Ich versuche ein Objekt anhand des folgenden Codes mit Surf Detector zu erkennen, ich möchte keine Übereinstimmungen zeichnen, ich möchte ein Rechteck um das erkannte Objekt zeichnen, aber irgendwie kann ich keine korrekte Homografie erhalten. Kann jemand darauf hinweisen, wo Ich gehe falsch.

#include <stdio.h>
#include <iostream>
#include "opencv2/core/core.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/calib3d/calib3d.hpp"

using namespace cv;

int main()
{
    Mat object = imread( "sample.jpeg", CV_LOAD_IMAGE_GRAYSCALE );

    if( !object.data )
    {
        std::cout<< "Error reading object " << std::endl;
        return -1;
    }

    //Detect the keypoints using SURF Detector
    int minHessian = 500;

    SurfFeatureDetector detector( minHessian );
    std::vector<KeyPoint> kp_object;

    detector.detect( object, kp_object );

    //Calculate descriptors (feature vectors)
    SurfDescriptorExtractor extractor;
    Mat des_object;

    extractor.compute( object, kp_object, des_object );

    FlannBasedMatcher matcher;

    VideoCapture cap(0);

    namedWindow("Good Matches",0);
    cvResizeWindow("Good Matches",800,800);

    std::vector<Point2f> obj_corners(4);

    //Get the corners from the object
    obj_corners[0] = (cvPoint(0,0));
    obj_corners[1] = (cvPoint(object.cols,0));
    obj_corners[2] = (cvPoint(object.cols,object.rows));
    obj_corners[3] = (cvPoint(0, object.rows));

    char key = 'a';
    int framecount = 0;
    while (key != 27)
    {
        Mat frame;
        cap >> frame;

        if (framecount < 5)
        {
            framecount++;
            continue;
        }

        Mat des_image, img_matches;
        std::vector<KeyPoint> kp_image;
        std::vector<vector<DMatch > > matches;
        std::vector<DMatch > good_matches;
        std::vector<Point2f> obj;
        std::vector<Point2f> scene;
        std::vector<Point2f> scene_corners(4);
        Mat H;
        Mat image;

        cvtColor(frame, image, CV_RGB2GRAY);

        detector.detect( image, kp_image );
       extractor.compute( image, kp_image, des_image );

        matcher.knnMatch(des_object, des_image, matches, 2);

       for(int i = 0; i < min(des_image.rows-1,(int) matches.size()); i++) //THIS LOOP IS SENSITIVE TO SEGFAULTS
      {
            if((matches[i][0].distance < 0.6*(matches[i][1].distance)) && ((int) matches[i].size()<=2 && (int) matches[i].size()>0))
         {
              good_matches.push_back(matches[i][0]);
            }
       }

        //Draw only "good" matches
     //  drawMatches( object, kp_object, image, kp_image, good_matches, img_matches, Scalar::all(-1), Scalar::all(-1), vector<char>(),DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS);

        if (good_matches.size() >= 4)
        {
            for( int i = 0; i < good_matches.size(); i++ )
            {
                //Get the keypoints from the good matches
                obj.push_back( kp_object[ good_matches[i].queryIdx ].pt );
                scene.push_back( kp_image[ good_matches[i].trainIdx ].pt );
           }

            H = findHomography( obj, scene, CV_RANSAC );

            perspectiveTransform( obj_corners, scene_corners, H);

            //Draw lines between the corners (the mapped object in the scene image )
            line( image, scene_corners[0] + Point2f( object.cols, 0), scene_corners[1] + Point2f( object.cols, 0), Scalar(0, 255, 0), 4 );
            line( image, scene_corners[1] + Point2f( object.cols, 0), scene_corners[2] + Point2f( object.cols, 0), Scalar( 0, 255, 0), 4 );
            line( image, scene_corners[2] + Point2f( object.cols, 0), scene_corners[3] + Point2f( object.cols, 0), Scalar( 0, 255, 0), 4 );
            line( image, scene_corners[3] + Point2f( object.cols, 0), scene_corners[0] + Point2f( object.cols, 0), Scalar( 0, 255, 0), 4 );
        }

        //Show detected matches
        imshow( "Good Matches", image );

        key = waitKey(1);
    }
    return 0;
}