OpenCV, feature matching with code from the tutorial

 

I copied the code of the Feature Matching with FLANN from the OpenCV tutorial page, and made the following changes:

  • I used the SIFT features, instead of SURF;

  • I modified the check for a 'good match'. Instead of 

    if( matches[i].distance < 2*min_dist )

    • I used 

        if( matches[i].distance <= 2*min_dist )

    otherwise I would get zero good matches when comparing an image with itself.

  • Modified parameter in drawing the keypoints: 

    drawMatches( img1, k1, img2, k2,
                 good_matches, img_matches, Scalar::all(-1), Scalar::all(-1),
                 vector<char>(), DrawMatchesFlags::DEFAULT);

    • I extracted the SIFT from all the images in the folder Ireland of the INRIA-Holidays dataset. Then I compared each image to all the others and draw the matches.

    However there is a strange problem I have never experienced with any other SIFT/Matcher implementation I used in the past:

  • the matches for an image I matched against itself are good. Each keypoint is mapped onto itself except for some. See image above. 图像与自身相匹配
  • When I match I against another image J (with J not equal to I), many points are mapped onto the same one. Some examples are below. 火柴火柴火柴

    • Is there anyone who used the same code from the OpenCV tutorial and can report a different experience from mine?

    Checkout the matcher_simple.cpp example. It uses a brute force matcher that seems to work pretty well. Here is the code: 

    // detecting keypoints
SurfFeatureDetector detector(400);
vector<KeyPoint> keypoints1, keypoints2;
detector.detect(img1, keypoints1);
detector.detect(img2, keypoints2);

// computing descriptors
SurfDescriptorExtractor extractor;
Mat descriptors1, descriptors2;
extractor.compute(img1, keypoints1, descriptors1);
extractor.compute(img2, keypoints2, descriptors2);

// matching descriptors
BFMatcher matcher(NORM_L2);
vector<DMatch> matches;
matcher.match(descriptors1, descriptors2, matches);

// drawing the results
namedWindow("matches", 1);
Mat img_matches;
drawMatches(img1, keypoints1, img2, keypoints2, matches, img_matches);
imshow("matches", img_matches);
waitKey(0);
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