Я пытаюсь обнаружить объект из следующего кода с использованием детектора прибоя, я не хочу рисовать спички, я хочу нарисовать прямоугольник вокруг обнаруженного объекта, но каким-то образом я не могу получить правильную гомографию, пожалуйста, кто-нибудь может указать, где Я иду не так.

#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;
}