Strange result of SURF_GPU and BruteForceMatcher_GPU with knnMatch - opencv

Question

OpenCV 2.4.5, CUDA 5.0
I tried to transfer my SURF matcher from the CPU to the GPU and got such a strange result. I use knnMatch and findHomography + perspectiveTransform together with my function, which checks the corners of the bounding box for the result to more precision.
GPU part:
const int baseImagesSize = baseImages.size();
SURF_GPU surf(1500);
surf.extended = false;
GpuMat keypoints_test_GPU, descriptors_test_GPU;
surf(frame, GpuMat(), keypoints_test_GPU, descriptors_test_GPU);
vector<float> descriptors_test_CPU;
surf.downloadDescriptors(descriptors_test_GPU, descriptors_test_CPU);
Mat descriptors_test_CPU_Mat(descriptors_test_CPU);
vector<Point2f> objs_corners(4);
BruteForceMatcher_GPU< L2<float> > matcher;
vector<KeyPoint> keypoints_test_CPU;
surf.downloadKeypoints(keypoints_test_GPU, keypoints_test_CPU);
for (int i = 0; i < baseImagesSize; ++i)
{
//Get the corners from the object
objs_corners[0] = cvPoint(0,0);
objs_corners[1] = cvPoint( baseImages[i].cols, 0 );
objs_corners[2] = cvPoint( baseImages[i].cols, baseImages[i].rows );
objs_corners[3] = cvPoint( 0, baseImages[i].rows );
//cout<<endl<<objs_corners[0]<<" "<<objs_corners[1]<<" "<<objs_corners[2]<<" "<<objs_corners[3]<<endl;
GpuMat keypoints_tmp_GPU, descriptors_tmp_GPU;
surf(baseImages[i], GpuMat(), keypoints_tmp_GPU, descriptors_tmp_GPU);
GpuMat trainIdx, distance;
vector< vector<DMatch> > matches;
matcher.knnMatch(descriptors_test_GPU, descriptors_tmp_GPU, matches, 2);
vector<KeyPoint> keypoints_tmp_CPU;
surf.downloadKeypoints(keypoints_tmp_GPU, keypoints_tmp_CPU);
std::vector<DMatch > good_matches;
for(int k = 0; k < min(descriptors_test_CPU_Mat.rows-1,(int) matches.size()); k++) //THIS LOOP IS SENSITIVE TO SEGFAULTS
{
if((matches[k][0].distance < 0.6*(matches[k][1].distance)) && ((int) matches[k].size()<=2 && (int) matches[k].size()>0))
{
good_matches.push_back(matches[k][0]);
}
}
vector<Point2f> obj;
vector<Point2f> scene;
vector<Point2f> scene_corners(4);
Mat H;
Mat img (baseImages[i]), img_matches, frame_cpu (frame);
std::ostringstream o_stream;
o_stream<<"Logo_save/"<<baseImagesNames[i];
try
{
drawMatches( img, keypoints_tmp_CPU, frame_cpu, keypoints_test_CPU, good_matches, img_matches, Scalar::all(-1), Scalar::all(-1), vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );
imwrite(o_stream.str(),img_matches);
}
catch(...)
{
cout<<"Error in drawMatches name: "<< baseImagesNames[i]<<endl;
}
if (good_matches.size() >= 4)
{
for( int k = 0; k < good_matches.size(); k++ )
{
//Get the keypoints from the good matches
obj.push_back( (keypoints_tmp_CPU)[ good_matches[k].queryIdx ].pt );
scene.push_back( keypoints_test_CPU[ good_matches[k].trainIdx ].pt );
}
cout<<good_matches.size()<<" "<<baseImagesNames[i]<<endl;
H = findHomography( obj, scene, CV_RANSAC);
perspectiveTransform( objs_corners, scene_corners, H);
bool falseDetect = isSmallAngle(scene_corners);
//cout<< falseDetect<< endl;
if(!falseDetect)
{
cout<<"DETECT "<<baseImagesNames[i]<<endl;
}
}
matcher.clear();
}
Bad result on GPU (MIN_HESSIAN==1500):
Bad result on GPU (MIN_HESSIAN==400):
CPU part:
SurfFeatureDetector detector( MIN_HESSIAN );//MIN_HESSIAN==400
const int baseImagesSize = baseImages.size();
vector< vector<KeyPoint> > kp_objects(baseImagesSize);
//Calculate descriptors (feature vectors)
SurfDescriptorExtractor extractor;
vector<Mat> des_objects(baseImagesSize);
FlannBasedMatcher matcher;
//namedWindow("SURF feature detector");
vector< vector<Point2f> > objs_corners(baseImagesSize,vector<Point2f>(4));
for (int i = 0; i < baseImagesSize; ++i)
{
detector.detect(baseImages[i], kp_objects[i]);
extractor.compute(baseImages[i], kp_objects[i], des_objects[i]);
//Get the corners from the object
(objs_corners[i])[0] = cvPoint(0,0);
(objs_corners[i])[1] = cvPoint( baseImages[i].cols, 0 );
(objs_corners[i])[2] = cvPoint( baseImages[i].cols, baseImages[i].rows );
(objs_corners[i])[3] = cvPoint( 0, baseImages[i].rows );
}
Mat des_image;
std::vector<KeyPoint> kp_image;
Mat image;
cvtColor(frame, image, CV_RGB2GRAY);
detector.detect( image, kp_image );
extractor.compute( image, kp_image, des_image );
for (int i = 0; i < baseImagesSize; ++i)
{
Mat img_matches;
std::vector<vector<DMatch > > matches;
std::vector<DMatch > good_matches;
std::vector<Point2f> obj;
std::vector<Point2f> scene;
std::vector<Point2f> scene_corners(4);
Mat H;
matcher.knnMatch(des_objects[i], des_image, matches, 2);
for(int k = 0; k < min(des_image.rows-1,(int) matches.size()); k++) //THIS LOOP IS SENSITIVE TO SEGFAULTS
{
if((matches[k][0].distance < 0.6*(matches[k][4].distance)) && ((int) matches[k].size()<=2 && (int) matches[k].size()>0))
{
good_matches.push_back(matches[k][0]);
}
}
//Draw only "good" matches
std::ostringstream o_stream;
o_stream<<"Logo_save/"<<baseImagesNames[i];
try
{
drawMatches( baseImages[i], kp_objects[i], image, kp_image, good_matches, img_matches, Scalar::all(-1), Scalar::all(-1), vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );
imwrite(o_stream.str(),img_matches);
}
catch(...)
{
cout<<"Error in drawMatches name: "<< baseImagesNames[i]<<endl;
}
if (good_matches.size() >= 4)
{
for( int k = 0; k < good_matches.size(); k++ )
{
//Get the keypoints from the good matches
obj.push_back( (kp_objects[i])[ good_matches[k].queryIdx ].pt );
scene.push_back( kp_image[ good_matches[k].trainIdx ].pt );
}
H = findHomography( obj, scene, CV_RANSAC);
perspectiveTransform( objs_corners[i], scene_corners, H);
bool falseDetect = isSmallAngle(scene_corners);
if(!falseDetect)
{
cout<<"DETECT "<<baseImagesNames[i]<<endl;
}
}
}
Good result on CPU (MIN_HESSIAN==400):

Answer 1

Problem solved here topic
Swap parameters in drawMatches call:
drawMatches(frame_cpu, keypoints_test_CPU, img, keypoints_tmp_CPU, ...);
Swap keypoints_tmp_CPU and keypoints_test_CPU:
obj.push_back( keypoints_test_CPU[ good_matches[k].trainIdx ].pt );
scene.push_back( (keypoints_tmp_CPU)[ good_matches[k].queryIdx ].pt );