy.outer(model_zerocentered[:,column],data_zerocentered[:,column])
-    U,d,Vh = numpy.linalg.linalg.svd(W.transpose())
-    S = numpy.matrix(numpy.identity( 3 ))
-    if(numpy.linalg.det(U) * numpy.linalg.det(Vh)<0):
-        S[2,2] = -1
-    rot = U*S*Vh
-    trans = data.mean(1) - rot * model.mean(1)
-    
-    model_aligned = rot * model + trans
-    alignment_error = model_aligned - data
-    
-    trans_error = numpy.sqrt(numpy.sum(numpy.multiply(alignment_error,alignment_error),0)).A[0]
-        
-    return rot,trans,trans_error
-
-def plot_traj(ax,stamps,traj,style,color,label):
-    """
-    Plot a trajectory using matplotlib. 
-    
-    Input:
-    ax -- the plot
-    stamps -- time stamps (1xn)
-    traj -- trajectory (3xn)
-    style -- line style
-    color -- line color
-    label -- plot legend
-    
-    """
-    stamps.sort()
-    interval = numpy.median([s-t for s,t in zip(stamps[1:],stamps[:-1])])
-    x = []
-    y = []
-    last = stamps[0]
-    for i in range(len(stamps)):
-        if stamps[i]-last < 2*interval:
-            x.append(traj[i][0])
-            y.append(traj[i][1])
-        elif len(x)>0:
-            ax.plot(x,y,style,color=color,label=label)
-            label=""
-            x=[]
-            y=[]
-        last= stamps[i]
-    if len(x)>0:
-        ax.plot(x,y,style,color=color,label=label)
-            
-
-if __name__=="__main__":
-    # parse command line
-    parser = argparse.ArgumentParser(description='''
-    This script computes the absolute trajectory error from the ground truth trajectory and the estimated trajectory. 
-    ''')
-    parser.add_argument('first_file', help='ground truth trajectory (format: timestamp tx ty tz qx qy qz qw)')
-    parser.add_argument('second_file', help='estimated trajectory (format: timestamp tx ty tz qx qy qz qw)')
-    parser.add_argument('--offset', help='time offset added to the timestamps of the second file (default: 0.0)',default=0.0)
-    parser.add_argument('--scale', help='scaling factor for the second trajectory (default: 1.0)',default=1.0)
-    parser.add_argument('--max_difference', help='maximally allowed time difference for matching entries (default: 0.02)',default=0.02)
-    parser.add_argument('--save', help='save aligned second trajectory to disk (format: stamp2 x2 y2 z2)')
-    parser.add_argument('--save_associations', help='save associated first and aligned second trajectory to disk (format: stamp1 x1 y1 z1 stamp2 x2 y2 z2)')
-    parser.add_argument('--plot', help='plot the first and the aligned second trajectory to an image (format: png)')
-    parser.add_argument('--verbose', help='print all evaluation data (otherwise, only the RMSE absolute translational error in meters after alignment will be printed)', action='store_true')
-    args = parser.parse_args()
-
-    first_list = associate.read_file_list(args.first_file)
-    second_list = associate.read_file_list(args.second_file)
-
-    matches = associate.associate(first_list, second_list, float(args.offset), float(args.max_difference))
-    if len(matches)<2:
-        sys.exit("Couldn't find matching timestamp pairs between groundtruth and estimated trajectory! Did you choose the correct sequence?")
-
-
-    first_xyz = numpy.matrix([[float(value) for value in first_list[a][0:3]] for a,b in matches]).transpose()
-    second_xyz = numpy.matrix([[float(value)*float(args.scale) for value in second_list[b][0:3]] for a,b in matches]).transpose()
-    rot,trans,trans_error = align(second_xyz,first_xyz)
-    
-    second_xyz_aligned = rot * second_xyz + trans
-    
-    first_stamps = first_list.keys()
-    first_stamps.sort()
-    first_xyz_full = numpy.matrix([[float(value) for value in first_list[b][0:3]] for b in first_stamps]).transpose()
-    
-    second_stamps = second_list.keys()
-    second_stamps.sort()
-    second_xyz_full = numpy.matrix([[float(value)*float(args.scale) for value in second_list[b][0:3]] for b in second_stamps]).transpose()
-    second_xyz_full_aligned = rot * second_xyz_full + trans
-    
-    if args.verbose:
-        print "compared_pose_pairs %d pairs"%(len(trans_error))
-
-        print "absolute_translational_error.rmse %f m"%numpy.sqrt(numpy.dot(trans_error,trans_error) / len(trans_error))
-        print "absolute_translational_error.mean %f m"%numpy.mean(trans_error)
-        print "absolute_translational_error.median %f m"%numpy.median(trans_error)
-        print "absolute_translational_error.std %f m"%numpy.std(trans_error)
-        print "absolute_translational_error.min %f m"%numpy.min(trans_error)
-        print "absolute_translational_error.max %f m"%numpy.max(trans_error)
-    else:
-        print "%f"%numpy.sqrt(numpy.dot(trans_error,trans_error) / len(trans_error))
-        
-    if args.save_associations:
-        file = open(args.save_associations,"w")
-        file.write("\n".join(["%f %f %f %f %f %f %f %f"%(a,x1,y1,z1,b,x2,y2,z2) for (a,b),(x1,y1,z1),(x2,y2,z2) in zip(matches,first_xyz.transpose().A,second_xyz_aligned.transpose().A)]))
-        file.close()
-        
-    if args.save:
-        file = open(args.save,"w")
-        file.write("\n".join(["%f "%stamp+" ".join(["%f"%d for d in line]) for stamp,line in zip(second_stamps,second_xyz_full_aligned.transpose().A)]))
-        file.close()
-
-    if args.plot:
-        import matplotlib
-        matplotlib.use('Agg')
-        import matplotlib.pyplot as plt
-
-        fig = plt.figure()
-        ax = fig.add_subplot(111)
-        plot_traj(ax,first_stamps,first_xyz_full.transpose().A,'-',"black","ground truth")
-        plot_traj(ax,second_stamps,second_xyz_full_aligned.transpose().A,'-',"blue","estimated")
-
-        label="difference"
-        for (a,b),(x1,y1,z1),(x2,y2,z2) in zip(matches,first_xyz.transpose().A,second_xyz_aligned.transpose().A):
-            ax.plot([x1,x2],[y1,y2],'-',color="red",label=label)
-            label=""
-            
-        ax.legend()
-            
-        ax.set_xlabel('x [m]')
-        ax.set_ylabel('y [m]')
-        plt.savefig(args.plot,dpi=90)
-        
diff --git a/CPU_version/svo_analysis/src/svo_analysis/tum_benchmark_tools/evaluate_rpe.py b/CPU_version/svo_analysis/src/svo_analysis/tum_benchmark_tools/evaluate_rpe.py
deleted file mode 100755
index fb42e4a..0000000
--- a/CPU_version/svo_analysis/src/svo_analysis/tum_benchmark_tools/evaluate_rpe.py
+++ /dev/null
@@ -1,382 +0,0 @@
-#!/usr/bin/python
-# Software License Agreement (BSD License)
-#
-# Copyright (c) 2013, Juergen Sturm, TUM
-# All rights reserved.
-#
-# Redistribution and use in source and binary forms, with or without
-# modification, are permitted provided that the following conditions
-# are met:
-#
-#  * Redistributions of source code must retain the above copyright
-#    notice, this list of conditions and the following disclaimer.
-#  * Redistributions in binary form must reproduce the above
-#    copyright notice, this list of conditions and the following
-#    disclaimer in the documentation and/or other materials provided
-#    with the distribution.
-#  * Neither the name of TUM nor the names of its
-#    contributors may be used to endorse or promote products derived
-#    from this software without specific prior written permission.
-#
-# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
-# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
-# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
-# FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
-# COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
-# INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
-# BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
-# LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
-# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
-# LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
-# ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
-# POSSIBILITY OF SUCH DAMAGE.
-
-"""
-This script computes the relative pose error from the ground truth trajectory
-and the estimated trajectory.
-"""
-
-import argparse
-import random
-import numpy
-import sys
-
-_EPS = numpy.finfo(float).eps * 4.0
-
-def transform44(l):
-    """
-    Generate a 4x4 homogeneous transformation matrix from a 3D point and unit quaternion.
-    
-    Input:
-    l -- tuple consisting of (stamp,tx,ty,tz,qx,qy,qz,qw) where
-         (tx,ty,tz) is the 3D position and (qx,qy,qz,qw) is the unit quaternion.
-         
-    Output:
-    matrix -- 4x4 homogeneous transformation matrix
-    """
-    t = l[1:4]
-    q = numpy.array(l[4:8], dtype=numpy.float64, copy=True)
-    nq = numpy.dot(q, q)
-    if nq < _EPS:
-        return numpy.array((
-        (                1.0,                 0.0,                 0.0, t[0])
-        (                0.0,                 1.0,                 0.0, t[1])
-        (                0.0,                 0.0,                 1.0, t[2])
-        (                0.0,                 0.0,                 0.0, 1.0)
-        ), dtype=numpy.float64)
-    q *= numpy.sqrt(2.0 / nq)
-    q = numpy.outer(q, q)
-    return numpy.array((
-        (1.0-q[1, 1]-q[2, 2],     q[0, 1]-q[2, 3],     q[0, 2]+q[1, 3], t[0]),
-        (    q[0, 1]+q[2, 3], 1.0-q[0, 0]-q[2, 2],     q[1, 2]-q[0, 3], t[1]),
-        (    q[0, 2]-q[1, 3],     q[1, 2]+q[0, 3], 1.0-q[0, 0]-q[1, 1], t[2]),
-        (                0.0,                 0.0,                 0.0, 1.0)
-        ), dtype=numpy.float64)
-
-def read_trajectory(filename, matrix=True):
-    """
-    Read a trajectory from a text file. 
-    
-    Input:
-    filename -- file to be read
-    matrix -- convert poses to 4x4 matrices
-    
-    Output:
-    dictionary of stamped 3D poses
-    """
-    file = open(filename)
-    data = file.read()
-    lines = data.replace(","," ").replace("\t"," ").split("\n") 
-    list = [[float(v.strip()) for v in line.split(" ") if v.strip()!=""] for line in lines if len(line)>0 and line[0]!="#"]
-    list_ok = []
-    for i,l in enumerate(list):
-        if l[4:8]==[0,0,0,0]:
-            continue
-        isnan = False
-        for v in l:
-            if numpy.isnan(v): 
-                isnan = True
-                break
-        if isnan:
-            sys.stderr.write("Warning: line %d of file '%s' has NaNs, skipping line\n"%(i,filename))
-            continue
-        list_ok.append(l)
-    if matrix :
-      traj = dict([(l[0],transform44(l[0:])) for l in list_ok])
-    else:
-      traj = dict([(l[0],l[1:8]) for l in list_ok])
-    return traj
-
-def find_closest_index(L,t):
-    """
-    Find the index of the closest value in a list.
-    
-    Input:
-    L -- the list
-    t -- value to be found
-    
-    Output:
-    index of the closest element
-    """
-    beginning = 0
-    difference = abs(L[0] - t)
-    best = 0
-    end = len(L)
-    while beginning < end:
-        middle = int((end+beginning)/2)
-        if abs(L[middle] - t) < difference:
-            difference = abs(L[middle] - t)
-            best = middle
-        if t == L[middle]:
-            return middle
-        elif L[middle] > t:
-            end = middle
-        else:
-            beginning = middle + 1
-    return best
-
-def ominus(a,b):
-    """
-    Compute the relative 3D transformation between a and b.
-    
-    Input:
-    a -- first pose (homogeneous 4x4 matrix)
-    b -- second pose (homogeneous 4x4 matrix)
-    
-    Output:
-    Relative 3D transformation from a to b.
-    """
-    return numpy.dot(numpy.linalg.inv(a),b)
-
-def scale(a,scalar):
-    """
-    Scale the translational components of a 4x4 homogeneous matrix by a scale factor.
-    """
-    return numpy.array(
-        [[a[0,0], a[0,1], a[0,2], a[0,3]*scalar],
-         [a[1,0], a[1,1], a[1,2], a[1,3]*scalar],
-         [a[2,0], a[2,1], a[2,2], a[2,3]*scalar],
-         [a[3,0], a[3,1], a[3,2], a[3,3]]]
-                       )
-
-def compute_distance(transform):
-    """
-    Compute the distance of the translational component of a 4x4 homogeneous matrix.
-    """
-    return numpy.linalg.norm(transform[0:3,3])
-
-def compute_angle(transform):
-    """
-    Compute the rotation angle from a 4x4 homogeneous matrix.
-    """
-    # an invitation to 3-d vision, p 27
-    return numpy.arccos( min(1,max(-1, (numpy.trace(transform[0:3,0:3]) - 1)/2) ))
-
-def distances_along_trajectory(traj):
-    """
-    Compute the translational distances along a trajectory. 
-    """
-    keys = traj.keys()
-    keys.sort()
-    motion = [ominus(traj[keys[i+1]],traj[keys[i]]) for i in range(len(keys)-1)]
-    distances = [0]
-    sum = 0
-    for t in motion:
-        sum += compute_distance(t)
-        distances.append(sum)
-    return distances
-    
-def rotations_along_trajectory(traj,scale):
-    """
-    Compute the angular rotations along a trajectory. 
-    """
-    keys = traj.keys()
-    keys.sort()
-    motion = [ominus(traj[keys[i+1]],traj[keys[i]]) for i in range(len(keys)-1)]
-    distances = [0]
-    sum = 0
-    for t in motion:
-        sum += compute_angle(t)*scale
-        distances.append(sum)
-    return distances
-    
-
-def evaluate_trajectory(traj_gt,traj_est,param_max_pairs=10000,param_fixed_delta=False,param_delta=1.00,param_delta_unit="s",param_offset=0.00,param_scale=1.00):
-    """
-    Compute the relative pose error between two trajectories.
-    
-    Input:
-    traj_gt -- the first trajectory (ground truth)
-    traj_est -- the second trajectory (estimated trajectory)
-    param_max_pairs -- number of relative poses to be evaluated
-    param_fixed_delta -- false: evaluate over all possible pairs
-                         true: only evaluate over pairs with a given distance (delta)
-    param_delta -- distance between the evaluated pairs
-    param_delta_unit -- unit for comparison:
-                        "s": seconds
-                        "m": meters
-                        "rad": radians
-                        "deg": degrees
-                        "f": frames
-    param_offset -- time offset between two trajectories (to model the delay)
-    param_scale -- scale to be applied to the second trajectory
-    
-    Output:
-    list of compared poses and the resulting translation and rotation error
-    """
-    stamps_gt = list(traj_gt.keys())
-    stamps_est = list(traj_est.keys())
-    stamps_gt.sort()
-    stamps_est.sort()
-    
-    stamps_est_return = []
-    for t_est in stamps_est:
-        t_gt = stamps_gt[find_closest_index(stamps_gt,t_est + param_offset)]
-        t_est_return = stamps_est[find_closest_index(stamps_est,t_gt - param_offset)]
-        t_gt_return = stamps_gt[find_closest_index(stamps_gt,t_est_return + param_offset)]
-        if not t_est_return in stamps_est_return:
-            stamps_est_return.append(t_est_return)
-    if(len(stamps_est_return)<2):
-        raise Exception("Number of overlap in the timestamps is too small. Did you run the evaluation on the right files?")
-
-    if param_delta_unit=="s":
-        index_est = list(traj_est.keys())
-        index_est.sort()
-    elif param_delta_unit=="m":
-        index_est = distances_along_trajectory(traj_est)
-    elif param_delta_unit=="rad":
-        index_est = rotations_along_trajectory(traj_est,1)
-    elif param_delta_unit=="deg":
-        index_est = rotations_along_trajectory(traj_est,180/numpy.pi)
-    elif param_delta_unit=="f":
-        index_est = range(len(traj_est))
-    else:
-        raise Exception("Unknown unit for delta: '%s'"%param_delta_unit)
-
-    if not param_fixed_delta:
-        if(param_max_pairs==0 or len(traj_est)<numpy.sqrt(param_max_pairs)):
-            pairs = [(i,j) for i in range(len(traj_est)) for j in range(len(traj_est))]
-        else:
-            pairs = [(random.randint(0,len(traj_est)-1),random.randint(0,len(traj_est)-1)) for i in range(param_max_pairs)]
-    else:
-        pairs = []
-        for i in range(len(traj_est)):
-            j = find_closest_index(index_est,index_est[i] + param_delta)
-            if j!=len(traj_est)-1: 
-                pairs.append((i,j))
-        if(param_max_pairs!=0 and len(pairs)>param_max_pairs):
-            pairs = random.sample(pairs,param_max_pairs)
-    
-    gt_interval = numpy.median([s-t for s,t in zip(stamps_gt[1:],stamps_gt[:-1])])
-    gt_max_time_difference = 2*gt_interval
-    
-    result = []
-    for i,j in pairs:
-        stamp_est_0 = stamps_est[i]
-        stamp_est_1 = stamps_est[j]
-
-        stamp_gt_0 = stamps_gt[ find_closest_index(stamps_gt,stamp_est_0 + param_offset) ]
-        stamp_gt_1 = stamps_gt[ find_closest_index(stamps_gt,stamp_est_1 + param_offset) ]
-        
-        if(abs(stamp_gt_0 - (stamp_est_0 + param_offset)) > gt_max_time_difference  or
-           abs(stamp_gt_1 - (stamp_est_1 + param_offset)) > gt_max_time_difference):
-            continue
-        
-        error44 = ominus(  scale(
-                           ominus( traj_est[stamp_est_1], traj_est[stamp_est_0] ),param_scale),
-                           ominus( traj_gt[stamp_gt_1], traj_gt[stamp_gt_0] ) )
-        
-        trans = compute_distance(error44)
-        rot = compute_angle(error44)
-        
-        result.append([stamp_est_0,stamp_est_1,stamp_gt_0,stamp_gt_1,trans,rot])
-        
-    if len(result)<2:
-        raise Exception("Couldn't find matching timestamp pairs between groundtruth and estimated trajectory!")
-        
-    return result
-
-def percentile(seq,q):
-    """
-    Return the q-percentile of a list
-    """
-    seq_sorted = list(seq)
-    seq_sorted.sort()
-    return seq_sorted[int((len(seq_sorted)-1)*q)]
-
-if __name__ == '__main__':
-    random.seed(0)
-
-    parser = argparse.ArgumentParser(description='''
-    This script computes the relative pose error from the ground truth trajectory and the estimated trajectory. 
-    ''')
-    parser.add_argument('groundtruth_file', help='ground-truth trajectory file (format: "timestamp tx ty tz qx qy qz qw")')
-    parser.add_argument('estimated_file', help='estimated trajectory file (format: "timestamp tx ty tz qx qy qz qw")')
-    parser.add_argument('--max_pairs', help='maximum number of pose comparisons (default: 10000, set to zero to disable downsampling)', default=10000)
-    parser.add_argument('--fixed_delta', help='only consider pose pairs that have a distance of delta delta_unit (e.g., for evaluating the drift per second/meter/radian)', action='store_true')
-    parser.add_argument('--delta', help='delta for evaluation (default: 1.0)',default=1.0)
-    parser.add_argument('--delta_unit', help='unit of delta (options: \'s\' for seconds, \'m\' for meters, \'rad\' for radians, \'f\' for frames; default: \'s\')',default='s')
-    parser.add_argument('--offset', help='time offset between ground-truth and estimated trajectory (default: 0.0)',default=0.0)
-    parser.add_argument('--scale', help='scaling factor for the estimated trajectory (default: 1.0)',default=1.0)
-    parser.add_argument('--save', help='text file to which the evaluation will be saved (format: stamp_est0 stamp_est1 stamp_gt0 stamp_gt1 trans_error rot_error)')
-    parser.add_argument('--plot', help='plot the result to a file (requires --fixed_delta, output format: png)')
-    parser.add_argument('--verbose', help='print all evaluation data (otherwise, only the mean translational error measured in meters will be printed)', action='store_true')
-    args = parser.parse_args()
-    
-    if args.plot and not args.fixed_delta:
-        sys.exit("The '--plot' option can only be used in combination with '--fixed_delta'")
-    
-    traj_gt = read_trajectory(args.groundtruth_file)
-    traj_est = read_trajectory(args.estimated_file)
-    
-    result = evaluate_trajectory(traj_gt,
-                                 traj_est,
-                                 int(args.max_pairs),
-                                 args.fixed_delta,
-                                 float(args.delta),
-                                 args.delta_unit,
-                                 float(args.offset),
-                                 float(args.scale))
-    
-    stamps = numpy.array(result)[:,0]
-    trans_error = numpy.array(result)[:,4]
-    rot_error = numpy.array(result)[:,5]
-    
-    if args.save:
-        f = open(args.save,"w")
-        f.write("\n".join([" ".join(["%f"%v for v in line]) for line in result]))
-        f.close()
-    
-    if args.verbose:
-        print "compared_pose_pairs %d pairs"%(len(trans_error))
-
-        print "translational_error.rmse %f m"%numpy.sqrt(numpy.dot(trans_error,trans_error) / len(trans_error))
-        print "translational_error.mean %f m"%numpy.mean(trans_error)
-        print "translational_error.median %f m"%numpy.median(trans_error)
-        print "translational_error.std %f m"%numpy.std(trans_error)
-        print "translational_error.min %f m"%numpy.min(trans_error)
-        print "translational_error.max %f m"%numpy.max(trans_error)
-
-        print "rotational_error.rmse %f deg"%(numpy.sqrt(numpy.dot(rot_error,rot_error) / len(rot_error)) * 180.0 / numpy.pi)
-        print "rotational_error.mean %f deg"%(numpy.mean(rot_error) * 180.0 / numpy.pi)
-        print "rotational_error.median %f deg"%numpy.median(rot_error)
-        print "rotational_error.std %f deg"%(numpy.std(rot_error) * 180.0 / numpy.pi)
-        print "rotational_error.min %f deg"%(numpy.min(rot_error) * 180.0 / numpy.pi)
-        print "rotational_error.max %f deg"%(numpy.max(rot_error) * 180.0 / numpy.pi)
-    else:
-        print numpy.mean(trans_error)
-
-    if args.plot:    
-        import matplotlib
-        matplotlib.use('Agg')
-        import matplotlib.pyplot as plt
-        import matplotlib.pylab as pylab
-        fig = plt.figure()
-        ax = fig.add_subplot(111)        
-        ax.plot(stamps - stamps[0],trans_error,'-',color="blue")
-        #ax.plot([t for t,e in err_rot],[e for t,e in err_rot],'-',color="red")
-        ax.set_xlabel('time [s]')
-        ax.set_ylabel('translational error [m]')
-        plt.savefig(args.plot,dpi=300)
-        
-
diff --git a/CPU_version/svo_msgs/.idea/.gitignore b/CPU_version/svo_msgs/.idea/.gitignore
deleted file mode 100644
index 73f69e0..0000000
--- a/CPU_version/svo_msgs/.idea/.gitignore
+++ /dev/null
@@ -1,8 +0,0 @@
-# Default ignored files
-/shelf/
-/workspace.xml
-# Datasource local storage ignored files
-/dataSources/
-/dataSources.local.xml
-# Editor-based HTTP Client requests
-/httpRequests/
diff --git a/CPU_version/svo_msgs/.idea/misc.xml b/CPU_version/svo_msgs/.idea/misc.xml
deleted file mode 100644
index 79b3c94..0000000
--- a/CPU_version/svo_msgs/.idea/misc.xml
+++ /dev/null
@@ -1,4 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="CMakeWorkspace" PROJECT_DIR="$PROJECT_DIR$" />
-</project>
\ No newline at end of file
diff --git a/CPU_version/svo_msgs/.idea/modules.xml b/CPU_version/svo_msgs/.idea/modules.xml
deleted file mode 100644
index 668cc83..0000000
--- a/CPU_version/svo_msgs/.idea/modules.xml
+++ /dev/null
@@ -1,8 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="ProjectModuleManager">
-    <modules>
-      <module fileurl="file://$PROJECT_DIR$/.idea/svo_msgs.iml" filepath="$PROJECT_DIR$/.idea/svo_msgs.iml" />
-    </modules>
-  </component>
-</project>
\ No newline at end of file
diff --git a/CPU_version/svo_msgs/.idea/svo_msgs.iml b/CPU_version/svo_msgs/.idea/svo_msgs.iml
deleted file mode 100644
index f08604b..0000000
--- a/CPU_version/svo_msgs/.idea/svo_msgs.iml
+++ /dev/null
@@ -1,2 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<module classpath="CMake" type="CPP_MODULE" version="4" />
\ No newline at end of file
diff --git a/CPU_version/svo_msgs/.idea/vcs.xml b/CPU_version/svo_msgs/.idea/vcs.xml
deleted file mode 100644
index 6c0b863..0000000
--- a/CPU_version/svo_msgs/.idea/vcs.xml
+++ /dev/null
@@ -1,6 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="VcsDirectoryMappings">
-    <mapping directory="$PROJECT_DIR$/.." vcs="Git" />
-  </component>
-</project>
\ No newline at end of file
diff --git a/CPU_version/svo_msgs/CMakeLists.txt b/CPU_version/svo_msgs/CMakeLists.txt
deleted file mode 100644
index 6d1a371..0000000
--- a/CPU_version/svo_msgs/CMakeLists.txt
+++ /dev/null
@@ -1,33 +0,0 @@
-cmake_minimum_required(VERSION 2.8.3)
-project(svo_msgs)
-
-# search for everything we need to build the messages, dont forget the message_generation
-find_package(catkin REQUIRED COMPONENTS
-  message_generation
-  geometry_msgs
-  sensor_msgs
-)
-
-
-
-# notify catkin to look at the previously found msg files
-add_message_files(
-  FILES
-  Info.msg
-)
-
-# build the header files from the msg files, and notify catkin about the dependencies
-generate_messages(
-  DEPENDENCIES
-  geometry_msgs
-  sensor_msgs
-)
-
-# export the dependencis of this package for who ever depends on us
-catkin_package(
-  CATKIN_DEPENDS message_runtime geometry_msgs
-)
-
-include_directories(
-  ${catkin_INCLUDE_DIRS}
-)
\ No newline at end of file
diff --git a/CPU_version/svo_msgs/msg/DenseInput.msg b/CPU_version/svo_msgs/msg/DenseInput.msg
deleted file mode 100644
index d36dee8..0000000
--- a/CPU_version/svo_msgs/msg/DenseInput.msg
+++ /dev/null
@@ -1,6 +0,0 @@
-Header header
-uint32 frame_id
-geometry_msgs/Pose pose
-sensor_msgs/Image image
-float32 min_depth
-float32 max_depth
\ No newline at end of file
diff --git a/CPU_version/svo_msgs/msg/Feature.msg b/CPU_version/svo_msgs/msg/Feature.msg
deleted file mode 100644
index 2972c32..0000000
--- a/CPU_version/svo_msgs/msg/Feature.msg
+++ /dev/null
@@ -1,5 +0,0 @@
-float32 u
-float32 v
-float32 x
-float32 y
-float32 z
\ No newline at end of file
diff --git a/CPU_version/svo_msgs/msg/Info.msg b/CPU_version/svo_msgs/msg/Info.msg
deleted file mode 100644
index b962e1b..0000000
--- a/CPU_version/svo_msgs/msg/Info.msg
+++ /dev/null
@@ -1,6 +0,0 @@
-Header      header
-float32     processing_time
-int32[]     keyframes
-int32       num_matches
-int32       tracking_quality
-int32       stage
\ No newline at end of file
diff --git a/CPU_version/svo_msgs/msg/NbvTrajectory.msg b/CPU_version/svo_msgs/msg/NbvTrajectory.msg
deleted file mode 100644
index 03f0792..0000000
--- a/CPU_version/svo_msgs/msg/NbvTrajectory.msg
+++ /dev/null
@@ -1,2 +0,0 @@
-Header header
-geometry_msgs/Pose[] trajectory
\ No newline at end of file
diff --git a/CPU_version/svo_msgs/package.xml b/CPU_version/svo_msgs/package.xml
deleted file mode 100644
index b122e2d..0000000
--- a/CPU_version/svo_msgs/package.xml
+++ /dev/null
@@ -1,19 +0,0 @@
-<?xml version="1.0"?>
-<package>
-  <name>svo_msgs</name>
-  <version>0.0.0</version>
-  <description>Custom messages for svo</description>
-  <maintainer email="forster@ifi.uzh.ch">Christian Forster</maintainer>
-  <license>BSD</license>
-  <buildtool_depend>catkin</buildtool_depend>
-
-  <build_depend>message_generation</build_depend>
-  <build_depend>geometry_msgs</build_depend>
-  <build_depend>sensor_msgs</build_depend>
-  
-  <run_depend>message_runtime</run_depend>
-  <run_depend>geometry_msgs</run_depend>
-  <run_depend>sensor_msgs</run_depend>
-
-  <export></export>
-</package>
\ No newline at end of file
diff --git a/CPU_version/vio_svo/.idea/.gitignore b/CPU_version/vio_svo/.idea/.gitignore
deleted file mode 100644
index 73f69e0..0000000
--- a/CPU_version/vio_svo/.idea/.gitignore
+++ /dev/null
@@ -1,8 +0,0 @@
-# Default ignored files
-/shelf/
-/workspace.xml
-# Datasource local storage ignored files
-/dataSources/
-/dataSources.local.xml
-# Editor-based HTTP Client requests
-/httpRequests/
diff --git a/CPU_version/vio_svo/.idea/misc.xml b/CPU_version/vio_svo/.idea/misc.xml
deleted file mode 100644
index 79b3c94..0000000
--- a/CPU_version/vio_svo/.idea/misc.xml
+++ /dev/null
@@ -1,4 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="CMakeWorkspace" PROJECT_DIR="$PROJECT_DIR$" />
-</project>
\ No newline at end of file
diff --git a/CPU_version/vio_svo/.idea/modules.xml b/CPU_version/vio_svo/.idea/modules.xml
deleted file mode 100644
index eb3cacf..0000000
--- a/CPU_version/vio_svo/.idea/modules.xml
+++ /dev/null
@@ -1,8 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="ProjectModuleManager">
-    <modules>
-      <module fileurl="file://$PROJECT_DIR$/.idea/svo_ros.iml" filepath="$PROJECT_DIR$/.idea/svo_ros.iml" />
-    </modules>
-  </component>
-</project>
\ No newline at end of file
diff --git a/CPU_version/vio_svo/.idea/svo_ros.iml b/CPU_version/vio_svo/.idea/svo_ros.iml
deleted file mode 100644
index f08604b..0000000
--- a/CPU_version/vio_svo/.idea/svo_ros.iml
+++ /dev/null
@@ -1,2 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<module classpath="CMake" type="CPP_MODULE" version="4" />
\ No newline at end of file
diff --git a/CPU_version/vio_svo/.idea/vcs.xml b/CPU_version/vio_svo/.idea/vcs.xml
deleted file mode 100644
index 6c0b863..0000000
--- a/CPU_version/vio_svo/.idea/vcs.xml
+++ /dev/null
@@ -1,6 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="VcsDirectoryMappings">
-    <mapping directory="$PROJECT_DIR$/.." vcs="Git" />
-  </component>
-</project>
\ No newline at end of file
diff --git a/CPU_version/vio_svo/CMakeLists.txt b/CPU_version/vio_svo/CMakeLists.txt
deleted file mode 100644
index 7fdf637..0000000
--- a/CPU_version/vio_svo/CMakeLists.txt
+++ /dev/null
@@ -1,90 +0,0 @@
-SET(PROJECT_NAME vio_svo)
-PROJECT(${PROJECT_NAME})
-CMAKE_MINIMUM_REQUIRED (VERSION 2.8.3)
-SET(CMAKE_BUILD_TYPE Release) # Release, RelWithDebInfo
-SET(CMAKE_VERBOSE_MAKEFILE OFF)
-SET(CMAKE_MODULE_PATH ${CMAKE_MODULE_PATH} "${PROJECT_SOURCE_DIR}/CMakeModules/")
-
-# Set build flags. Set IS_ARM on odroid board as environment variable
-SET(CMAKE_CXX_FLAGS "-Wall -D_LINUX -D_REENTRANT -march=native -Wno-unused-variable -Wno-unused-but-set-variable -Wno-unknown-pragmas")
-IF(DEFINED ENV{ARM_ARCHITECTURE})
-  SET(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")
-ELSE()
-  SET(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mmmx -msse -msse -msse2 -msse3 -mssse3")
-ENDIF()
-IF(CMAKE_COMPILER_IS_GNUCC)
-  SET(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++0x")
-ELSE()
-  SET(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11")
-ENDIF()
-SET(CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS} -O3 -fsee -fomit-frame-pointer -fno-signed-zeros -fno-math-errno -funroll-loops")
-
-# Add catkin and required ROS packages
-FIND_PACKAGE(catkin REQUIRED COMPONENTS
-        geometry_msgs
-        roscpp
-  cmake_modules
-  nav_msgs
-  std_msgs
-  visualization_msgs
-  sensor_msgs
-  image_transport
-  cv_bridge
-  tf
-  svo
-  vikit_common
-  vikit_ros
-)
-
-# Add plain cmake packages 
-FIND_PACKAGE(OpenCV 3 REQUIRED)
-FIND_PACKAGE(Eigen REQUIRED)
-FIND_PACKAGE(Sophus REQUIRED)
-FIND_PACKAGE(Boost REQUIRED COMPONENTS thread)
-FIND_PACKAGE(GTSAM REQUIRED)
-
-# notify catkin to look at the previously found msg files
-add_message_files(
-        FILES
-        Info.msg
-)
-
-# build the header files from the msg files, and notify catkin about the dependencies
-generate_messages(
-        DEPENDENCIES
-        geometry_msgs
-        sensor_msgs
-)
-# Describe catkin Project
-catkin_package(
-  DEPENDS Eigen OpenCV Sophus Boost
-  CATKIN_DEPENDS roscpp nav_msgs std_msgs visualization_msgs sensor_msgs image_transport cv_bridge tf svo vikit_common vikit_ros geometry_msgs
-  INCLUDE_DIRS include
-  LIBRARIES svo_visualizer
-)
-
-# Include dirs
-INCLUDE_DIRECTORIES(
-        include
-  ${Eigen_INCLUDE_DIRS}
-  ${OpenCV_INCLUDE_DIRS}
-  ${Sophus_INCLUDE_DIRS}
-  ${Boost_INCLUDE_DIRS}
-  ${catkin_INCLUDE_DIRS}
-)
-
-# Set link libraries
-LIST(APPEND LINK_LIBS 
-  ${OpenCV_LIBS}
-  ${Sophus_LIBRARIES}
-  ${Boost_LIBRARIES}
-  ${catkin_LIBRARIES}
-)
-
-# Create visualizer library
-ADD_LIBRARY(svo_visualizer src/visualizer.cpp)
-TARGET_LINK_LIBRARIES(svo_visualizer ${LINK_LIBS} gtsam)
-                                 
-# Create Executables                      
-ADD_EXECUTABLE(vo src/vo_node.cpp)
-TARGET_LINK_LIBRARIES(vo svo_visualizer ${LINK_LIBS})
diff --git a/CPU_version/vio_svo/include/vio_svo/visualizer.h b/CPU_version/vio_svo/include/vio_svo/visualizer.h
deleted file mode 100644
index 1b730ee..0000000
--- a/CPU_version/vio_svo/include/vio_svo/visualizer.h
+++ /dev/null
@@ -1,73 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#ifndef SVO_VISUALIZER_H_
-#define SVO_VISUALIZER_H_
-
-#include <queue>
-#include <ros/ros.h>
-#include <svo/global.h>
-#include <visualization_msgs/Marker.h>
-#include <visualization_msgs/MarkerArray.h>
-#include <tf/transform_broadcaster.h>
-#include <image_transport/image_transport.h>
-#include <boost/thread.hpp>
-#include <boost/shared_ptr.hpp>
-
-namespace svo {
-
-class Frame;
-class Point;
-class Map;
-class FrameHandlerMono;
-
-typedef boost::shared_ptr<Frame> FramePtr;
-
-/// This class bundles all functions to publish visualisation messages.
-class Visualizer
-{
-public:
-  ros::NodeHandle pnh_;
-  size_t trace_id_;
-  ros::Publisher pub_frames_;
-  ros::Publisher pub_points_;
-  ros::Publisher pub_pose_;
-  ros::Publisher pub_info_;
-  tf::TransformBroadcaster br_;
-  SE3 T_world_from_vision_;
-
-  Visualizer();
-
-  ~Visualizer() {};
-
-  void publishMinimal(
-      const cv::Mat& img,
-      const FramePtr& frame,
-      const FrameHandlerMono& slam,
-      const double timestamp);
-
-  void visualizeMarkers(
-      const FramePtr& frame,
-      const set<FramePtr>& core_kfs,
-      const Map& map);
-
-  void removeDeletedPts(const Map& map);
-
-};
-
-} // end namespace svo
-
-#endif /* SVO_VISUALIZER_H_ */
diff --git a/CPU_version/vio_svo/launch/Px30.launch b/CPU_version/vio_svo/launch/Px30.launch
deleted file mode 100644
index 7e3e73c..0000000
--- a/CPU_version/vio_svo/launch/Px30.launch
+++ /dev/null
@@ -1,22 +0,0 @@
-<launch>
-
-  <node pkg="vio_svo" type="vo" name="vio" clear_params="true" output="screen">
-
-    <!-- Camera topic to subscribe to -->
-    <param name="cam_topic" value="/CoreNode/grey_img" type="str" />
-    <param name="imu_topic" value="/SensorNode/imu" type="str" />
-    
-    <!-- Camera calibration file -->
-    <rosparam file="$(find vio_svo)/param/px30.yaml" />
-
-    <!-- IMU 2 Camera Frame -->
-    <param name="init_rx" value="1.88496" /><!--  90 + 18 -->
-    <param name="init_ry" value="0.0" /> <!--  90 -->
-    <param name="init_rz" value="0.0" /> <!-- 0  -->
-
-  </node>
-
-  <!-- Default parameter settings: choose between vo_fast and vo_accurate -->
-  <rosparam file="$(find vio_svo)/param/vo_fast.yaml" />
-
-</launch>
diff --git a/CPU_version/vio_svo/launch/live.launch b/CPU_version/vio_svo/launch/live.launch
deleted file mode 100644
index 7cd0ad8..0000000
--- a/CPU_version/vio_svo/launch/live.launch
+++ /dev/null
@@ -1,16 +0,0 @@
-<launch>
-  
-    <node pkg="svo_ros" type="vo" name="svo" clear_params="true" output="screen">
-    
-        <!-- Camera topic to subscribe to -->
-        <param name="cam_topic" value="/camera/image_raw" type="str" />
-        
-        <!-- Camera calibration file -->
-        <rosparam file="$(find svo_ros)/param/camera_atan.yaml" />
-        
-        <!-- Default parameter settings: choose between vo_fast and vo_accurate -->
-        <rosparam file="$(find svo_ros)/param/vo_fast.yaml" />
-
-    </node>
-        
-</launch>
diff --git a/CPU_version/vio_svo/launch/test.launch b/CPU_version/vio_svo/launch/test.launch
deleted file mode 100644
index 4bcd965..0000000
--- a/CPU_version/vio_svo/launch/test.launch
+++ /dev/null
@@ -1,22 +0,0 @@
-<launch>
-
-  <node pkg="vio_svo" type="vo" name="vio" clear_params="true" output="screen">
-
-    <!-- Camera topic to subscribe to -->
-    <param name="cam_topic" value="/camera/image_raw" type="str" />
-    <param name="imu_topic" value="/SensorNode/imu" type="str" />
-
-    <!-- Camera calibration file -->
-    <rosparam file="$(find vio_svo)/param/camera_atan.yaml" />
-
-    <!-- Default parameter settings: choose between vo_fast and vo_accurate -->
-    <rosparam file="$(find vio_svo)/param/vo_fast.yaml" />
-
-    <!-- Initial camera orientation, make it point downwards -->
-    <param name="init_rx" value="3.14" />
-    <param name="init_ry" value="0.00" />
-    <param name="init_rz" value="0.00" />
-
-  </node>
-
-</launch>
diff --git a/CPU_version/vio_svo/launch/unity.launch b/CPU_version/vio_svo/launch/unity.launch
deleted file mode 100644
index ea34997..0000000
--- a/CPU_version/vio_svo/launch/unity.launch
+++ /dev/null
@@ -1,22 +0,0 @@
-<launch>
-
-  <node pkg="vio_svo" type="vo" name="vio" clear_params="true" output="screen">
-
-    <!-- Camera topic to subscribe to -->
-    <param name="cam_topic" value="/image_converter/output_image " type="str" />
-    <param name="imu_topic" value="/imu_unity/imu" type="str" />
-
-    <!-- Camera calibration file -->
-    <rosparam file="$(find vio_svo)/param/unity.yaml" />
-
-    <!-- Default parameter settings: choose between vo_fast and vo_accurate -->
-    <rosparam file="$(find vio_svo)/param/vo_fast.yaml" />
-
-    <!-- Initial camera orientation, make it point downwards -->
-    <param name="init_rx" value="0.00" />
-    <param name="init_ry" value="0.00" />
-    <param name="init_rz" value="0.00" />
-
-  </node>
-
-</launch>
\ No newline at end of file
diff --git a/CPU_version/vio_svo/msg/Info.msg b/CPU_version/vio_svo/msg/Info.msg
deleted file mode 100644
index b962e1b..0000000
--- a/CPU_version/vio_svo/msg/Info.msg
+++ /dev/null
@@ -1,6 +0,0 @@
-Header      header
-float32     processing_time
-int32[]     keyframes
-int32       num_matches
-int32       tracking_quality
-int32       stage
\ No newline at end of file
diff --git a/CPU_version/vio_svo/package.xml b/CPU_version/vio_svo/package.xml
deleted file mode 100644
index c63372b..0000000
--- a/CPU_version/vio_svo/package.xml
+++ /dev/null
@@ -1,43 +0,0 @@
-<?xml version="1.0"?>
-<package>
-  <name>vio_svo</name>
-  <version>0.1.0</version>
-  <description>
-    Monocular Visual Odometry - ROS Nodes
-  </description>
-  <author>Christian Forster</author>
-  <maintainer email="majidgeravand@gfuse.it">Majid Geravand</maintainer>
-  <license>GPLv3</license>
-
-  <!-- Dependencies which this package needs to build itself. -->
-  <buildtool_depend>catkin</buildtool_depend>
-
-  <!-- Dependencies needed to compile this package. -->
-  <build_depend>roscpp</build_depend>
-  <build_depend>cmake_modules</build_depend> <!-- for FindEigen.cmake module -->
-  <build_depend>nav_msgs</build_depend>
-  <build_depend>std_msgs</build_depend>
-  <build_depend>visualization_msgs</build_depend>
-  <build_depend>sensor_msgs</build_depend>
-  <build_depend>image_transport</build_depend>
-  <build_depend>cv_bridge</build_depend>
-  <build_depend>tf</build_depend>
-  <build_depend>svo</build_depend>
-  <build_depend>vikit_common</build_depend>
-  <build_depend>vikit_ros</build_depend>
-  <build_depend>geometry_msgs</build_depend>
-  
-  <!-- Dependencies needed after this package is compiled. -->
-  <run_depend>roscpp</run_depend>
-  <run_depend>nav_msgs</run_depend>
-  <run_depend>std_msgs</run_depend>
-  <run_depend>visualization_msgs</run_depend>
-  <run_depend>sensor_msgs</run_depend>
-  <run_depend>image_transport</run_depend>
-  <run_depend>cv_bridge</run_depend>
-  <run_depend>tf</run_depend>
-  <run_depend>svo</run_depend>
-  <run_depend>vikit_common</run_depend>
-  <run_depend>vikit_ros</run_depend>
-  <run_depend>geometry_msgs</run_depend>
-</package>
\ No newline at end of file
diff --git a/CPU_version/vio_svo/param/camera_atan.yaml b/CPU_version/vio_svo/param/camera_atan.yaml
deleted file mode 100644
index e3c625c..0000000
--- a/CPU_version/vio_svo/param/camera_atan.yaml
+++ /dev/null
@@ -1,8 +0,0 @@
-cam_model: ATAN
-cam_width: 752
-cam_height: 480
-cam_fx: 0.509326
-cam_fy: 0.796651
-cam_cx: 0.45905
-cam_cy: 0.510056
-cam_d0: 0.9320
\ No newline at end of file
diff --git a/CPU_version/vio_svo/param/camera_pinhole.yaml b/CPU_version/vio_svo/param/camera_pinhole.yaml
deleted file mode 100644
index 506a856..0000000
--- a/CPU_version/vio_svo/param/camera_pinhole.yaml
+++ /dev/null
@@ -1,11 +0,0 @@
-cam_model: Pinhole
-cam_width: 640
-cam_height: 480
-cam_fx: 789.860721
-cam_fy: 790.097440
-cam_cx: 305.323524
-cam_cy: 260.464072
-cam_d0: 0.027470
-cam_d1: -0.051518
-cam_d2: 0.004375
-cam_d3: -0.004028
\ No newline at end of file
diff --git a/CPU_version/vio_svo/param/px30.yaml b/CPU_version/vio_svo/param/px30.yaml
deleted file mode 100644
index 10fa932..0000000
--- a/CPU_version/vio_svo/param/px30.yaml
+++ /dev/null
@@ -1,8 +0,0 @@
-cam_model: ATAN
-cam_width: 640
-cam_height: 480
-cam_fx: 0.463632
-cam_fy: 0.823661
-cam_cx: 0.497465
-cam_cy: 0.498443
-cam_d0: 1.01687
\ No newline at end of file
diff --git a/CPU_version/vio_svo/param/unity.yaml b/CPU_version/vio_svo/param/unity.yaml
deleted file mode 100644
index 023f378..0000000
--- a/CPU_version/vio_svo/param/unity.yaml
+++ /dev/null
@@ -1,8 +0,0 @@
-cam_model: ATAN
-cam_width: 1024
-cam_height: 720
-cam_fx: 1.98248
-cam_fy: 2.68212
-cam_cx: 0.502524
-cam_cy: 0.497744
-cam_d0: -0.000499999
\ No newline at end of file
diff --git a/CPU_version/vio_svo/param/vo_accurate.yaml b/CPU_version/vio_svo/param/vo_accurate.yaml
deleted file mode 100644
index 8446875..0000000
--- a/CPU_version/vio_svo/param/vo_accurate.yaml
+++ /dev/null
@@ -1,4 +0,0 @@
-grid_size: 20
-max_n_kfs: 50
-loba_num_iter: 10
-max_fts: 200
\ No newline at end of file
diff --git a/CPU_version/vio_svo/param/vo_fast.yaml b/CPU_version/vio_svo/param/vo_fast.yaml
deleted file mode 100644
index e33b18a..0000000
--- a/CPU_version/vio_svo/param/vo_fast.yaml
+++ /dev/null
@@ -1,13 +0,0 @@
-svo:
-  grid_size: 30            #Feature grid size of a cell in [px].
-  max_n_kfs: 10            #Limit the number of keyframes in the map. This makes nslam essentially. a Visual Odometry. Set to 0 if unlimited number of keyframes are allowed.  Minimum number of keyframes is 3.
-  loba_num_iter: 0         #Number of iterations in the local bundle adjustment.
-  quality_min_fts: 10      #If the number of tracked features drops below this threshold. Tracking quality is bad.
-  quality_max_drop_fts: 60 #If within one frame, this amount of features are dropped. Tracking quality is bad.
-  ACC_noise: 0.00001          #acc white noise in continuous
-  GYO_noise: 0.00001          #gyro white noise in continuous
-  IUC: 0.1                #integration uncertainty continuous
-  ABC: 0.1                #acc bias in continuous
-  GBC: 0.1                #gyro bias in continuous
-  EBP: 0.1                #error in the bias used for preintegration
-  NRP: 0.0000001                #noise used for projection in preintegration
diff --git a/CPU_version/vio_svo/rqt.perspective b/CPU_version/vio_svo/rqt.perspective
deleted file mode 100644
index 66dd7ef..0000000
--- a/CPU_version/vio_svo/rqt.perspective
+++ /dev/null
@@ -1,293 +0,0 @@
-{
-  "keys": {}, 
-  "groups": {
-    "pluginmanager": {
-      "keys": {
-        "running-plugins": {
-          "type": "repr", 
-          "repr": "{u'rqt_rviz/RViz': [1], u'rqt_reconfigure/Param': [1], u'rqt_image_view/ImageView': [1], u'svo_rqt/Svo': [1]}"
-        }
-      }, 
-      "groups": {
-        "plugin__rqt_rviz__RViz__1": {
-          "keys": {}, 
-          "groups": {
-            "dock_widget__": {
-              "keys": {
-                "dockable": {
-                  "type": "repr", 
-                  "repr": "True"
-                }, 
-                "parent": {
-                  "type": "repr", 
-                  "repr": "None"
-                }
-              }, 
-              "groups": {}
-            }
-          }
-        }, 
-        "plugin__rqt_robot_steering__RobotSteering__1": {
-          "keys": {}, 
-          "groups": {
-            "dock_widget__RobotSteeringUi": {
-              "keys": {
-                "dockable": {
-                  "type": "repr", 
-                  "repr": "u'true'"
-                }, 
-                "parent": {
-                  "type": "repr", 
-                  "repr": "None"
-                }
-              }, 
-              "groups": {}
-            }, 
-            "plugin": {
-              "keys": {
-                "topic": {
-                  "type": "repr", 
-                  "repr": "u'/cmd_vel'"
-                }, 
-                "vx_min": {
-                  "type": "repr", 
-                  "repr": "u'-1'"
-                }, 
-                "vw_min": {
-                  "type": "repr", 
-                  "repr": "u'-3'"
-                }, 
-                "vw_max": {
-                  "type": "repr", 
-                  "repr": "u'3'"
-                }, 
-                "vx_max": {
-                  "type": "repr", 
-                  "repr": "u'1'"
-                }
-              }, 
-              "groups": {}
-            }
-          }
-        }, 
-        "plugin__rqt_reconfigure__Param__1": {
-          "keys": {}, 
-          "groups": {
-            "dock_widget___plugincontainer_top_widget": {
-              "keys": {
-                "dockable": {
-                  "type": "repr", 
-                  "repr": "True"
-                }, 
-                "parent": {
-                  "type": "repr", 
-                  "repr": "None"
-                }
-              }, 
-              "groups": {}
-            }, 
-            "plugin": {
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diff --git a/CPU_version/vio_svo/rviz_config.rviz b/CPU_version/vio_svo/rviz_config.rviz
deleted file mode 100644
index 95d7c0e..0000000
--- a/CPU_version/vio_svo/rviz_config.rviz
+++ /dev/null
@@ -1,153 +0,0 @@
-Panels:
-  - Class: rviz/Displays
-    Help Height: 108
-    Name: Displays
-    Property Tree Widget:
-      Expanded:
-        - /Global Options1
-        - /Status1
-        - /TF1
-        - /Marker1
-        - /Marker2
-        - /Marker2/Namespaces1
-        - /Image1
-      Splitter Ratio: 0.5
-    Tree Height: 680
-  - Class: rviz/Selection
-    Name: Selection
-  - Class: rviz/Tool Properties
-    Expanded:
-      - /2D Pose Estimate1
-      - /2D Nav Goal1
-      - /Publish Point1
-    Name: Tool Properties
-    Splitter Ratio: 0.588679
-  - Class: rviz/Views
-    Expanded:
-      - /Current View1
-    Name: Views
-    Splitter Ratio: 0.5
-  - Class: rviz/Time
-    Experimental: false
-    Name: Time
-    SyncMode: 0
-    SyncSource: Image
-Visualization Manager:
-  Class: ""
-  Displays:
-    - Alpha: 0.5
-      Cell Size: 1
-      Class: rviz/Grid
-      Color: 160; 160; 164
-      Enabled: true
-      Line Style:
-        Line Width: 0.03
-        Value: Lines
-      Name: Grid
-      Normal Cell Count: 0
-      Offset:
-        X: 0
-        Y: 0
-        Z: 0
-      Plane: XY
-      Plane Cell Count: 10
-      Reference Frame: <Fixed Frame>
-      Value: true
-    - Class: rviz/TF
-      Enabled: false
-      Frame Timeout: 15
-      Frames:
-        All Enabled: true
-      Marker Scale: 1
-      Name: TF
-      Show Arrows: true
-      Show Axes: true
-      Show Names: true
-      Tree:
-        {}
-      Update Interval: 0
-      Value: false
-    - Class: rviz/Marker
-      Enabled: true
-      Marker Topic: /svo/keyframes
-      Name: Marker
-      Namespaces:
-        cams: true
-        kfs: true
-      Queue Size: 100
-      Value: true
-    - Class: rviz/Marker
-      Enabled: true
-      Marker Topic: /svo/points
-      Name: Marker
-      Namespaces:
-        pts: true
-        trajectory: true
-      Queue Size: 100
-      Value: true
-    - Class: rviz/Image
-      Enabled: true
-      Image Topic: /svo/image
-      Max Value: 1
-      Median window: 5
-      Min Value: 0
-      Name: Image
-      Normalize Range: true
-      Queue Size: 2
-      Transport Hint: raw
-      Value: true
-  Enabled: true
-  Global Options:
-    Background Color: 255; 255; 255
-    Fixed Frame: /world
-  Name: root
-  Tools:
-    - Class: rviz/Interact
-      Hide Inactive Objects: true
-    - Class: rviz/MoveCamera
-    - Class: rviz/Select
-    - Class: rviz/FocusCamera
-    - Class: rviz/Measure
-    - Class: rviz/SetInitialPose
-      Topic: /initialpose
-    - Class: rviz/SetGoal
-      Topic: /move_base_simple/goal
-    - Class: rviz/PublishPoint
-      Single click: true
-      Topic: /clicked_point
-  Value: true
-  Views:
-    Current:
-      Class: rviz/Orbit
-      Distance: 5.48911
-      Focal Point:
-        X: 0.777511
-        Y: 0.689927
-        Z: -0.445833
-      Name: Current View
-      Near Clip Distance: 0.01
-      Pitch: 0.125204
-      Target Frame: <Fixed Frame>
-      Value: Orbit (rviz)
-      Yaw: 4.45215
-    Saved: ~
-Window Geometry:
-  Displays:
-    collapsed: false
-  Height: 1416
-  Hide Left Dock: false
-  Hide Right Dock: true
-  Image:
-    collapsed: false
-  QMainWindow State: 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
-  Selection:
-    collapsed: false
-  Time:
-    collapsed: false
-  Tool Properties:
-    collapsed: false
-  Views:
-    collapsed: true
-  Width: 2511
-  X: 1962
-  Y: 24
diff --git a/CPU_version/vio_svo/src/visualizer.cpp b/CPU_version/vio_svo/src/visualizer.cpp
deleted file mode 100644
index 901f9ef..0000000
--- a/CPU_version/vio_svo/src/visualizer.cpp
+++ /dev/null
@@ -1,127 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-
-#include <vio_svo/visualizer.h>
-#include <svo/frame_handler_mono.h>
-#include <svo/point.h>
-#include <svo/map.h>
-#include <svo/feature.h>
-#include <vio_svo/Info.h>
-#include <geometry_msgs/PoseWithCovarianceStamped.h>
-#include <vikit/timer.h>
-#include <vikit/output_helper.h>
-#include <deque>
-
-namespace svo {
-
-Visualizer::
-Visualizer() :
-    pnh_("~"),
-    trace_id_(0),
-    T_world_from_vision_(Matrix3d::Identity(), Vector3d::Zero())
-{
-  // Init ROS Marker Publishers
-  pub_frames_ = pnh_.advertise<visualization_msgs::Marker>("keyframes", 10);
-  pub_points_ = pnh_.advertise<visualization_msgs::Marker>("points", 1000);
-  pub_pose_ = pnh_.advertise<geometry_msgs::PoseWithCovarianceStamped>("pose",10);
-  pub_info_ = pnh_.advertise<vio_svo::Info>("info", 10);
-}
-
-void Visualizer::publishMinimal(
-    const cv::Mat& img,
-    const FramePtr& frame,
-    const FrameHandlerMono& slam,
-    const double timestamp)
-{
-  ++trace_id_;
-  std_msgs::Header header_msg;
-  header_msg.frame_id = "/cam";
-  header_msg.seq = trace_id_;
-  header_msg.stamp = ros::Time(timestamp);
-
-  // publish info msg.
-  if(pub_info_.getNumSubscribers() > 0)
-  {
-      vio_svo::Info msg_info;
-    msg_info.header = header_msg;
-    msg_info.processing_time = slam.lastProcessingTime();
-    msg_info.keyframes.reserve(slam.map().keyframes_.size());
-    for(list<FramePtr>::const_iterator it=slam.map().keyframes_.begin(); it!=slam.map().keyframes_.end(); ++it)
-      msg_info.keyframes.push_back((*it)->id_);
-    msg_info.stage = static_cast<int>(slam.stage());
-    msg_info.tracking_quality = static_cast<int>(slam.trackingQuality());
-    if(frame != NULL)
-      msg_info.num_matches = slam.lastNumObservations();
-    else
-      msg_info.num_matches = 0;
-    pub_info_.publish(msg_info);
-  }
-  if(pub_pose_.getNumSubscribers() > 0 && slam.stage() == FrameHandlerBase::STAGE_DEFAULT_FRAME)
-  {
-    Quaterniond q;
-    Vector3d p;
-    Matrix<double,6,6> Cov;
-    // publish cam in world frame (Estimated odometry in the worls frame)
-    SE3 T_world_from_cam(T_world_from_vision_*frame->T_f_w_.inverse());// do not confused with inverse. the T_f_w_ is the from camera to initial position with reference of camera
-    q = Quaterniond(T_world_from_cam.rotation_matrix()*T_world_from_vision_.rotation_matrix().transpose());
-    p = T_world_from_cam.translation();
-    Cov = T_world_from_cam.Adj()*frame->Cov_*T_world_from_cam.inverse().Adj();
-    geometry_msgs::PoseWithCovarianceStampedPtr msg_pose(new geometry_msgs::PoseWithCovarianceStamped);
-    msg_pose->header = header_msg;
-    msg_pose->pose.pose.position.x = p[0];
-    msg_pose->pose.pose.position.y = p[1];
-    msg_pose->pose.pose.position.z = p[2];
-    msg_pose->pose.pose.orientation.x = q.x();
-    msg_pose->pose.pose.orientation.y = q.y();
-    msg_pose->pose.pose.orientation.z = q.z();
-    msg_pose->pose.pose.orientation.w = q.w();
-    for(size_t i=0; i<36; ++i)
-      msg_pose->pose.covariance[i] = Cov(i%6, i/6);
-    pub_pose_.publish(msg_pose);
-  }
-}
-
-void Visualizer::visualizeMarkers(
-    const FramePtr& frame,
-    const set<FramePtr>& core_kfs,
-    const Map& map)
-{
-  if(frame == NULL)
-    return;
-
-  vk::output_helper::publishTfTransform(
-      frame->T_f_w_*T_world_from_vision_.inverse(),
-      ros::Time(frame->timestamp_), "cam_pos", "world", br_);
-
-  if(pub_frames_.getNumSubscribers() > 0 || pub_points_.getNumSubscribers() > 0)
-  {
-    vk::output_helper::publishPointMarker(
-        pub_points_, T_world_from_vision_*frame->pos(), "trajectory",
-        ros::Time::now(), trace_id_, 0, 0.006, Vector3d(0.,0.,0.5));
-    removeDeletedPts(map);
-  }
-}
-
-void Visualizer::removeDeletedPts(const Map& map)
-{
-  if(pub_points_.getNumSubscribers() > 0)
-  {
-    for(list<Point*>::const_iterator it=map.trash_points_.begin(); it!=map.trash_points_.end(); ++it)
-      vk::output_helper::publishPointMarker(pub_points_, Vector3d(), "pts", ros::Time::now(), (*it)->id_, 2, 0.006, Vector3d());
-  }
-}
-
-} // end namespace svo
diff --git a/CPU_version/vio_svo/src/vo_node.cpp b/CPU_version/vio_svo/src/vo_node.cpp
deleted file mode 100644
index 9779f3e..0000000
--- a/CPU_version/vio_svo/src/vo_node.cpp
+++ /dev/null
@@ -1,148 +0,0 @@
-// This file is part of SVO - Semi-direct Visual Odometry.
-//
-// Copyright (C) 2014 Christian Forster <forster at ifi dot uzh dot ch>
-// (Robotics and Perception Group, University of Zurich, Switzerland).
-//
-// SVO is free software: you can redistribute it and/or modify it under the
-// terms of the GNU General Public License as published by the Free Software
-// Foundation, either version 3 of the License, or any later version.
-//
-// SVO is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
-//
-// You should have received a copy of the GNU General Public License
-// along with this program.  If not, see <http://www.gnu.org/licenses/>.
-#include <ros/package.h>
-#include <string>
-#include <svo/frame_handler_mono.h>
-#include <vio_svo/visualizer.h>
-#include <vikit/params_helper.h>
-#include <sensor_msgs/Image.h>
-#include <sensor_msgs/Imu.h>
-#include <image_transport/image_transport.h>
-#include <boost/thread.hpp>
-#include <cv_bridge/cv_bridge.h>
-#include <Eigen/Core>
-#include <vikit/abstract_camera.h>
-#include <vikit/camera_loader.h>
-#include <svo/frame.h>
-
-
-namespace svo {
-
-/// SVO Interface
-class VoNode
-{
-public:
-      svo::FrameHandlerMono* vo_;
-      svo::Visualizer visualizer_;
-      bool publish_markers_;                 //!< publish only the minimal amount of info (choice for embedded devices)
-      vk::AbstractCamera* cam_;
-      FILE* logtime;
-      bool quit_;
-      boost::thread* imu_th;
-      VoNode();
-      ~VoNode();
-      void imgCb(const sensor_msgs::ImageConstPtr& msg);
-      void imuCb(const sensor_msgs::ImuPtr& imu);
-      void imu();
-private:
-    double* imu_;
-};
-
-VoNode::VoNode() :
-      vo_(NULL),
-      publish_markers_(vk::getParam<bool>("vio/publish_markers", true)),
-      cam_(NULL),
-      quit_(false)
-{
-      // Create Camera
-      imu_=(double *)calloc(static_cast<std::size_t>(6), sizeof(double));
-      if(!vk::camera_loader::loadFromRosNs("vio", cam_))
-        throw std::runtime_error("Camera model not correctly specified.");
-      // Get initial position and orientation
-      visualizer_.T_world_from_vision_ = Sophus::SE3(
-          vk::rpy2dcm(Vector3d(vk::getParam<double>("vio/init_rx", 0.0),
-                               vk::getParam<double>("vio/init_ry", 0.0),
-                               vk::getParam<double>("vio/init_rz", 0.0))),
-          Eigen::Vector3d(vk::getParam<double>("vio/init_tx", 0.0),
-                          vk::getParam<double>("vio/init_ty", 0.0),
-                          vk::getParam<double>("vio/init_tz", 0.0)));
-      // Init VO and start
-      vo_ = new svo::FrameHandlerMono(cam_,visualizer_.T_world_from_vision_);
-      vo_->start();
-    imu_th=new boost::thread(&VoNode::imu,this);
-    logtime = fopen((std::string(getenv("HOME"))+"/time.txt").c_str(), "w+");
-
-}
-
-VoNode::~VoNode()
-{
-    quit_=true;
-    fclose(logtime);
-    imu_th->join();
-    delete imu_th;
-    delete logtime;
-    delete vo_;
-    delete cam_;
-}
-
-void VoNode::imgCb(const sensor_msgs::ImageConstPtr& msg)
-{
-      try {
-          auto start=std::chrono::steady_clock::now();
-          cv::Mat img=cv_bridge::toCvShare(msg, "mono8")->image;
-          vo_->addImage(img, msg->header.stamp.toSec());
-          visualizer_.publishMinimal(img, vo_->lastFrame(), *vo_, msg->header.stamp.toSec());
-          if(publish_markers_ && vo_->stage() != FrameHandlerBase::STAGE_PAUSED)
-              visualizer_.visualizeMarkers(vo_->lastFrame(), vo_->coreKeyframes(), vo_->map());
-          if(vo_->stage() == FrameHandlerMono::STAGE_PAUSED)
-              usleep(100000);
-          fprintf(logtime, "%s\n",std::to_string(std::chrono::duration<double>(std::chrono::steady_clock::now()-start).count()).c_str());
-
-      } catch (cv_bridge::Exception& e) {
-        ROS_ERROR("cv_bridge exception: %s", e.what());
-      }
-}
-void VoNode::imuCb(const sensor_msgs::ImuPtr &imu) {
-    double imu_in[6];
-    imu_in[0] = 0.1*imu_[0]+0.9*imu->linear_acceleration.x;
-    imu_in[1] = 0.1*imu_[1]+0.9*imu->linear_acceleration.y;
-    imu_in[2] = 0.1*imu_[2]+0.9*imu->linear_acceleration.z;
-    imu_in[3] = 0.1*imu_[3]+0.9*imu->angular_velocity.x;
-    imu_in[4] = 0.1*imu_[4]+0.9*imu->angular_velocity.y;
-    imu_in[5] = 0.1*imu_[5]+0.9*imu->angular_velocity.z;
-    memcpy(imu_, imu_in, static_cast<std::size_t>(6*sizeof(double)));
-    vo_->imu_integPtr_->update(imu_in);
-}
-void VoNode::imu(){
-    ros::NodeHandle nh;
-    // subscribe to cam msgs
-    image_transport::ImageTransport it(nh);
-    image_transport::Subscriber it_sub = it.subscribe(vk::getParam<std::string>("vio/cam_topic", "camera/image_raw"), 1, &svo::VoNode::imgCb, this);
-    // start processing callbacks
-    while(ros::ok() && !quit_)
-    {
-        ros::spinOnce();
-    }
-
-}
-} // namespace svo
-
-int main(int argc, char **argv)
-{
-  ros::init(argc, argv, "vio");
-  svo::VoNode vo_node;
-  ros::NodeHandle nh;
-  ros::Subscriber imu_sub=nh.subscribe(vk::getParam<std::string>("vio/imu_topic", "imu/raw"),1,&svo::VoNode::imuCb, &vo_node);
-  // start processing callbacks
-  while(ros::ok() && !vo_node.quit_)
-  {
-      ros::spinOnce();
-      usleep(1000);
-      // TODO check when last image was processed. when too long ago. publish warning that no msgs are received!
-  }
-  printf("SVO terminated.\n");
-  return 0;
-}
diff --git a/GPU_version/vio/include/vio/reprojector.h b/GPU_version/vio/include/vio/reprojector.h
index 1a60333..0d757fc 100644
--- a/GPU_version/vio/include/vio/reprojector.h
+++ b/GPU_version/vio/include/vio/reprojector.h
@@ -19,6 +19,9 @@
 
 #include <vio/global.h>
 #include <vio/matcher.h>
+#include <CL/cl.h>
+#include <vio/cl_class.h>
+#include <vio/initialization.h>
 
 namespace vk {
 class AbstractCamera;
@@ -44,7 +47,7 @@ public:
     size_t max_n_kfs;   //!< max number of keyframes to reproject from
     bool find_match_direct;
     Options()
-    : max_n_kfs(10),
+    : max_n_kfs(30),
       find_match_direct(true)
     {}
   } options_;
@@ -52,7 +55,7 @@ public:
   size_t n_matches_;
   size_t n_trials_;
 
-  Reprojector(vk::AbstractCamera* cam, Map& map);
+  Reprojector(vk::AbstractCamera* cam, Map& map, opencl* kernel);
 
   ~Reprojector();
 
@@ -94,6 +97,9 @@ private:
   void resetGrid();
   bool reprojectCell(Cell& cell, FramePtr frame);
   bool reprojectPoint(FramePtr frame, Point* point);
+
+protected:
+    opencl* gpu_freak;
 };
 
 } // namespace vio
diff --git a/GPU_version/vio/kernel/freak.cl b/GPU_version/vio/kernel/freak.cl
new file mode 100644
index 0000000..c3f6010
--- /dev/null
+++ b/GPU_version/vio/kernel/freak.cl
@@ -0,0 +1,129 @@
+void meanIntensity( image2d_t _image, image2d_t _integral, float kp_x, float kp_y,
+							  int scale, int rot, int* point, float3* patternLookupPtr, uchar* output)
+{
+    // Prepare a suitable OpenCL image sampler.
+    sampler_t const sampler = CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;
+    // get point position in image
+    float3* FreakPoint = patternLookupPtr + (scale * FREAK_NB_ORIENTATION * FREAK_NB_POINTS + rot * FREAK_NB_POINTS + (*point));
+    float xf = FreakPoint->x + kp_x;
+    float yf = FreakPoint->y + kp_y;
+    int x = (int)xf;
+    int y = (int)yf;
+
+    // get the sigma:
+    float radius = FreakPoint->z;//sigma
+
+    // calculate output:
+    if( radius < 0.5 )
+    {
+        // interpolation multipliers:
+        const int r_x = (int)((xf - x) * 1024);
+        const int r_y = (int)((yf - y) * 1024);
+        const int r_x_1 = (1024 - r_x);
+        const int r_y_1 = (1024 - r_y);
+        uint ret_val;
+        // linear interpolation:
+        ret_val = (r_x_1 * r_y_1 * (int)(read_imageui(_image, sampler, (int2)(y  , x  ))).x)
+                + (r_x   * r_y_1 * (int)(read_imageui(_image, sampler, (int2)(y  , x+1))).x)
+                + (r_x_1 * r_y   * (int)(read_imageui(_image, sampler, (int2)(y+1, x  ))).x)
+                + (r_x   * r_y   * (int)(read_imageui(_image, sampler, (int2)(y+1, x+1))).x);
+        // return the rounded mean
+        ret_val += 2 * 1024 * 1024;
+        output[*point] = (uchar)(ret_val / (4 * 1024 * 1024));
+    }
+
+    // calculate borders
+    const int x_left   = round(xf - radius);
+    const int y_top    = round(yf - radius);
+    const int x_right  = round(xf + radius + 1); // integral image is 1px wider
+    const int y_bottom = round(yf + radius + 1); // integral image is 1px higher
+    int ret_val;
+
+    ret_val  = read_imageui(_integral, sampler, (int2)(y_bottom, x_right)).x; // bottom right corner
+    ret_val -= read_imageui(_integral, sampler, (int2)(y_bottom, x_left)).x; // bottom left corner
+    ret_val += read_imageui(_integral, sampler, (int2)(y_top,    x_left)).x; // top left corner
+    ret_val -= read_imageui(_integral, sampler, (int2)(y_top,    x_right)).x; // top right corner
+    const int area = (x_right - x_left) * (y_bottom - y_top);
+    ret_val = (ret_val + area / 2) / area;
+    output[*point] = (uchar)(ret_val);
+}
+////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+__kernel void freak(
+    __global		image2d_t*	image, // grayescale image
+	__global		image2d_t*	imgIntegral,
+    __global		float4*			keypoints, // ptx, pty, angle
+    __global		uchar*			descriptors, // kp_size * (64 = NB_PAIRS/8) - CV_8U with zero values
+	__global		int*				patternSizes, // array size : NB_SCALES = 64
+	__global		int4*				orientationPairs, // array size : FREAK_NB_ORIENTATION = 256
+	__global		float3*			patternLookup, // array size : NB_SCALES(64) * FREAK_NB_ORIENTATION(256) * FREAK_NB_POINTS(43)
+	__global		uchar2*			descriptionPairs, // array size : NB_PAIRS = 512
+	__global		int*				nOctaves,
+	__global		int*				kpScaleIdx //array size = kp_size - used to save pattern scale index corresponding to each keypoints
+	)
+{
+    const float sizeCst = (float)(NB_SCALES / (FREAK_LOG2 * *nOctaves));
+    uchar pointsValue[FREAK_NB_POINTS];
+    int thetaIdx = 0;
+    int direction0;
+    int direction1;
+
+	int k = get_global_id(0);
+
+    kpScaleIdx[k] = max( (int)(log(7.0 / FREAK_SMALLEST_KP_SIZE) * sizeCst + 0.5) ,0);
+    if( kpScaleIdx[k] >= NB_SCALES )
+        kpScaleIdx[k] = NB_SCALES - 1;
+
+    if( keypoints[k].x <= patternSizes[kpScaleIdx[k]] || // check if the description at this specific position and scale fits inside the image
+        keypoints[k].y <= patternSizes[kpScaleIdx[k]] ||
+        keypoints[k].x >= get_image_dim(image[(int)keypoints[k].w]).y - patternSizes[kpScaleIdx[k]] ||
+        keypoints[k].y >= get_image_dim(image[(int)keypoints[k].w]).x - patternSizes[kpScaleIdx[k]])
+		return;
+
+        // get the points intensity value in the un-rotated pattern
+        for( int i = FREAK_NB_POINTS; i--; )
+        {
+            meanIntensity(image[(int)keypoints[k].w], imgIntegral[(int)keypoints[k].w], keypoints[k].x, keypoints[k].y,
+                          *(kpScaleIdx + k), 0, &i, patternLookup, pointsValue);
+        }
+        direction0 = 0;
+        direction1 = 0;
+        for( int m = 45; m--; )
+        {
+            // iterate through the orientation pairs
+            const int delta = (pointsValue[ orientationPairs[m].w ] - pointsValue[ orientationPairs[m].x ]);
+            direction0 += delta * (orientationPairs[m].y) / 2048; // weight_dx
+            direction1 += delta * (orientationPairs[m].z) / 2048; // weight_dy
+        }
+
+        thetaIdx = round(FREAK_NB_ORIENTATION *
+						(float)(atan2((float)direction1,(float)direction0) * (180.0 / 3.141592653589793238462643383279502884197169399375)) *
+						(1 / 360.0));
+
+        if( thetaIdx < 0 )
+            thetaIdx += FREAK_NB_ORIENTATION;
+
+        if( thetaIdx >= FREAK_NB_ORIENTATION )
+            thetaIdx -= FREAK_NB_ORIENTATION;
+
+        // extract descriptor at the computed orientation
+        for( int i = FREAK_NB_POINTS; i--; )
+        {
+            meanIntensity(image[(int)keypoints[k].w], imgIntegral[(int)keypoints[k].w], keypoints[k].x, keypoints[k].y,
+                          *(kpScaleIdx + k), thetaIdx, &i, patternLookup, pointsValue);
+        }
+
+        // Extract descriptor
+		int cnt = 0;
+        for( int n = 0; n<4; n++ )
+        {
+			for (int m = 8; m >= 1; m--)
+			{
+				for(int kk = (n*16)+15; kk >= (n*16); --kk, ++cnt)
+				{
+					descriptors[(int)keypoints[k].w*300*64 + (k * 64) + kk] *= 2;
+					if (pointsValue[(int)descriptionPairs[cnt].x] >= pointsValue[(int)descriptionPairs[cnt].y])
+						descriptors[(int)keypoints[k].w*300*64 + (k * 64) + kk] += 1;
+				}
+			}
+        }
+}
\ No newline at end of file
diff --git a/GPU_version/vio/kernel/integral_image.cl b/GPU_version/vio/kernel/integral_image.cl
new file mode 100644
index 0000000..0dfb3cc
--- /dev/null
+++ b/GPU_version/vio/kernel/integral_image.cl
@@ -0,0 +1,14 @@
+__kernel void integral_image(
+    __read_only	    image2d_t*	int_img, // grayescale image - height X width
+	__write_only	image2d_t*	out_img // (height+1) X (width+1) with zero values
+	)
+{
+	sampler_t const sampler = CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;
+	int k = get_global_id(0)
+    int2 coord = (int2)(get_global_id(1)+1, get_global_id(2)+1);
+	int res = 0;
+	for (int i = 0; i < coord.x; i++)
+		for (int j = 0; j < coord.y; j++)
+			res += read_imageui(int_img[k], sampler, (int2)(i, j)); // bottom right corner
+	write_imageui(out_img[k], coord, res);
+}
\ No newline at end of file
diff --git a/GPU_version/vio/src/cl_class.cpp b/GPU_version/vio/src/cl_class.cpp
index c3af6a1..f615102 100644
--- a/GPU_version/vio/src/cl_class.cpp
+++ b/GPU_version/vio/src/cl_class.cpp
@@ -41,7 +41,9 @@ opencl::opencl(vk::AbstractCamera* cam):cam(cam) {
                         " -DF_Y="+std::to_string(camera[1])+
                         " -DC_X="+std::to_string(camera[2])+
                         " -DC_Y="+std::to_string(camera[3])+
-                        " -DS="+std::to_string(camera[4]);
+                        " -DS="+std::to_string(camera[4])+
+                        " -DFREAK_LOG2=0.693147180559945 -DFREAK_NB_ORIENTATION=256 -DFREAK_NB_POINTS=43"+
+                        " -DFREAK_SMALLEST_KP_SIZE=7 -DNB_PAIRS=512 -DNB_SCALES=64";
     if(program->build({ *device },options.c_str()) !=0)
         std::cout << " Error building: " << program->getBuildInfo<CL_PROGRAM_BUILD_STATUS>(*device)<<'\n'
                   << " Binary type: " << program->getBuildInfo<CL_PROGRAM_BINARY_TYPE>(*device)<<'\n'
diff --git a/GPU_version/vio/src/frame_handler_mono.cpp b/GPU_version/vio/src/frame_handler_mono.cpp
index 576b57d..a4d4fe4 100644
--- a/GPU_version/vio/src/frame_handler_mono.cpp
+++ b/GPU_version/vio/src/frame_handler_mono.cpp
@@ -171,6 +171,7 @@ FrameHandlerBase::UpdateResult FrameHandlerMono::processFrame()
   SparseImgAlignGpu img_align(Config::kltMaxLevel(), Config::kltMinLevel(),30, SparseImgAlignGpu::GaussNewton, false,gpu_fast_);
   if(img_align.run(last_frame_, new_frame_)==0)return  RESULT_FAILURE;
   reprojector_.reprojectMap(new_frame_, overlap_kfs_);
+  // assert // TODO
 /*
   std::cout<<"Reprojection Map nPoint: "<<overlap_kfs_.back().second
              <<"\tnCell: "<<reprojector_.n_trials_<<"\t nMatches: "<<reprojector_.n_matches_
diff --git a/GPU_version/vio/src/reprojector.cpp b/GPU_version/vio/src/reprojector.cpp
index d2d68bc..db856f2 100644
--- a/GPU_version/vio/src/reprojector.cpp
+++ b/GPU_version/vio/src/reprojector.cpp
@@ -30,8 +30,8 @@
 
 namespace vio {
 
-Reprojector::Reprojector(vk::AbstractCamera* cam, Map& map) :
-    map_(map)
+Reprojector::Reprojector(vk::AbstractCamera* cam, Map& map, opencl* kernel) :
+    map_(map), gpu_freak(kernel)
 {
   initializeGrid(cam);
 }
@@ -130,15 +130,227 @@ void Reprojector::reprojectMap(
   // Now we go through each grid cell and select one point to match.
   // At the end, we should have at maximum one reprojected point per cell.
   //SVO_START_TIMER("feature_align");
-  for(size_t i=0; i<grid_.cells.size(); ++i)
-  {
-    // we prefer good quality points over unkown quality (more likely to match)
-    // and unknown quality over candidates (position not optimized)
-    if(reprojectCell(*grid_.cells.at(grid_.cell_order[i]), frame))
-      ++n_matches_;
-    if(n_matches_ > (size_t) Config::maxFts())
-      break;
+
+  //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+  std::vector<cl_float4> kps; // keypoints
+  cl_float4  data;
+  int frame_number = 0;
+  for(auto it_frame = overlap_kfs.begin(), ite_frame = overlap_kfs.end(); it_frame != ite_frame; it_frame++){
+      for(auto it_ftr = it_frame->first->fts_.begin(), ite_ftr = it_frame->first->fts_.end(); it_ftr != ite_ftr; it_ftr++){
+          data.w = frame_number;
+          data.x = (*it_ftr)->px.x();
+          data.y = (*it_ftr)->px.y();
+          data.z = 0.0;
+          kps.push_back(data);
+      }
+      frame_number++;
   }
+  cl_float4 keypoints[kps.size()];
+  size_t counter = 0;
+  for(auto it = kps.begin(), ite = kps.end(); it != ite; it++) {
+      cl_float4  ftr;
+      ftr.w = it->w;
+      ftr.x = it->x;
+      ftr.y = it->y;
+      ftr.z = it->z;
+      keypoints[counter++] = ftr;
+  }
+  //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+  /*cl_float3 keypoints[overlap_kfs.back().second];
+  size_t counter = 0;
+  for(size_t i = 0; i < grid_.cells.size(); ++i)
+  {
+      Cell* cell = grid_.cells.at(grid_.cell_order[i]);
+      for(auto it = cell->begin(), ite = cell->end(); it != ite; it++, counter++)
+      {
+          keypoints[counter].x = it->px.x(); //x
+          keypoints[counter].y = it->px.y(); //y
+          keypoints[counter].z = 0.0; //angle
+      }
+  }*/
+//  opencl_initializer();
+//  cv::Mat img = overlap_kfs.back().first->img();
+//  cv::Mat integral_img=cv::Mat(cv::Size(701, 501),CV_8UC1);
+//  gpu_freak->reload_buf(0,0,img);
+//  gpu_freak->run(0);
+//  gpu_freak->read(0,1,1,&integral_img);
+
+  // FREAK preprocessing
+  static const float FREAK_LOG2 = 0.693147180559945;
+  static const int FREAK_NB_ORIENTATION = 256;
+  static const int NB_ORIENPAIRS = 45;
+  static const int FREAK_NB_POINTS = 43;
+  static const int FREAK_SMALLEST_KP_SIZE = 7; // smallest size of keypoints
+  static const int NB_PAIRS = 512;
+  static const int NB_SCALES = 64;
+
+  bool orientationNormalized = true;
+  bool scaleNormalized = true;
+  float patternScale = 22.0f;
+  int nOctaves = 4;
+
+  bool extAll = false; // true if all pairs need to be extracted for pairs selection
+
+  cl_float3 patternLookup[NB_SCALES * FREAK_NB_ORIENTATION * FREAK_NB_POINTS]; // look-up table for the pattern points (position+sigma of all points at all scales and orientation)
+  int patternSizes[NB_SCALES]; // size of the pattern at a specific scale (used to check if a point is within image boundaries)
+  cl_uchar2 descriptionPairs[NB_PAIRS];
+  cl_int4 orientationPairs[NB_ORIENPAIRS];
+
+  // default pairs
+  static const int FREAK_DEF_PAIRS[NB_PAIRS] = {
+    404,431,818,511,181,52,311,874,774,543,719,230,417,205,11,
+    560,149,265,39,306,165,857,250,8,61,15,55,717,44,412,
+    592,134,761,695,660,782,625,487,549,516,271,665,762,392,178,
+    796,773,31,672,845,548,794,677,654,241,831,225,238,849,83,
+    691,484,826,707,122,517,583,731,328,339,571,475,394,472,580,
+    381,137,93,380,327,619,729,808,218,213,459,141,806,341,95,
+    382,568,124,750,193,749,706,843,79,199,317,329,768,198,100,
+    466,613,78,562,783,689,136,838,94,142,164,679,219,419,366,
+    418,423,77,89,523,259,683,312,555,20,470,684,123,458,453,833,
+    72,113,253,108,313,25,153,648,411,607,618,128,305,232,301,84,
+    56,264,371,46,407,360,38,99,176,710,114,578,66,372,653,
+    129,359,424,159,821,10,323,393,5,340,891,9,790,47,0,175,346,
+    236,26,172,147,574,561,32,294,429,724,755,398,787,288,299,
+    769,565,767,722,757,224,465,723,498,467,235,127,802,446,233,
+    544,482,800,318,16,532,801,441,554,173,60,530,713,469,30,
+    212,630,899,170,266,799,88,49,512,399,23,500,107,524,90,
+    194,143,135,192,206,345,148,71,119,101,563,870,158,254,214,
+    276,464,332,725,188,385,24,476,40,231,620,171,258,67,109,
+    844,244,187,388,701,690,50,7,850,479,48,522,22,154,12,659,
+    736,655,577,737,830,811,174,21,237,335,353,234,53,270,62,
+    182,45,177,245,812,673,355,556,612,166,204,54,248,365,226,
+    242,452,700,685,573,14,842,481,468,781,564,416,179,405,35,
+    819,608,624,367,98,643,448,2,460,676,440,240,130,146,184,
+    185,430,65,807,377,82,121,708,239,310,138,596,730,575,477,
+    851,797,247,27,85,586,307,779,326,494,856,324,827,96,748,
+    13,397,125,688,702,92,293,716,277,140,112,4,80,855,839,1,
+    413,347,584,493,289,696,19,751,379,76,73,115,6,590,183,734,
+    197,483,217,344,330,400,186,243,587,220,780,200,793,246,824,
+    41,735,579,81,703,322,760,720,139,480,490,91,814,813,163,
+    152,488,763,263,425,410,576,120,319,668,150,160,302,491,515,
+    260,145,428,97,251,395,272,252,18,106,358,854,485,144,550,
+    131,133,378,68,102,104,58,361,275,209,697,582,338,742,589,
+    325,408,229,28,304,191,189,110,126,486,211,547,533,70,215,
+    670,249,36,581,389,605,331,518,442,822
+  };
+
+  float scaleStep = pow(2.0, (float)(nOctaves)/NB_SCALES ); // 2 ^ ( (nOctaves-1) /nbScales)
+
+  const int nn[8] = {6, 6, 6, 6, 6, 6, 6, 1}; // number of points on each concentric circle (from outer to inner)
+  const float bigR = (float)(2.0 / 3.0); // bigger radius
+  const float smallR = (float)(2.0 / 24.0); // smaller radius
+  const float unitSpace = (float)((bigR - smallR) / 21.0 ); // define spaces between concentric circles (from center to outer: 1,2,3,4,5,6)
+  // radii of the concentric cirles (from outer to inner)
+  const float radius[8] = {bigR                 , bigR -  6 * unitSpace, bigR - 11 * unitSpace, bigR - 15 * unitSpace,
+                           bigR - 18 * unitSpace, bigR - 20 * unitSpace, smallR               , 0.0};
+  // sigma of pattern points (each group of 6 points on a concentric cirle has the same sigma)
+  const float sigma[8] = {float(radius[0] / 2.0), float(radius[1] / 2.0), float(radius[2] / 2.0), float(radius[3] / 2.0),
+                          float(radius[4] / 2.0), float(radius[5] / 2.0), float(radius[6] / 2.0), float(radius[6] / 2.0)};
+
+  for( int scaleIdx=0; scaleIdx < NB_SCALES; ++scaleIdx )
+  {
+      patternSizes[scaleIdx] = 0; // proper initialization
+      float scalingFactor = pow(scaleStep,scaleIdx); //scale of the pattern, scaleStep ^ scaleIdx
+
+      for( int orientationIdx = 0; orientationIdx < FREAK_NB_ORIENTATION; ++orientationIdx )
+      {
+          int pointIdx = 0;
+
+          for( size_t i = 0; i < 8; ++i )
+          {
+              for( int k = 0 ; k < nn[i]; ++k )
+              {
+                  float alpha = (float)(k) * 2 * (float)3.141592653589793238462643383279502884197169399375 / (float)(nn[i])
+                              + ((float)3.141592653589793238462643383279502884197169399375 / nn[i] * ( i % 2 )/*beta*/)
+                              + ((float)(orientationIdx * 2 * (float)3.141592653589793238462643383279502884197169399375 / (float)(FREAK_NB_ORIENTATION)) /* theta*/);
+
+                  // add the point to the look-up table
+                  cl_float3* point = &patternLookup[scaleIdx * FREAK_NB_ORIENTATION * FREAK_NB_POINTS + orientationIdx * FREAK_NB_POINTS + pointIdx];
+                  point->x = (float)(radius[i] * cos(alpha) * scalingFactor * patternScale); //x
+                  point->y = (float)(radius[i] * sin(alpha) * scalingFactor * patternScale); //y
+                  point->z = (float)(sigma[i] * scalingFactor * patternScale); //sigma
+
+                  // adapt the sizeList if necessary
+                  const int sizeMax = (int)(ceil((radius[i] + sigma[i]) * scalingFactor * patternScale)) + 1;
+                  if( patternSizes[scaleIdx] < sizeMax )
+                      patternSizes[scaleIdx] = sizeMax;
+
+                  ++pointIdx;
+              }
+          }
+      }
+  }
+
+  // build the list of orientation pairs
+  orientationPairs[0].w=0;   orientationPairs[0].x=3;   orientationPairs[1].w=1;   orientationPairs[1].x=4;    orientationPairs[2].w=2;   orientationPairs[2].x=5;
+  orientationPairs[3].w=0;   orientationPairs[3].x=2;   orientationPairs[4].w=1;   orientationPairs[4].x=3;    orientationPairs[5].w=2;   orientationPairs[5].x=4;
+  orientationPairs[6].w=3;   orientationPairs[6].x=5;   orientationPairs[7].w=4;   orientationPairs[7].x=0;    orientationPairs[8].w=5;   orientationPairs[8].x=1;
+
+  orientationPairs[9].w=6;   orientationPairs[9].x=9;   orientationPairs[10].w=7;  orientationPairs[10].x=10;  orientationPairs[11].w=8;  orientationPairs[11].x=11;
+  orientationPairs[12].w=6;  orientationPairs[12].x=8;  orientationPairs[13].w=7;  orientationPairs[13].x=9;   orientationPairs[14].w=8;  orientationPairs[14].x=10;
+  orientationPairs[15].w=9;  orientationPairs[15].x=11; orientationPairs[16].w=10; orientationPairs[16].x=6;   orientationPairs[17].w=11; orientationPairs[17].x=7;
+
+  orientationPairs[18].w=12; orientationPairs[18].x=15; orientationPairs[19].w=13; orientationPairs[19].x=16;  orientationPairs[20].w=14; orientationPairs[20].x=17;
+  orientationPairs[21].w=12; orientationPairs[21].x=14; orientationPairs[22].w=13; orientationPairs[22].x=15;  orientationPairs[23].w=14; orientationPairs[23].x=16;
+  orientationPairs[24].w=15; orientationPairs[24].x=17; orientationPairs[25].w=16; orientationPairs[25].x=12;  orientationPairs[26].w=17; orientationPairs[26].x=13;
+
+  orientationPairs[27].w=18; orientationPairs[27].x=21; orientationPairs[28].w=19; orientationPairs[28].x=22;  orientationPairs[29].w=20; orientationPairs[29].x=23;
+  orientationPairs[30].w=18; orientationPairs[30].x=20; orientationPairs[31].w=19; orientationPairs[31].x=21;  orientationPairs[32].w=20; orientationPairs[32].x=22;
+  orientationPairs[33].w=21; orientationPairs[33].x=23; orientationPairs[34].w=22; orientationPairs[34].x=18;  orientationPairs[35].w=23; orientationPairs[35].x=19;
+
+  orientationPairs[36].w=24; orientationPairs[36].x=27; orientationPairs[37].w=25; orientationPairs[37].x=28;  orientationPairs[38].w=26; orientationPairs[38].x=29;
+  orientationPairs[39].w=30; orientationPairs[39].x=33; orientationPairs[40].w=31; orientationPairs[40].x=34;  orientationPairs[41].w=32; orientationPairs[41].x=35;
+  orientationPairs[42].w=36; orientationPairs[42].x=39; orientationPairs[43].w=37; orientationPairs[43].x=40;  orientationPairs[44].w=38; orientationPairs[44].x=41;
+
+  for( unsigned m = NB_ORIENPAIRS; m--; )
+  {
+      float dx = patternLookup[orientationPairs[m].w].x - patternLookup[orientationPairs[m].x].x;
+      float dy = patternLookup[orientationPairs[m].w].y - patternLookup[orientationPairs[m].x].y;
+      float norm_sq = (dx * dx + dy * dy);
+      orientationPairs[m].y = round((dx / (norm_sq)) * 4096.0); //weight_dx
+      orientationPairs[m].z = round((dy / (norm_sq)) * 4096.0); //weight_dy
+  }
+
+  // build the list of description pairs
+  cl_uchar2 allPairs[(int)((FREAK_NB_POINTS * (FREAK_NB_POINTS + 1)) / 2)];
+  for( int i = 1, idx = 0; i < FREAK_NB_POINTS; ++i )
+  {
+      // (generate all the pairs)
+      for( int j = 0; j < i; ++j )
+      {
+          allPairs[idx++] = (cl_uchar2){(uchar)i, (uchar)j};
+      }
+  }
+  for( int i = 0; i < NB_PAIRS; ++i )
+      descriptionPairs[i] = allPairs[FREAK_DEF_PAIRS[i]];
+
+  int kpScaleIdx[overlap_kfs.back().second];
+
+
+//  gpu_freak->reload_buf(1,0,img);
+//  gpu_freak->reload_buf(1,1,integral_img);
+//  gpu_freak->reload_buf(1,2, keypoints);
+//  gpu_freak->reload_buf(1,4,patternSizes);
+//  gpu_freak->reload_buf(1,5,orientationPairs);
+//  gpu_freak->reload_buf(1,6,patternLookup);
+//  gpu_freak->reload_buf(1,7,descriptionPairs);
+//  gpu_freak->write_buf(1,8,nOctaves);
+//  gpu_freak->reload_buf(1,9,kpScaleIdx);
+//  gpu_freak->run(1);
+//  cl_uchar descriptor[frame_number*300*64]={0};
+//  gpu_freak->read(1,3,300*64,descriptor);
+
+  //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+
+//  for(size_t i=0; i<grid_.cells.size(); ++i)
+//  {
+//    // we prefer good quality points over unkown quality (more likely to match)
+//    // and unknown quality over candidates (position not optimized)
+//    if(reprojectCell(*grid_.cells.at(grid_.cell_order[i]), frame))
+//      ++n_matches_;
+//    if(n_matches_ > (size_t) Config::maxFts())
+//      break;
+//  }
 // SVO_STOP_TIMER("feature_align");
 }
 
@@ -151,7 +363,7 @@ bool Reprojector::pointQualityComparator(Candidate& lhs, Candidate& rhs)
 
 bool Reprojector::reprojectCell(Cell& cell, FramePtr frame)
 {
-  cell.sort(boost::bind(&Reprojector::pointQualityComparator, _1, _2));
+    cell.sort(boost::bind(&Reprojector::pointQualityComparator, _1, _2));
   Cell::iterator it=cell.begin();
   while(it!=cell.end())
   {