trying to make the active search grid work

src/CMakeLists.txt

@@ -118,6 +118,7 @@ SET(headers
 	algorithms/opticalflowpyrlk/alg_opticalflowpyrlk.h
 	algorithms/activesearch/alg_activesearch.h)
 
+
 # locate the necessary dependencies
 FIND_PACKAGE(Eigen3 REQUIRED)
 FIND_PACKAGE(OpenCV REQUIRED)

src/detectors/detector_base.cpp

@@ -30,30 +30,25 @@ KeyPointVector DetectorBase::detect(const cv::Mat& _image, cv::Rect& _roi)
 {
 	// FIX this
 	KeyPointVector kpts;
-	if (!_image.empty() && _roi.height > 2*pattern_radius_ && _roi.width > 2*pattern_radius_)
+	if (!_image.empty())
 	{
 		cv::Mat _image_roi;
-		//adaptRoi(getPatternRadius(), _image, _roi, _image_roi);
-
-		std::cout << "radii: " << getPatternRadius() << "   ROI: " << _roi.x << " " << _roi.y << " " <<  _roi.width << " " << _roi.height << std::endl;
-
-
-		adaptRoi(100, _image, _roi, _image_roi);
-
-std::cout << "radii: " << getPatternRadius() << "   ROI: " << _roi.x << " " << _roi.y << " " <<  _roi.width << " " << _roi.height << std::endl;
-
-//cv::imshow("ACTIVESEARCH algorithm", _image_roi);
-//cv::waitKey(1);
-//
-//  		sleep(2);
-
-  		kpts = detect(_image_roi);
-
-  		for (int ii = 0; ii < kpts.size(); ++ii)
-  		{
-  			kpts[ii].pt.x = kpts[ii].pt.x + _roi.x;
-  			kpts[ii].pt.y = kpts[ii].pt.y + _roi.y;
-  		}
+		adaptRoi(getPatternRadius(), _image, _roi, _image_roi);
+
+		try
+		{
+			kpts = detect(_image_roi);
+
+	  		for (int ii = 0; ii < kpts.size(); ++ii)
+	  		{
+	  			kpts[ii].pt.x = kpts[ii].pt.x + _roi.x;
+	  			kpts[ii].pt.y = kpts[ii].pt.y + _roi.y;
+	  		}
+		}
+		catch( cv::Exception& e )
+		{
+			std::cerr << "exception caught: " << e.what() << std::endl;
+		}
 	}
 	return kpts;
 }

src/detectors/orb/detector_orb.h

@@ -63,7 +63,7 @@ inline void DetectorORB::defineDetector(const ParamsBasePtr _params)
 			params_ptr->scoreType,
 			params_ptr->patchSize);
 
-	pattern_radius_ = params_ptr->edgeThreshold;
+	pattern_radius_ = params_ptr->patchSize;
 }
 
 /*

src/examples/test_algorithm_activesearch.cpp

@@ -45,7 +45,7 @@
 #include "../algorithms/activesearch/alg_activesearch.h"
 
 // TODO: set as user parameters
-#define MAX_NEW_FEATURES 100
+#define MAX_NEW_FEATURES 500
 #define MIN_FEATURES_TO_TRACK 10
 #define MIN_RESPONSE_NEW_FEATURES 80
 #define MATCHER_MIN_NORMALIZED_SCORE 0.85
@@ -109,13 +109,13 @@ void detectNewFeatures(cv::Mat& _frame,
                     _active_search_grid_ptr->hitCell(new_keypoints[0]);
 
                     // Debug
-                    // drawRoi(_frame,roi,_active_search_grid_ptr->getName(),cv::Scalar(50,255,0), 1, 0.1);
+                    drawRoi(_frame,roi,_active_search_grid_ptr->getName(),cv::Scalar(50,255,0), 1, 0.1);
                 }
             }
             else
             {
             	_active_search_grid_ptr->blockCell(roi);
-            	// drawRoi(_frame,roi,_active_search_grid_ptr->getName(),cv::Scalar(255,0,0), 1, 0.1);
+            	drawRoi(_frame,roi,_active_search_grid_ptr->getName(),cv::Scalar(255,0,0), 1, 0.1);
             }
 
             // Debug
@@ -367,8 +367,8 @@ int main(void)
 	active_search_grid_ptr->setParams(params_ptr);
 
 	// Set main ROI areas depending on ACTIVE SEARCH GRID sizes
-	roi_h_ = params_ptr->img_size_v/params_ptr->n_cells_v;
-	roi_w_ = params_ptr->img_size_h/params_ptr->n_cells_h;
+	roi_h_ = params_ptr->img_size_v/(params_ptr->n_cells_v);
+	roi_w_ = params_ptr->img_size_h/(params_ptr->n_cells_h);
 
 	std::vector<feature> features_last_frame_vec;
 
@@ -382,16 +382,16 @@ int main(void)
 
     	// Process
         std::vector<feature> features_tracked_vec;
-//    	if (features_last_frame_vec.size() < MIN_FEATURES_TO_TRACK)
-//    	{
+    	if (features_last_frame_vec.size() < MIN_FEATURES_TO_TRACK)
+    	{
     		// TODO: When to renew?
     		active_search_grid_ptr->renew();
     		detectNewFeatures(frame_cur, det_ptr, des_ptr, active_search_grid_ptr, features_tracked_vec);
-//    	}
-//    	else
-//    	{
-//    		trackFeatures(frame_cur, det_ptr, des_ptr, mat_ptr, active_search_grid_ptr, features_last_frame_vec,features_tracked_vec);
-//    	}
+    	}
+    	else
+    	{
+    		trackFeatures(frame_cur, det_ptr, des_ptr, mat_ptr, active_search_grid_ptr, features_last_frame_vec,features_tracked_vec);
+    	}
 
         features_last_frame_vec.clear();
         features_last_frame_vec = features_tracked_vec;

src/examples/yaml/ACTIVESEARCH.yaml

@@ -8,18 +8,18 @@ detector:
   nfeatures: 100
   scale factor: 2
   nlevels: 8
-  edge threshold: 8   # 16
+  edge threshold: 16   # 16
   first level: 0 
   WTA_K: 2            # See: http://docs.opencv.org/trunk/db/d95/classcv_1_1ORB.html#a180ae17d3300cf2c619aa240d9b607e5
   score type: 1       #enum { kBytes = 32, HARRIS_SCORE=0, FAST_SCORE=1 };
-  patch size: 15      # 31
+  patch size: 31      # 31
 
 descriptor:
   type: "ORB"         
   nfeatures: 100
   scale factor: 2
   nlevels: 8
-  edge threshold: 8   # 16
+  edge threshold: 16   # 16
   first level: 0 
   WTA_K: 2            # See: http://docs.opencv.org/trunk/db/d95/classcv_1_1ORB.html#a180ae17d3300cf2c619aa240d9b607e5
   score type: 1       #enum { kBytes = 32, HARRIS_SCORE=0, FAST_SCORE=1 };
@@ -33,7 +33,7 @@ algorithm:
   type: "ACTIVESEARCH"   
   img size h: 640
   img size v: 480
-  grid height: 8
-  grid width: 12
+  grid height: 10
+  grid width: 10
   margin: 0
   separation: 10
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