我只想获得高质量的特征点

Question

我目前正在使用 OpenCV3.4.0、QT creator 中的 c++ 进行实时特征匹配。

我的代码匹配我通过网络摄像头获得的第一帧和从网络摄像头输入的当前帧之间的特征。

Mat frame1, frame2, img1, img2, img1_gray, img2_gray;
int n = 0;
VideoCapture cap1(0);
namedWindow("Video Capture1", WINDOW_NORMAL);
namedWindow("Reference img", WINDOW_NORMAL);
namedWindow("matches1", WINDOW_NORMAL);

moveWindow("Video Capture1",50, 0);
moveWindow("Reference img",50, 100);
moveWindow("matches1",100,100);



while((char)waitKey(1)!='q'){
       //raw image saved in frame
       cap1>>frame1;

       n=n+1;
       if (n ==1){
           imwrite("frame1.jpg",  frame1);
           cout<<"First frame saved as 'frame1'!!"<<endl;
       }
       if(frame1.empty())
       break;


       imshow("Video Capture1",frame1);

       img1 = imread("frame1.jpg");
       img2 = frame1;

       cvtColor(img1, img1_gray, cv::COLOR_BGR2GRAY);
       cvtColor(img2, img2_gray, cv::COLOR_BGR2GRAY);

       imshow("Reference img",img1);

       // detecting keypoints
       int minHessian = 400;
       Ptr<Feature2D> detector = xfeatures2d::SurfFeatureDetector::create();
       vector<KeyPoint> keypoints1, keypoints2;
       detector->detect(img1_gray,keypoints1);
       detector->detect(img2_gray,keypoints2);

       // computing descriptors
       Ptr<DescriptorExtractor> extractor = xfeatures2d::SurfFeatureDetector::create();
       Mat descriptors1, descriptors2;
       extractor->compute(img1_gray,keypoints1,descriptors1);
       extractor->compute(img2_gray,keypoints2,descriptors2);

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

       // drawing the results

       Mat img_matches;
       drawMatches(img1, keypoints1, img2, keypoints2, matches, img_matches);
       imshow("matches1", img_matches);

但是代码returns匹配的点太多，分不清哪个匹配哪个

那么，有什么方法可以只得到高质量的匹配点吗？

如何像 MATLAB 一样在 QT creator 中获取每个匹配点的像素坐标？

Answer 1

So, are there any methods to get high-quality matched points only?

我敢打赌有很多不同的方法。我正在使用例如对称性测试。因此，当从 img2 匹配到 img1 时，从 img1 到 img2 的匹配项也必须存在。我正在使用 Improve matching of feature points with OpenCV 的测试。那里显示了多项其他测试。

void symmetryTest(const std::vector<cv::DMatch> &matches1,const std::vector<cv::DMatch> &matches2,std::vector<cv::DMatch>& symMatches)
{
    symMatches.clear();
    for (vector<DMatch>::const_iterator matchIterator1= matches1.begin();matchIterator1!= matches1.end(); ++matchIterator1)
    {
        for (vector<DMatch>::const_iterator matchIterator2= matches2.begin();matchIterator2!= matches2.end();++matchIterator2)
        {
            if ((*matchIterator1).queryIdx ==(*matchIterator2).trainIdx &&(*matchIterator2).queryIdx ==(*matchIterator1).trainIdx)
            {
                symMatches.push_back(DMatch((*matchIterator1).queryIdx,(*matchIterator1).trainIdx,(*matchIterator1).distance));
                break;
            }
        }
    }
}

正如 András Kovács 在相关回答中所说，您还可以使用 RANSAC 计算基本矩阵以使用 cv::findFundamentalMat.

消除异常值

And how can I get each matched point's pixel coordinates in QT creator just like MATLAB?

我希望我理解正确，您希望获得匹配的同系物点的点坐标。我在 symmetryTest 之后提取点的坐标。坐标在关键点内。

for (size_t rows = 0; rows < sym_matches.size(); rows++) {

        float x1 = keypoints_1[sym_matches[rows].queryIdx].pt.x;
        float y1 = keypoints_1[sym_matches[rows].queryIdx].pt.y;        

        float x2 = keypoints_2[sym_matches[rows].trainIdx].pt.x;
        float y2 = keypoints_2[sym_matches[rows].trainIdx].pt.y;

        // Push the coordinates in a vector e.g. std:vector<cv::Point2f>>
    }

您可以对 matches、keypoints1 和 keypoint2 执行相同的操作。

我只想获得高质量的特征点

I want to get high quality feature points only

c++

opencv

feature-extraction

feature-detection