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我已经在 OpenCV 中使用 C++ 实现了一个光流代码。但是，我想检测一半图像帧中的光流。我应该编辑哪个部分？是来自下面的这个函数吗？

cvCalcOpticalFlowPyrLK(
  frame1_1C, frame2_1C, 
  pyramid1, pyramid2, 
  frame1_features, 
  frame2_features, 
  number_of_features, 
  optical_flow_window, 
  5, 
  optical_flow_found_feature, 
  optical_flow_feature_error, 
  optical_flow_termination_criteria, 
  0 );
4

2 回答 2

1

不需要。函数本身不需要更改。您需要做的只是将要计算光流的图像部分传递给函数。

您可以定义要对其执行光流计算的图像范围。使用

想要的图像=图像（范围（x1，y1），范围（x2，y2））

以下是基于示例文件夹中的 lkdemo.cpp 的工作代码。唯一值得的改变是

灰色 = 灰色（范围（1,480），范围（1,320））；//给出图像的左半部分

它定义了感兴趣的区域。

#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()
{
    cout << "*** Using OpenCV version " << CV_VERSION <<" ***"<< endl;
    cout << "\n\nUsage: \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"<< endl;
}

int main( int argc, char** argv )
{
    help();
     //Termination of the algo after 20 iterations or accuracy going under 0.03 
    TermCriteria termcrit(CV_TERMCRIT_ITER|CV_TERMCRIT_EPS, 20, 0.3);
    Size subPixWinSize(10,10), winSize(31,31);
    const int MAX_COUNT = 500;
    bool needToInit = false;
    bool nightMode = false;
    //Video capture is from the default device i.e. the webcam
    VideoCapture cap(0);
    if( !cap.isOpened() )
    {
        cout << "Could not initialize capturing...\n";
        return 0;
    }

    namedWindow( "Half screen Optical flow Demo!", 1 );
    Mat gray, prevGray, image;
    vector<Point2f> points[2];

    for(;;)
    {
        Mat frame;

        //Output from the Videocapture is piped to 'frame'
        cap >> frame;
        if( frame.empty() )
            break;

        frame.copyTo(image);
        cvtColor(image, gray, COLOR_BGR2GRAY);

        // Night mode not disabled
        if( nightMode )
            image = Scalar::all(0);
        gray = gray(Range(1,480), Range(1,320));
        if( needToInit || points[0].size()<=5)
        {                  
            goodFeaturesToTrack(gray, points[1], MAX_COUNT, 0.01, 10, Mat(), 3, 0, 0.4);
            cornerSubPix(gray, points[1], subPixWinSize, Size(-1,-1), termcrit);

        }
        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, 3, termcrit, 0, 0.001);
            size_t i, k;

            for( i = k = 0; i < points[1].size(); i++ )
            {
                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);
        }      
        needToInit = false;
        imshow("Half screen Optical flow 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);
    }
    cap.release();
    return 0;
}
于 2015-03-25T23:20:07.270 回答
0

如果您只想在图像的一半中检测光流，那么您可以简单地将图像的一半（frame1_1C，frame2_1C）作为参数。例如，以下代码初始化一个属于 frame1_1C 左半部分的矩阵：

cv::Mat frame1_1C_half(frame1_1C, cv::Range(0, frame1_1C.rows), cv::Range(0, frame1_1C.cols/2));
于 2013-04-10T11:01:20.413 回答