OpenCV关于稀疏光流跟踪的演示程序以及一些错误提示

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intmain(){Matsrc0 = imread("0.jpg",CV_LOAD_IMAGE_COLOR);Matsrc1 = imread("1.jpg",CV_LOAD_IMAGE_COLOR);Matgray0;Matgray1;int corner_count = 5000;vector<Point2f> corners0;vector<Point2f> corners1;cvtColor(src0,gray0,CV_BGR2GRAY);goodFeaturesToTrack(gray0,corners0,corner_count,0.01,5,Mat(),3,false,0.04);cornerSubPix(gray0,corners0,Size(10,10),Size(-1,-1),TermCriteria(CV_TERMCRIT_ITER|CV_TERMCRIT_EPS,20,0.03));cvtColor(src1,gray1,CV_BGR2GRAY);goodFeaturesToTrack(gray1,corners1,corner_count,0.01,5,Mat(),3,false,0.04);cornerSubPix(gray1,corners1,Size(10,10),Size(-1,-1),TermCriteria(CV_TERMCRIT_ITER|CV_TERMCRIT_EPS,20,0.03));vector<Point2f>::iterator it;for(it = corners0.begin(); it != corners0.end();it++){circle(src0,*it,1,Scalar(255,0,255),1,8,0);}for(it = corners1.begin(); it != corners1.end();it++){circle(src0,*it,1,Scalar(255,0,255),1,8,0);}imshow("src0",src0);waitKey(0);system("pause");return0;}

错误提示：goodFeaturesToTrack函数中mask参数如果填入的是0，VS编译出错；mask的值设置为Mat()则可以正常使用。

使用光流算法的一点儿感想：处理耗时较多。

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