From 39660003a272105f9b21259e2936b65a9f105377 Mon Sep 17 00:00:00 2001
From: matlabbe <matlabbe@620bd6b2-0a58-f614-fd9a-1bd335dccda9>
Date: Mon, 29 Oct 2012 20:50:56 +0000
Subject: [PATCH] Example: added hard-coded switch to choose between BFMatcher
 and FLANN matching.

git-svn-id: http://find-object.googlecode.com/svn/trunk/find_object@180 620bd6b2-0a58-f614-fd9a-1bd335dccda9
---
 example/main.cpp | 96 ++++++++++++++++++++++++++++++++++--------------
 1 file changed, 69 insertions(+), 27 deletions(-)

diff --git a/example/main.cpp b/example/main.cpp
index 599c50bd..7ef90c3b 100644
--- a/example/main.cpp
+++ b/example/main.cpp
@@ -95,35 +95,55 @@ int main(int argc, char * argv[])
 		////////////////////////////
 		cv::Mat results;
 		cv::Mat dists;
+		std::vector<std::vector<cv::DMatch> > matches;
+		bool isBinaryDescriptors;
 		int k=2; // find the 2 nearest neighbors
+		bool useBFMatcher = false; // SET TO TRUE TO USE BRUTE FORCE MATCHER (may give better results with binary descriptors)
 		if(objectDescriptors.type()==CV_8U)
 		{
-			// Binary descriptors detected (from ORB or Brief)
+			// Binary descriptors detected (from ORB, Brief, BRISK, FREAK)
+			printf("Binary descriptors detected...\n");
+			isBinaryDescriptors = true;
+			if(useBFMatcher)
+			{
+				cv::BFMatcher matcher(cv::NORM_HAMMING);
+				matcher.knnMatch(objectDescriptors, sceneDescriptors, matches, k);
+			}
+			else
+			{
+				// Create Flann LSH index
+				cv::flann::Index flannIndex(sceneDescriptors, cv::flann::LshIndexParams(12, 20, 2), cvflann::FLANN_DIST_HAMMING);
+				printf("Time creating FLANN LSH index = %d ms\n", time.restart());
+				results = cv::Mat(objectDescriptors.rows, k, CV_32SC1); // Results index
+				dists = cv::Mat(objectDescriptors.rows, k, CV_32FC1); // Distance results are CV_32FC1 ?!?!? NOTE OpenCV doc is not clear about that...
 
-			// Create Flann LSH index
-			cv::flann::Index flannIndex(sceneDescriptors, cv::flann::LshIndexParams(12, 20, 2), cvflann::FLANN_DIST_HAMMING);
-			printf("Time creating FLANN LSH index = %d ms\n", time.restart());
-			results = cv::Mat(objectDescriptors.rows, k, CV_32SC1); // Results index
-			dists = cv::Mat(objectDescriptors.rows, k, CV_32FC1); // Distance results are CV_32FC1 ?!?!? NOTE OpenCV doc is not clear about that...
-
-			// search (nearest neighbor)
-			flannIndex.knnSearch(objectDescriptors, results, dists, k, cv::flann::SearchParams() );
-			printf("Time nearest neighbor search = %d ms\n", time.restart());
+				// search (nearest neighbor)
+				flannIndex.knnSearch(objectDescriptors, results, dists, k, cv::flann::SearchParams() );
+			}
 		}
 		else
 		{
 			// assume it is CV_32F
+			printf("Float descriptors detected...\n");
+			isBinaryDescriptors = false;
+			if(useBFMatcher)
+			{
+				cv::BFMatcher matcher(cv::NORM_L2);
+				matcher.knnMatch(objectDescriptors, sceneDescriptors, matches, k);
+			}
+			else
+			{
+				// Create Flann KDTree index
+				cv::flann::Index flannIndex(sceneDescriptors, cv::flann::KDTreeIndexParams(), cvflann::FLANN_DIST_EUCLIDEAN);
+				printf("Time creating FLANN KDTree index = %d ms\n", time.restart());
+				results = cv::Mat(objectDescriptors.rows, k, CV_32SC1); // Results index
+				dists = cv::Mat(objectDescriptors.rows, k, CV_32FC1); // Distance results are CV_32FC1
 
-			// Create Flann KDTree index
-			cv::flann::Index flannIndex(sceneDescriptors, cv::flann::KDTreeIndexParams(), cvflann::FLANN_DIST_EUCLIDEAN);
-			printf("Time creating FLANN KDTree index = %d ms\n", time.restart());
-			results = cv::Mat(objectDescriptors.rows, k, CV_32SC1); // Results index
-			dists = cv::Mat(objectDescriptors.rows, k, CV_32FC1); // Distance results are CV_32FC1
-
-			// search (nearest neighbor)
-			flannIndex.knnSearch(objectDescriptors, results, dists, k, cv::flann::SearchParams() );
-			printf("Time nearest neighbor search = %d ms\n", time.restart());
+				// search (nearest neighbor)
+				flannIndex.knnSearch(objectDescriptors, results, dists, k, cv::flann::SearchParams() );
+			}
 		}
+		printf("Time nearest neighbor search = %d ms\n", time.restart());
 
 
 
@@ -141,17 +161,39 @@ int main(int argc, char * argv[])
 		std::vector<cv::Point2f> mpts_1, mpts_2; // Used for homography
 		std::vector<int> indexes_1, indexes_2; // Used for homography
 		std::vector<uchar> outlier_mask;  // Used for homography
-		for(int i=0; i<objectDescriptors.rows; ++i)
+		// Check if this descriptor matches with those of the objects
+		if(!useBFMatcher)
 		{
-			// Check if this descriptor matches with those of the objects
-			// Apply NNDR
-			if(dists.at<float>(i,0) <= nndrRatio * dists.at<float>(i,1))
+			for(int i=0; i<objectDescriptors.rows; ++i)
 			{
-				mpts_1.push_back(objectKeypoints.at(i).pt);
-				indexes_1.push_back(i);
+				// Apply NNDR
+				//printf("q=%d dist1=%f dist2=%f\n", i, dists.at<float>(i,0), dists.at<float>(i,1));
+				if(isBinaryDescriptors || //Binary, just take the nearest
+				   dists.at<float>(i,0) <= nndrRatio * dists.at<float>(i,1))
+				{
+					mpts_1.push_back(objectKeypoints.at(i).pt);
+					indexes_1.push_back(i);
 
-				mpts_2.push_back(sceneKeypoints.at(results.at<int>(i,0)).pt);
-				indexes_2.push_back(results.at<int>(i,0));
+					mpts_2.push_back(sceneKeypoints.at(results.at<int>(i,0)).pt);
+					indexes_2.push_back(results.at<int>(i,0));
+				}
+			}
+		}
+		else
+		{
+			for(unsigned int i=0; i<matches.size(); ++i)
+			{
+				// Apply NNDR
+				//printf("q=%d dist1=%f dist2=%f\n", matches.at(i).at(0).queryIdx, matches.at(i).at(0).distance, matches.at(i).at(1).distance);
+				if(isBinaryDescriptors || //Binary, just take the nearest
+				   matches.at(i).at(0).distance <= nndrRatio * matches.at(i).at(1).distance)
+				{
+					mpts_1.push_back(objectKeypoints.at(matches.at(i).at(0).queryIdx).pt);
+					indexes_1.push_back(matches.at(i).at(0).queryIdx);
+
+					mpts_2.push_back(sceneKeypoints.at(matches.at(i).at(0).trainIdx).pt);
+					indexes_2.push_back(matches.at(i).at(0).trainIdx);
+				}
 			}
 		}