opencv实现跟踪鼠标选取的目标

简介

　　本篇讲解opencv video鼠标选中的物体跟踪，使用的是opencv提供的calcOpticalFlowPyrLK。

calcOpticalFlowPyrLK介绍

　　void calcOpticalFlowPyrLK(InputArray prevImg, InputArray nextImg, InputArray prevPts, InputOutputArray nextPts,                              OutputArray status, OutputArray err, Size winSize=Size(21,21), int maxLevel=3,                               TermCriteria criteria=TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, 0.01),                               int flags=0, double minEigThreshold=1e-4 );    prevImg:前一帧video图像。    nextImg:当前video图像。    prevPts:前一帧video图像中被跟踪的坐标点。    nextPts：prevPts保存的坐标点，在当前帧video图像中计算出来的对应坐标，也就是跟踪到的坐标点。    winSize：在每层的搜索窗口的大小。    criteria：算法递归停止的条件。    。。。。。

具体实现

实现代码

#include "opencv2/video/tracking.hpp"#include "opencv2/imgproc/imgproc.hpp"#include "opencv2/highgui/highgui.hpp" #include <iostream>#include <ctype.h>#include <stdio.h>#include <unistd.h>#include <stdlib.h> using namespace cv;using namespace std; vector<Point2f> point1, point2;bool left_mouse = false;Point2f point;int pic_info[4];Mat gray, prevGray, image;const Scalar GREEN = Scalar(0,255,0);int rect_width = 0, rect_height = 0;Point tmpPoint; static void onMouse( int event, int x, int y, int /*flags*/, void* /*param*/ ){Mat mouse_show;image.copyTo(mouse_show); if(event == CV_EVENT_LBUTTONDOWN){pic_info[0] = x;pic_info[1] = y;left_mouse = true;}else if(event == CV_EVENT_LBUTTONUP){rectangle(mouse_show, Point(pic_info[0], pic_info[1]), Point(x, y), GREEN, 2);rect_width = <a href="http://www.opengroup.org/onlinepubs/%3Cspan%20class=" nu19"="" style="text-decoration: none; color: rgb(11, 0, 128); background-image: none; background-position: initial initial; background-repeat: initial initial;">009695399/functions/abs.html">abs(x - pic_info[0]);rect_height = <a href="http://www.opengroup.org/onlinepubs/%3Cspan%20class=" nu19"="" style="text-decoration: none; color: rgb(11, 0, 128); background-image: none; background-position: initial initial; background-repeat: initial initial;">009695399/functions/abs.html">abs(y - pic_info[1]);x = (pic_info[0] + x) / 2;y = (pic_info[1] + y) / 2;point = Point2f((float)x, (float)y);point1.clear();point2.clear();        point1.push_back(point);        imshow("LK Demo", mouse_show);left_mouse = false;}else if((event == CV_EVENT_MOUSEMOVE) && (left_mouse == true)){rectangle(mouse_show, Point(pic_info[0], pic_info[1]), Point(x, y), GREEN, 2);        imshow("LK Demo", mouse_show);}} int main( int argc, char** argv ){    VideoCapture cap;    TermCriteria termcrit(CV_TERMCRIT_ITER|CV_TERMCRIT_EPS, 20, 0.03); //迭代算法的终止条件    Size winSize(31,31);     cap.open(argv[1]);    if(!cap.isOpened()){        cout << "Could not initialize capturing...\n";        return 0;    }     namedWindow( "LK Demo", 1 );    setMouseCallback( "LK Demo", onMouse, 0 );     for(;;){        Mat frame;        cap >> frame;        if( frame.empty() )            break;        frame.copyTo(image);        cvtColor(image, gray, COLOR_BGR2GRAY);        if((!point1.empty())){            vector<uchar> status;            vector<float> err;            if(prevGray.empty())                gray.copyTo(prevGray);            calcOpticalFlowPyrLK(prevGray, gray, point1, point2, status, err, winSize,                                 3, termcrit, 0, 0.001); //使用金字塔Lucas&Kanade方法计算一个稀疏特征集的光流tmpPoint = point2[0];rectangle(image, Point(tmpPoint.x - 20, tmpPoint.y - 20), Point(tmpPoint.x + 20, tmpPoint.y + 20), GREEN, 2);        }         imshow("LK Demo", image);waitKey(100);        std::swap(point2, point1);        cv::swap(prevGray, gray);    }    return 0;}

代码讲解

　　1、首先设置了算法calcOpticalFlowPyrLK将会使用到的递归停止条件(termcrit),关于termcrit的具体讲解，可以看这里有具体讲解:http://blog.csdn.net/yang_xian521/article/details/6905244 ，接着打开视频文件，句柄保存在cap中。然后设置了显示窗口，已经它的鼠标响应函数。

 VideoCapture cap;    TermCriteria termcrit(CV_TERMCRIT_ITER|CV_TERMCRIT_EPS, 20, 0.03); //迭代算法的终止条件    Size winSize(31,31);     cap.open(argv[1]);    if(!cap.isOpened()){        cout << "Could not initialize capturing...\n";        return 0;    }     namedWindow( "LK Demo", 1 );    setMouseCallback( "LK Demo", onMouse, 0 );

　　2、鼠标响应函数，主要做的就是，在当前video帧中画一个矩形，然后计算出该矩形的中心位置坐标,保存到point1中。这个位置坐标就是在calcOpticalFlowPyrLK算法中用来跟踪的点。

static void onMouse( int event, int x, int y, int /*flags*/, void* /*param*/ ){Mat mouse_show;image.copyTo(mouse_show); if(event == CV_EVENT_LBUTTONDOWN){pic_info[0] = x;pic_info[1] = y;left_mouse = true;}else if(event == CV_EVENT_LBUTTONUP){rectangle(mouse_show, Point(pic_info[0], pic_info[1]), Point(x, y), GREEN, 2);rect_width = <a href="http://www.opengroup.org/onlinepubs/%3Cspan%20class=" nu19"="" style="text-decoration: none; color: rgb(11, 0, 128); background-image: none; background-position: initial initial; background-repeat: initial initial;">009695399/functions/abs.html">abs(x - pic_info[0]);rect_height = <a href="http://www.opengroup.org/onlinepubs/%3Cspan%20class=" nu19"="" style="text-decoration: none; color: rgb(11, 0, 128); background-image: none; background-position: initial initial; background-repeat: initial initial;">009695399/functions/abs.html">abs(y - pic_info[1]);x = (pic_info[0] + x) / 2;y = (pic_info[1] + y) / 2;point = Point2f((float)x, (float)y);point1.clear();point2.clear();        point1.push_back(point);        imshow("LK Demo", mouse_show);left_mouse = false;}else if((event == CV_EVENT_MOUSEMOVE) && (left_mouse == true)){rectangle(mouse_show, Point(pic_info[0], pic_info[1]), Point(x, y), GREEN, 2);        imshow("LK Demo", mouse_show);}}

　　3、当用户还没有鼠标框选跟踪目标时候，软件会不断的读取出video的数据，保存到frame中，接着copy一份当前帧数据到gray中，并将gray中的图像灰阶化，然后显示出video frame数据。最后交换了point2和point1中的坐标信息和保存了当前灰阶化后的帧率到prevGray中。

    for(;;){        Mat frame;        cap >> frame;        if( frame.empty() )            break;        frame.copyTo(image);        cvtColor(image, gray, COLOR_BGR2GRAY);        ...........        imshow("LK Demo", image);waitKey(100);        std::swap(point2, point1);        cv::swap(prevGray, gray);    }

　　4、最后当用户框选了跟踪目标之后，也就是point1不为空之后，开始用calcOpticalFlowPyrLK跟踪计算，注意传入该函数的参数:prevGray相当于之前保存的前一帧的数据；gray是当前帧数据；point1是前一帧中被跟踪的目标位置；point2是计算出来的被跟踪目标在当前帧的位置。　　最后用计算出来的在当前帧中，跟踪目标坐标point2作为中心，在当前帧中画出一个40X40的矩形作为标记，最后显示出来。

        if((!point1.empty())){            vector<uchar> status;            vector<float> err;            if(prevGray.empty())                gray.copyTo(prevGray);            calcOpticalFlowPyrLK(prevGray, gray, point1, point2, status, err, winSize,                                 3, termcrit, 0, 0.001); //使用金字塔Lucas&Kanade方法计算一个稀疏特征集的光流tmpPoint = point2[0];rectangle(image, Point(tmpPoint.x - 20, tmpPoint.y - 20), Point(tmpPoint.x + 20, tmpPoint.y + 20), GREEN, 2);        }

效果演示

　　对应的效果演示如下: