I am making a program that tracks features with ORB from OpenCV (2.43) I followed this tutorial and used advice from here.
My goal is to track the object in video feed (face) and draw a rectangle around it.
My program finds keypoints and matches them correctly, but when I try to use findHomography + perspectiveTransform to find new corners for the image usually returns some nonsense type values (though sometimes it returns correct homography).
Here is an example picture:
Here is the corresponding problematic part:
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_object.cols, 0 );
obj_corners[2] = cvPoint( img_object.cols, img_object.rows ); obj_corners[3] = cvPoint( 0, img_object.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_object.cols, 0), scene_corners[1] + Point2f( img_object.cols, 0), Scalar(0, 255, 0), 4 );
line( img_matches, scene_corners[1] + Point2f( img_object.cols, 0), scene_corners[2] + Point2f( img_object.cols, 0), Scalar( 0, 255, 0), 4 );
line( img_matches, scene_corners[2] + Point2f( img_object.cols, 0), scene_corners[3] + Point2f( img_object.cols, 0), Scalar( 0, 255, 0), 4 );
line( img_matches, scene_corners[3] + Point2f( img_object.cols, 0), scene_corners[0] + Point2f( img_object.cols, 0), Scalar( 0, 255, 0), 4 );
Rest of the code is practically the same as in the links I provided. The lines drawn seem completley random, my goal is only to get minimal rectangle of the source object in new scene, so if there is alternative to using homography that works too.
P.S. Source image to track is a region that is copied from video input and then tracked in new pictures from that input, does it matter?