【OpenCV C++】光流法进行运动目标检测

    #include <opencv2/video/video.hpp>
    #include <opencv2/highgui/highgui.hpp>
    #include <opencv2/imgproc/imgproc.hpp>
    #include <opencv2/core/core.hpp>
    #include <iostream>
    #include <cstdio>
    
    using namespace std;
    using namespace cv;
    
    //-----------------------------------【全局函数声明】-----------------------------------------
    //		描述：声明全局函数
    //-------------------------------------------------------------------------------------------------
    void tracking(Mat& frame, Mat& output);
    bool addNewPoints();
    bool acceptTrackedPoint(int i);
    
    //-----------------------------------【全局变量声明】-----------------------------------------
    //		描述：声明全局变量
    //-------------------------------------------------------------------------------------------------
    string window_name = "optical flow tracking";
    Mat gray;	// 当前图片
    Mat gray_prev;	// 预测图片
    vector<Point2f> points[2];	// point0为特征点的原来位置，point1为特征点的新位置
    vector<Point2f> initial;	// 初始化跟踪点的位置
    vector<Point2f> features;	// 检测的特征
    int maxCount = 500;	// 检测的最大特征数
    double qLevel = 0.01;	// 特征检测的等级
    double minDist = 10.0;	// 两特征点之间的最小距离
    vector<uchar> status;	// 跟踪特征的状态，特征的流发现为1，否则为0
    vector<float> err;
    
    //-----------------------------------【main( )函数】--------------------------------------------
    //		描述：控制台应用程序的入口函数，我们的程序从这里开始
    //-------------------------------------------------------------------------------------------------
    int main()
    {
    
    	Mat frame;
    	Mat result;
    
    	VideoCapture capture(0);
    
    	if (capture.isOpened())	// 摄像头读取文件开关
    	{
    		while (true)
    		{
    			capture >> frame;
    
    			if (!frame.empty())
    			{
    				tracking(frame, result);
    			}
    			else
    			{
    				printf(" --(!) No captured frame -- Break!");
    				break;
    			}
    
    			int c = waitKey(50);
    			if ((char)c == 27)
    			{
    				break;
    			}
    		}
    	}
    	return 0;
    }
    
    //-------------------------------------------------------------------------------------------------
    // function: tracking
    // brief: 跟踪
    // parameter: frame	输入的视频帧
    //			  output 有跟踪结果的视频帧
    // return: void
    //-------------------------------------------------------------------------------------------------
    void tracking(Mat& frame, Mat& output)
    {
    
    	//此句代码的OpenCV3版为：
    	cvtColor(frame, gray, COLOR_BGR2GRAY);
    	//此句代码的OpenCV2版为：
    	//cvtColor(frame, gray, CV_BGR2GRAY);
    
    	frame.copyTo(output);
    
    	// 添加特征点
    	if (addNewPoints())
    	{
    		goodFeaturesToTrack(gray, features, maxCount, qLevel, minDist);
    		points[0].insert(points[0].end(), features.begin(), features.end());
    		initial.insert(initial.end(), features.begin(), features.end());
    	}
    
    	if (gray_prev.empty())
    	{
    		gray.copyTo(gray_prev);
    	}
    	// l-k光流法运动估计
    	calcOpticalFlowPyrLK(gray_prev, gray, points[0], points[1], status, err);
    	// 去掉一些不好的特征点
    	int k = 0;
    	for (size_t i = 0; i < points[1].size(); i++)
    	{
    		if (acceptTrackedPoint(i))
    		{
    			initial[k] = initial[i];
    			points[1][k++] = points[1][i];
    		}
    	}
    	points[1].resize(k);
    	initial.resize(k);
    	// 显示特征点和运动轨迹
    	for (size_t i = 0; i < points[1].size(); i++)
    	{
    		line(output, initial[i], points[1][i], Scalar(0, 0, 255));
    		circle(output, points[1][i], 3, Scalar(0, 255, 0), -1);
    	}
    
    	// 把当前跟踪结果作为下一此参考
    	swap(points[1], points[0]);
    	swap(gray_prev, gray);
    
    	imshow(window_name, output);
    }
    
    //-------------------------------------------------------------------------------------------------
    // function: addNewPoints
    // brief: 检测新点是否应该被添加
    // parameter:
    // return: 是否被添加标志
    //-------------------------------------------------------------------------------------------------
    bool addNewPoints()
    {
    	return points[0].size() <= 10;
    }
    
    //-------------------------------------------------------------------------------------------------
    // function: acceptTrackedPoint
    // brief: 决定哪些跟踪点被接受
    // parameter:
    // return:
    //-------------------------------------------------------------------------------------------------
    bool acceptTrackedPoint(int i)
    {
    	return status[i] && ((abs(points[0][i].x - points[1][i].x) + abs(points[0][i].y - points[1][i].y)) > 2);
    }