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CPU_version/svo/src/feature_detection.cpp

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+// 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
+