c - opencv跟踪点

Question

我想将点放在视频帧的坐标上，我确定并跟踪它们，就像 opencv 示例“lk demo”

我不明白该示例。哪些函数放置点并跟踪它们

感谢您的建议

/* Demo of modified Lucas-Kanade optical flow algorithm.
   See the printf below */

#ifdef _CH_
#pragma package <opencv>
#endif

#define CV_NO_BACKWARD_COMPATIBILITY

#ifndef _EiC
#include "cv.h"
#include "highgui.h"
#include <stdio.h>
#include <ctype.h>
#endif

IplImage *image = 0, *grey = 0, *prev_grey = 0, *pyramid = 0, *prev_pyramid = 0, *swap_temp;

int win_size = 10;
const int MAX_COUNT = 500;
CvPoint2D32f* points[2] = {0,0}, *swap_points;
char* status = 0;
int count = 0;
int need_to_init = 0;
int night_mode = 0;
int flags = 0;
int add_remove_pt = 0;
CvPoint pt;


void on_mouse( int event, int x, int y, int flags, void* param )
{
    if( !image )
        return;

    if( image->origin )
        y = image->height - y;

    if( event == CV_EVENT_LBUTTONDOWN )
    {
        pt = cvPoint(x,y);
        add_remove_pt = 1;
    }
}


int main( int argc, char** argv )
{
    CvCapture* capture = 0;

    if( argc == 1 || (argc == 2 && strlen(argv[1]) == 1 && isdigit(argv[1][0])))
        capture = cvCaptureFromCAM( argc == 2 ? argv[1][0] - '0' : 0 );
    else if( argc == 2 )
        capture = cvCaptureFromAVI( argv[1] );

    if( !capture )
    {
        fprintf(stderr,"Could not initialize capturing...\n");
        return -1;
    }

    /* print a welcome message, and the OpenCV version */
    printf ("Welcome to lkdemo, using OpenCV version %s (%d.%d.%d)\n",
        CV_VERSION,
        CV_MAJOR_VERSION, CV_MINOR_VERSION, CV_SUBMINOR_VERSION);

    printf( "Hot keys: \n"
            "\tESC - quit the program\n"
            "\tr - auto-initialize tracking\n"
            "\tc - delete all the points\n"
            "\tn - switch the \"night\" mode on/off\n"
            "To add/remove a feature point click it\n" );

    cvNamedWindow( "LkDemo", 0 );
    cvSetMouseCallback( "LkDemo", on_mouse, 0 );

    for(;;)
    {
        IplImage* frame = 0;
        int i, k, c;

        frame = cvQueryFrame( capture );
        if( !frame )
            break;

        if( !image )
        {
            /* allocate all the buffers */
            image = cvCreateImage( cvGetSize(frame), 8, 3 );
            image->origin = frame->origin;
            grey = cvCreateImage( cvGetSize(frame), 8, 1 );
            prev_grey = cvCreateImage( cvGetSize(frame), 8, 1 );
            pyramid = cvCreateImage( cvGetSize(frame), 8, 1 );
            prev_pyramid = cvCreateImage( cvGetSize(frame), 8, 1 );
            points[0] = (CvPoint2D32f*)cvAlloc(MAX_COUNT*sizeof(points[0][0]));
            points[1] = (CvPoint2D32f*)cvAlloc(MAX_COUNT*sizeof(points[0][0]));
            status = (char*)cvAlloc(MAX_COUNT);
            flags = 0;
        }

        cvCopy( frame, image, 0 );
        cvCvtColor( image, grey, CV_BGR2GRAY );

        if( night_mode )
            cvZero( image );

        if( need_to_init )
        {
            /* automatic initialization */
            IplImage* eig = cvCreateImage( cvGetSize(grey), 32, 1 );
            IplImage* temp = cvCreateImage( cvGetSize(grey), 32, 1 );
            double quality = 0.01;
            double min_distance = 10;

            count = MAX_COUNT;
            cvGoodFeaturesToTrack( grey, eig, temp, points[1], &count,
                                   quality, min_distance, 0, 3, 0, 0.04 );
            cvFindCornerSubPix( grey, points[1], count,
                cvSize(win_size,win_size), cvSize(-1,-1),
                cvTermCriteria(CV_TERMCRIT_ITER|CV_TERMCRIT_EPS,20,0.03));
            cvReleaseImage( &eig );
            cvReleaseImage( &temp );

            add_remove_pt = 0;
        }
        else if( count > 0 )
        {
            cvCalcOpticalFlowPyrLK( prev_grey, grey, prev_pyramid, pyramid,
                points[0], points[1], count, cvSize(win_size,win_size), 3, status, 0,
                cvTermCriteria(CV_TERMCRIT_ITER|CV_TERMCRIT_EPS,20,0.03), flags );
            flags |= CV_LKFLOW_PYR_A_READY;
            for( i = k = 0; i < count; i++ )
            {
                if( add_remove_pt )
                {
                    double dx = pt.x - points[1][i].x;
                    double dy = pt.y - points[1][i].y;

                    if( dx*dx + dy*dy <= 25 )
                    {
                        add_remove_pt = 0;
                        continue;
                    }
                }

                if( !status[i] )
                    continue;

                points[1][k++] = points[1][i];
                cvCircle( image, cvPointFrom32f(points[1][i]), 3, CV_RGB(0,255,0), -1, 8,0);
            }
            count = k;
        }

        if( add_remove_pt && count < MAX_COUNT )
        {
            points[1][count++] = cvPointTo32f(pt);
            cvFindCornerSubPix( grey, points[1] + count - 1, 1,
                cvSize(win_size,win_size), cvSize(-1,-1),
                cvTermCriteria(CV_TERMCRIT_ITER|CV_TERMCRIT_EPS,20,0.03));
            add_remove_pt = 0;
        }

        CV_SWAP( prev_grey, grey, swap_temp );
        CV_SWAP( prev_pyramid, pyramid, swap_temp );
        CV_SWAP( points[0], points[1], swap_points );
        need_to_init = 0;
        cvShowImage( "LkDemo", image );

        c = cvWaitKey(10);
        if( (char)c == 27 )
            break;
        switch( (char) c )
        {
        case 'r':
            need_to_init = 1;
            break;
        case 'c':
            count = 0;
            break;
        case 'n':
            night_mode ^= 1;
            break;
        default:
            ;
        }
    }

    cvReleaseCapture( &capture );
    cvDestroyWindow("LkDemo");

    return 0;
}

#ifdef _EiC
main(1,"lkdemo.c");
#endif

Answer 1

算法的第一次迭代:您只需找到一些您想要跟踪的特征。它们存储在点数组中，并在图像上用绿点标记以供您跟踪。然后，在后续迭代中，该算法使用光流函数来跟踪点的移动。

cvGoodFeaturesToTrack 和 cvFindCornerSubPix 正在初始化您关注的点，cvCalcOpticalFlowPyrLK 跟踪给定点的运动，cvCircle 将绿点放在点所在的位置。

希望这有帮助。