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有谁熟悉这个错误？我实时测试了一个冲浪描述符，它运行良好，但几秒钟后它崩溃了，我得到了这个错误。在此处输入图像描述 在此处输入图像描述

当没有检测到点时，它是相关的。我再次运行我的代码，检测到的对象停留了 2 分钟以上，仍然没有错误。但是当我移除对象并且没有积分时，它会在 40 秒后再次崩溃。

#include <stdio.h>
#include <iostream>
#include <fstream>
#include <string>
#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"
#include "opencv2/nonfree/features2d.hpp"
#include "opencv2/legacy/legacy.hpp"

using namespace cv;
using namespace std;

char key = 'a';
int framecount = 0;

SurfFeatureDetector detector(1000);
SurfDescriptorExtractor extractor;
FlannBasedMatcher matcher;

Mat frame, des_object, image;
Mat des_image, img_matches, H;

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

int main()
{             
            //reference image
    Mat object = imread("D:/milo.jpg", CV_LOAD_IMAGE_GRAYSCALE );

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

            //compute detectors and descriptors of reference image
detector.detect( object, kp_object );
extractor.compute( object, kp_object, des_object );

            //create video capture object
CvCapture* capture = cvCaptureFromCAM(0);
cvSetCaptureProperty(capture, CV_CAP_PROP_FRAME_WIDTH, 270);
cvSetCaptureProperty(capture, CV_CAP_PROP_FRAME_HEIGHT, 190);

//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 );

            //wile loop for real time detection
while (key != 27)
{
    Mat frame;
    frame = cvQueryFrame(capture);

    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);


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

    //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 (goodMatchesCounter >= 4)
    {

        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], scene_corners[1], Scalar( 0, 0, 0), 4 );
        line( image, scene_corners[1], scene_corners[2], Scalar( 0, 0, 0),
                         4 );
        line( image, scene_corners[2], scene_corners[3], Scalar( 0, 0, 0),
                         4 );
        line( image, scene_corners[3], scene_corners[0], Scalar( 0, 0, 0),
                         4 );

    }

    //Show detected matches
    imshow( "Good Matches", image );
    key = waitKey(1);
   }
    return 0;
  }
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