Question

如何在lkdemo.pp（klt光流跟踪器opencv示例）源代码中添加基于roi的选择？我希望在第一帧中选择roi并跟踪在roi中选择的特征点。

#include "opencv2/video/tracking.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"

#include <iostream>
#include <ctype.h>

using namespace cv;
using namespace std;

static void help()
{
    // print a welcome message, and the OpenCV version
    cout << "\nThis is a demo of Lukas-Kanade optical flow lkdemo(),\n"
            "Using OpenCV version " << CV_VERSION << endl;

}

Point2f point;
bool addRemovePt = false;

static void onMouse( int event, int x, int y, int , void* )
{
    if( event == CV_EVENT_LBUTTONDOWN )
    {
        point = Point2f((float)x, (float)y);
        addRemovePt = true;
    }
}

int main( int argc, char** argv )
{
    help();

    VideoCapture cap(CV_CAP_ANY);
    TermCriteria termcrit(CV_TERMCRIT_ITER|CV_TERMCRIT_EPS, 20, 0.03);
    Size subPixWinSize(10,10), winSize(61,61);

    const int MAX_COUNT = 500;
    bool needToInit = false;
    bool nightMode = false;

    //if( argc == 1 || (argc == 2 && strlen(argv[1]) == 1 && isdigit(argv[1][0])))
        //cap.open(argc == 2 ? argv[1][0] - '0' : 0);
    //else if( argc == 2 )
        //cap.open(argv[1]);

    if( !cap.isOpened() )
    {
        cout << "Could not initialize capturing...\n";
        return 0;
    }

    namedWindow( "LK Demo", 1 );
    setMouseCallback( "LK Demo", onMouse, 0 );

    Mat gray, prevGray, image;
    vector<Point2f> points[2];

    for(;;)
    {
        Mat frame;
        cap >> frame;
        if( frame.empty() )
            break;

        frame.copyTo(image);
        cvtColor(image, gray, COLOR_RGB2GRAY);

        if( nightMode )
            image = Scalar::all(0);

        if( needToInit )
        {
            // automatic initialization
            goodFeaturesToTrack(gray, points[1], MAX_COUNT, 0.01, 10, Mat(), 3, 0, 0.04);
            cornerSubPix(gray, points[1], subPixWinSize, Size(-1,-1), termcrit);
            addRemovePt = false;
        }
        else if( !points[0].empty() )
        {
            vector<uchar> status;
            vector<float> err;
            if(prevGray.empty())
                gray.copyTo(prevGray);
            calcOpticalFlowPyrLK(prevGray, gray, points[0], points[1], status, err, winSize,10, termcrit, 0, 0.001);
            size_t i, k;
            for( i = k = 0; i < points[1].size(); i++ )
            {
                if( addRemovePt )
                {
                    if( norm(point - points[1][i]) <= 5 )
                    {
                        addRemovePt = false;
                        continue;
                    }
                }

                if( !status[i] )
                    continue;

                points[1][k++] = points[1][i];
                circle( image, points[1][i], 3, Scalar(0,255,0), -1, 8);
            }
            points[1].resize(k);
        }

        if( addRemovePt && points[1].size() < (size_t)MAX_COUNT )
        {
            vector<Point2f> tmp;
            tmp.push_back(point);
            cornerSubPix( gray, tmp, winSize, cvSize(-1,-1), termcrit);
            points[1].push_back(tmp[0]);
            addRemovePt = false;
        }

        needToInit = false;
        imshow("LK Demo", image);

        char c = (char)waitKey(10);
        if( c == 27 )
            break;
        switch( c )
        {
        case 'r':
            needToInit = true;
            break;
        case 'c':
            points[0].clear();
            points[1].clear();
            break;
        case 'n':
            nightMode = !nightMode;
            break;
        }

        std::swap(points[1], points[0]);
        cv::swap(prevGray, gray);
    }

    return 0;
}

Answer 1

以下是我在这些情况下使用的内容：

void SelectNewTemplate(int event, int posx, int posy, int flags, void* userdata)
{
    if( event == EVENT_MBUTTONDOWN )
    {
        waitKey();
    }
    if( event == CV_EVENT_LBUTTONDOWN )
    {
        x1pt = posx;
        y1pt = posy;
    }
    if( event == CV_EVENT_LBUTTONUP )
    {
        x2pt = posx;
        y2pt = posy;

        Rect newTemp(x1pt, y1pt, (x2pt - x1pt), (y2pt - y1pt));
        Mat imgROI = frame(newTemp);
    }
}

用法：用鼠标中键暂停视频，然后离开clic，拖动然后放开，按任意键继续。

之后，您可以在新的投资回报率图片上计算您的功能：imgROI。

希望有所帮助，托马斯

基于ROI的KLT光学跟踪器在opencv

1 个答案: