Features2d中的功能检测

Question

有人知道检测功能是如何工作的吗？例如这里：

Mat img = imread (...);    
SurfFeatureDetector detector(400); 
vector<KeyPoint> keypoints;
detector.detect(img, keypoints);

尤其是关键点的书写方式。

我需要在不使用的情况下在关键点中写一些坐标

detector.detect(...);

这行不通

keypoints.push_back(KeyPoint(i,j);

---

下一个问题： 我有这个功能：

void trajkovic(Mat img, vector<KeyPoint> keypoints)
{    for( int i = 0; i < img.rows-3; i++ )
        for( int j = 0; j < img.cols-3; j++ )
        {   Point2f keyPointLocation(i, j);
            keypoints.push_back(KeyPoint(keyPointLocation, 1)); } }

int main()
{   Mat img_object = imread( ".../box.png", CV_LOAD_IMAGE_GRAYSCALE );
    Mat img_scene = imread( ".../box_in_scene.png", CV_LOAD_IMAGE_GRAYSCALE );

    std::vector<KeyPoint> keypoints_object, keypoints_scene;
    trajkovic(img_object, keypoints_object);
    trajkovic(img_scene, keypoints_scene);

• 而不是 (*detector.detect(img_object, keypoints_object);*)

  //-- Step 2: Calculate descriptors (feature vectors)
  SurfDescriptorExtractor extractor;
  
  Mat descriptors_object, descriptors_scene;
  
  extractor.compute( img_object, keypoints_object, descriptors_object );
  extractor.compute( img_scene, 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, img_scene, keypoints_scene,
               good_matches, img_matches, Scalar::all(-1), Scalar::all(-1),
               vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );
  
  
  //-- Localize the object from img_1 in img_2
  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 );
  
  cvWaitKey(0);
  return 0;
  

  }

在 findHomography 中我有一个错误：“断言失败 (npoints >=0 && points2.Vector(2) == npoints)) in findHomography，文件 /modules/calib3d/src/fundam.cpp，第 1062 行”

怎么了？ 我猜是有问题

keypoints.push_back(KeyPoint(keyPointLocation, 1));

非常感谢

Answer 1

首先你应该去抛出opencv documentation。 cv::KeyPoint 是一个存储由cv::FeatureDetector 对象检测到的点的结构。它包含关键点的坐标、有意义的邻域的直径、方向和响应。关键点的计算取决于检测器的定义（Sift,Surf,Mser,...）

开始here！

Answer 2

如果您想手动创建KeyPoint's，这里有一个小示例可以帮助您入门：

vector<KeyPoint> keyPoints;
for(int i = 0; i < 10; i++)
{
    for(int j = 0; j < 10; j++)
    {
        Point2f keyPointLocation(i, j);
        float meaningfulNeighborhoodDiameter = 5.0;
        keyPoints.push_back(KeyPoint(keyPointLocation, meaningfulNeighborhoodDiameter));
    }
}

希望有帮助！