使用SURF进行手部检测

Question

我正在使用SURF算法进行实时手部检测。我会让用户将手放在一个矩形中，然后将其用作我的对象，并使用该对象在第一帧中找到手，在下一个循环中将检测到的手设置为我的对象，依此类推...... 但运行时显示以下错误

OpenCV错误：cvFindHomography中的断言失败（计数＆gt; = 4），文件/build/buildd/opencv-2.4.8+dfsg1/modules/calib3d/src/fundam.cpp，第235行 在抛出'cv :: Exception'的实例后终止调用   what（）：/ build / buildd / opencv-2.4.8 + dfsg1 /modules / calib3d / src / fedam.cpp：235：错误：（-215）count＆gt; = 4 in function cvFindHomography

这是我的代码：

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

using namespace cv;
using namespace std;
int main()
{

 char k;

 Mat img_object,img_scene,frame;

 VideoCapture cap(0);

 if(cap.isOpened()==0)
{
    cout<<"ERROR";
    return -1;
}
while(1)
{
    cap>>frame;
    rectangle(frame,Point(100,100),Point(300,300),(0,255,0),4,8,0);
    imshow("gig",frame);
    k=waitKey(1);
     if(k=='q')
     {
         Mat img_object1(frame,Rect(25,25,100,100));
         img_object=img_object1.clone();
         cvtColor(img_object,img_object,CV_BGR2GRAY);
        break;
    }

}


while(1)
{
    cap>>img_scene;

    cvtColor(img_scene,img_scene,CV_BGR2GRAY);

    int minHessian = 50;

    SurfFeatureDetector detector( minHessian );

    std::vector<KeyPoint> keypoints_object, keypoints_scene;

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


     SurfDescriptorExtractor extractor;

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


     FlannBasedMatcher matcher;
     std::vector< DMatch > matches;
     matcher.match( descriptors_object, descriptors_scene, matches );

     double max_dist = 0; double min_dist = 100;


     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 );


     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 );


     std::vector<Point2f> obj;
     std::vector<Point2f> scene;

     for( int i = 0; i < good_matches.size(); i++ )
     {

         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 );


     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);


     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 );



    Mat nn(img_scene,Rect((scene_corners[0] ).x,(scene_corners[0] ).y,(scene_corners[2] ).x,(scene_corners[2]).y));

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


    img_object=nn.clone();

      k=waitKey(1);
    if(k=='q')
    {
        break;
    }
} 

  return 0;
}