hi!
i write one program for finding one object in a image file in a video . i read the istruction in the opencv manual and i use the SURF and the FLAAN matcher. the program draw lines between the corners in the mapped object in the video file. the problem is that in some frame the lines are not present or lines draw a strange figure.
for example...this is the correct output
and this is the wrong result for some frame
this is the code for the program:
void surf_detection(Mat img_1,Mat img_2); /** @function main */
int main( int argc, char** argv ) {
int i; int key;
CvCapture* capture = cvCaptureFromAVI("video.MPG");// Read the video file
if (!capture){
cout <<" Error in capture video file" << endl;
return -1;
}
Mat img_template = imread("template.png"); // read template image
CvVideoWriter *writer = 0; int isColor = 1;
//Get capture device properties cvQueryFrame(capture); // this call is necessary to get correct // capture properties int frameH = (int) cvGetCaptureProperty(capture, CV_CAP_PROP_FRAME_HEIGHT); int frameW = (int) cvGetCaptureProperty(capture, CV_CAP_PROP_FRAME_WIDTH); int fps = (int) cvGetCaptureProperty(capture, CV_CAP_PROP_FPS); int numFrames = (int) cvGetCaptureProperty(capture, CV_CAP_PROP_FRAME_COUNT);
writer=cvCreateVideoWriter("out.avi",CV_FOURCC('P','I','M','1'), fps,cvSize(frameW,frameH),isColor);
IplImage* img = 0;
for(i=0;i<numframes;i++){ cvgrabframe(capture);="" capture="" a="" frame="" img="cvRetrieveFrame(capture);" retrieve="" the="" captured="" frame<="" p="">
printf("Frame n° %d \n", i );
surf_detection (img_template,img);
cvWriteFrame(writer,img); // add the frame to the file cvShowImage("mainWin", img); key=cvWaitKey(20); // wait 20 ms
} cvReleaseVideoWriter(&writer);
//waitKey(0); // Wait for a keystroke in the window return 0; }
/* @function surf_detection */ /* USE OF FUNCTION/ /* param1: immagine del template/ /* param2: immagine estratta dal video*/ void surf_detection(Mat img_1,Mat img_2) {
if( !img_1.data || !img_2.data ) { std::cout<< " --(!) Error reading images " << std::endl;
}
//-- Step 1: Detect the keypoints using SURF Detector int minHessian = 400; SurfFeatureDetector detector( minHessian ); std::vector<keypoint> keypoints_1, keypoints_2;
std::vector< DMatch > good_matches;
do{
detector.detect( img_1, keypoints_1 ); detector.detect( img_2, keypoints_2 );
//-- Draw keypoints
Mat img_keypoints_1; Mat img_keypoints_2; drawKeypoints( img_1, keypoints_1, img_keypoints_1, Scalar::all(-1), DrawMatchesFlags::DEFAULT ); drawKeypoints( img_2, keypoints_2, img_keypoints_2, Scalar::all(-1), DrawMatchesFlags::DEFAULT );
//-- Step 2: Calculate descriptors (feature vectors) SurfDescriptorExtractor extractor; Mat descriptors_1, descriptors_2; extractor.compute( img_1, keypoints_1, descriptors_1 ); extractor.compute( img_2, keypoints_2, descriptors_2 );
//-- Step 3: Matching descriptor vectors using FLANN matcher FlannBasedMatcher matcher; std::vector< DMatch > matches; matcher.match( descriptors_1, descriptors_2, matches ); double max_dist = 0; double min_dist = 100;
//-- Quick calculation of max and min distances between keypoints for( int i = 0; i < descriptors_1.rows; i++ ) { double dist = matches[i].distance; if( dist < min_dist ) min_dist = dist; if( dist > max_dist ) max_dist = dist; }
printf("-- Max dist : %f \n", max_dist ); printf("-- Min dist : %f \n", min_dist );
//-- Draw only "good" matches (i.e. whose distance is less than 2*min_dist ) //-- PS.- radiusMatch can also be used here.
for( int i = 0; i < descriptors_1.rows; i++ ) { if( matches[i].distance < 2*min_dist ) { good_matches.push_back( matches[i]); } }
}while(good_matches.size()<100);
//-- Draw only "good" matches Mat img_matches; drawMatches( img_1, keypoints_1, img_2, keypoints_2,good_matches, img_matches, Scalar::all(-1), Scalar::all(-1), vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );
//-- Localize the object std::vector<point2f> obj; std::vector<point2f> scene; for( int i = 0; i < good_matches.size(); i++ ) { //-- Get the keypoints from the good matches obj.push_back( keypoints_1[ good_matches[i].queryIdx ].pt ); scene.push_back( keypoints_2[ good_matches[i].trainIdx ].pt ); }
// se non trova H....sarebbe da usare la vecchia H e disegnarla con un colore diverso Mat H = findHomography( obj, scene, CV_RANSAC );
//-- Get the corners from the image_1 ( the object to be "detected" ) std::vector<point2f> obj_corners(4); obj_corners[0] = cvPoint(0,0); obj_corners[1] = cvPoint( img_1.cols, 0 ); obj_corners[2] = cvPoint( img_1.cols, img_1.rows ); obj_corners[3] = cvPoint( 0, img_1.rows ); std::vector<point2f> scene_corners(4);
perspectiveTransform( obj_corners, scene_corners, H);
//-- Draw lines between the corners (the mapped object in the scene - image_2 ) line( img_matches, scene_corners[0] + Point2f( img_1.cols, 0), scene_corners[1] + Point2f( img_1.cols, 0), Scalar(0, 255, 0), 4 ); line( img_matches, scene_corners[1] + Point2f( img_1.cols, 0), scene_corners[2] + Point2f( img_1.cols, 0), Scalar( 0, 255, 0), 4 ); line( img_matches, scene_corners[2] + Point2f( img_1.cols, 0), scene_corners[3] + Point2f( img_1.cols, 0), Scalar( 0, 255, 0), 4 ); line( img_matches, scene_corners[3] + Point2f( img_1.cols, 0), scene_corners[0] + Point2f( img_1.cols, 0), Scalar( 0, 255, 0), 4 );
//-- Show detected matches imshow( "Good Matches & Object detection", img_matches );
for( int i = 0; i < good_matches.size(); i++ ) { printf( "-- Good Match [%d] Keypoint 1: %d -- Keypoint 2: %d \n", i, good_matches[i].queryIdx, good_matches[i].trainIdx ); }
waitKey(0);
}
