opencv光流法对特定区域进行跟踪

本例子使用了opencv3.0，利用鼠标选择矩形框，然后对选择的区域进行跟踪

//---------------------------------光流法对特定区域进行跟踪-----------------#include <iostream>#include <opencv2/opencv.hpp>#include <opencv2/video.hpp>#include <opencv2/highgui.hpp>#include <opencv2/imgproc.hpp>#include <opencv2/core/core.hpp>#include <cstdio>using namespace std;using namespace cv;//------------------------------------【全局函数声明】------------------------------void tracking(Mat &frame,Mat &output);//-------------------------------------【全局变量声明】-------------------------------string window_name = "flow tracking";Mat gray;                                                  //当前帧图片Mat gray_prev;                                             //预测帧图片Mat image;vector<Point2f> points[2];                                 //point0为特征点的原来位置，point1位特征点新的位置vector<uchar> status;                                      //跟踪特征的状态，特征的流发现为1，否则为0vector<float> err;Rect selection;Point origin;                               //定义原点，Point pointCentral;bool selectObject = false;int trackObject = 0;static void onMouse(int event,int x,int y,int ,void*){    if(selectObject)    {        selection.x=MIN(x,origin.x);        selection.y=MIN(y,origin.y);        selection.width = abs(x-origin.x);        selection.height = abs(y-origin.y);        selection &= Rect(0,0,image.cols,image.rows);     //保证selection在画面的里边    }    switch (event)    {        case EVENT_LBUTTONDOWN:            origin = Point(x,y);            selection = Rect(x,y,0,0);            selectObject = true;            break;        case EVENT_LBUTTONUP:            selectObject = false;            if(selection.width > 0 && selection.height > 0)            {                trackObject = -1;            }            break;    }}int main() {    Mat frame;//定义视频帧    Mat result;//定义结果    VideoCapture capture(0);                       //读取视频    if(capture.isOpened())                                 //如果视频打开成功，则进行以下步骤    {        while(true)        {            capture>>frame;                                //读取当前视频帧到frame中            frame.copyTo(image);            setMouseCallback(window_name,onMouse,0);            if(!frame.empty())                             //如果当前帧不为空            {                tracking(image,result);                    //调用定义的函数，开始跟踪            }            else            {                cout<<"没有视频帧";                          //否则报错                break;            }            int c = waitKey(50);                           //每隔50ms刷新一次            if((char)c == 27)                              //用户在50ms以内按下“esc”这个按键，则跳出循环            {                break;            }            switch (c)            {                case 'c':                                  //停止追踪                    trackObject = 0;                    break;                default:                    break;            }        }    }    return 0;}void tracking(Mat &frame,Mat &output){    cvtColor(frame,gray,COLOR_BGR2GRAY);                   //将当前的视频帧转换为灰度图，保存到gray中    frame.copyTo(output);                                  //拷贝当前帧到输出output中    if(selectObject)    {        rectangle(output,Point(selection.x,selection.y),Point(selection.x+selection.width,                                                              selection.y+selection.height),Scalar(255,0,0));    }    //鼠标抬起时，进行检测    if(trackObject == -1)    {        //选取selection区域的中心点为初始点        pointCentral = Point(selection.x+selection.width/2,selection.y+selection.height/2);        points[0].push_back(pointCentral);        if(gray_prev.empty())        {            gray.copyTo(gray_prev);                            //如果前一帧为空，则复制当前帧到前一帧        }        if(points[0].size() == 0)        {            cout<<"这里错了；额"<<endl;        }        calcOpticalFlowPyrLK(gray_prev,gray, points[0],points[1],status,err);        //绘制跟踪框图，以point【1】为中心，与selection的长和宽相同的矩形        rectangle(output,Point(points[1][0].x - selection.width/2,points[1][0].y+selection.height/2),                  Point(points[1][0].x + selection.width/2,points[1][0].y-selection.height/2),Scalar(255,0,0),3,8,0);        //画线，在output图像上，点initial[i]到点points[1][i]的直线段，颜色为（0，0，255）        line(output,points[0][0],points[1][0],Scalar(0,0,255),4,8);        //画圆，在output图像上，圆心为point[1][i],半径为3，圆的颜色为（0，255，0）        circle(output,points[1][0],6,Scalar(0,255,0),-1,8);        swap(points[1],points[0]);                             //交换特征点容器points[0]和特征点容器points[1]        swap(gray_prev,gray);                                  //把当前帧的图像赋值为上一帧图像，以便传入下一次迭代的calcOpticalFlowPyrLK    }    imshow(window_name,output);                            //在窗口window_name展示输出的结果}