OpenCV DrawMatchesFlags - 没有关键点选项？

Question

我正在将图像中的 SURF 点与视频源进行匹配。我希望以不同的分辨率对此进行测试，但我遇到了一个恼人的问题，即当匹配的关键点在小分辨率上绘制时，由于彩色关键点，我无法再看到视频源中发生的事情。有没有办法阻止 OpenCV 在视频上绘制这些并只显示单应性？

我试过查看 DrawMatchesFlags 的选项，但它们似乎只改变正在绘制的关键点的类型，而不是提供删除它们的选项。我正在创建 Mat img_matches，它使用 drawMatches:

在其上绘制关键点

  drawMatches( img_object, keypoints_object, frame, keypoints_scene, good_matches, img_matches, Scalar::all(-1), Scalar::all(-1), vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );

然后我使用 OpenCV findHomography 函数检测单应性并使用以下方法绘制结果：

imshow( "Good Matches & Object detection", img_matches );

如何删除视频源上的特征点匹配并仅显示单应性？

编辑：

检测绘图功能：

  //-- Step 1: Detect the keypoints using SURF Detector
  int minHessian = 400;

  SurfFeatureDetector detector( minHessian );

  std::vector<cv::KeyPoint> keypoints_object, keypoints_scene;

  detector.detect( img_object, keypoints_object );
  detector.detect( frame, keypoints_scene );

  //-- Step 2: Calculate descriptors (feature vectors)
  SurfDescriptorExtractor extractor;

  Mat descriptors_object, descriptors_scene;

  extractor.compute( img_object, keypoints_object, descriptors_object );
  extractor.compute( frame, keypoints_scene, descriptors_scene );

  //-- Step 3: Matching descriptor vectors using FLANN matcher
  FlannBasedMatcher matcher;
  std::vector< DMatch > matches;
  matcher.match( descriptors_object, descriptors_scene, matches );

  double max_dist = 0; double min_dist = 100;

  //-- Quick calculation of max and min distances between keypoints
  for( int i = 0; i < descriptors_object.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 3*min_dist )
  std::vector< DMatch > good_matches;

  for( int i = 0; i < descriptors_object.rows; i++ )
  { if( matches[i].distance < 3*min_dist )
     { good_matches.push_back( matches[i]); }
  }

  Mat img_matches;
  drawMatches( img_object, keypoints_object, frame, keypoints_scene,
               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_object[ good_matches[i].queryIdx ].pt );
    scene.push_back( keypoints_scene[ good_matches[i].trainIdx ].pt );
  }

  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 );

Answer 1

将绘图部分改为：

Mat img_matches;
std::vector< DMatch > emptyVec;  //Make a empty match vector so it won't be drawn.
drawMatches( img_1, keypoints_1, img_2, keypoints_2,
           emptyVec, img_matches, Scalar::all(-1), Scalar::all(-1),
           vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );

OpenCV DrawMatchesFlags - 没有关键点选项？

OpenCV DrawMatchesFlags - no keypoint option?

c++

opencv

feature-detection

surf

homography