OpenCV 3.2 Tracking 物体跟踪

跟踪就是在连续视频帧中定位物体，通常的跟踪算法包括以下几类：

1. Dense OpticalFlow　稠密光流

2. Sparse OpticalFlow　稀疏光流　最典型的如KLT算法（Kanade-Lucas-Tomshi）

3. Kalman Filter

4. Meanshift andCamshift

5. Multiple objecttracking

需要注意跟踪和识别的区别，通常来说跟踪可以比识别快很多，且跟踪失败了可以找回来。

OpenCV 3以后实现了很多追踪算法，都实现在contrib模块中，安装参考。

下面code实现了跟踪笔记本摄像头画面中的固定区域物体，可以选用OpenCV实现的算法

#include<opencv2/opencv.hpp>

#include<opencv2/tracking.hpp>

 

usingnamespace std;

usingnamespace cv;

 

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

  // can change to BOOSTING, MIL, KCF (OpenCV 3.1), TLD, MEDIANFLOW, orGOTURN (OpenCV 3.2)

  Ptr<Tracker> tracker = Tracker::create("MEDIANFLOW");

  VideoCapture video(0);

  if(!video.isOpened()){

    cerr << "cannot read video!" << endl;

    return -1;

  }

  Mat frame;

  video.read(frame);

  Rect2d box(270,120,180, 260);

  tracker->init(frame, box);

  while(video.read(frame)){

    tracker->update(frame, box);

    rectangle(frame, box, Scalar(255,0,0), 2, 1);

    imshow("Tracking", frame);

    int k=waitKey(1);

    if(k==27) break;

  }

}

这里介绍一下使用OpenCV进行目标跟踪的方法，之前用过一点。opencv中目标跟踪的一些比较新的方法（比如MIL、KCF、TLD等）都在opencv_contrib库里，所以首先你需要安装它，详见Opencv3.1.0+opencv_contrib配置及使用SIFT测试 。 
关于tracking这一块可参考Opencv的官网 Tracking API 、Introduction to OpenCV Tracker 。 
如果只是想要测试下非常简单，官网都给了例程；要深入了解其原理，查看相关论文即可。关于其效果的话，看你的使用场合和怎么理解了。 
这里贴一下我根据例程稍作修改的测试程序。 
源码：

#include <opencv2/core/utility.hpp>#include <opencv2/tracking.hpp>#include <opencv2/videoio.hpp>#include <opencv2/highgui.hpp>#include <iostream>#include <cstring>using namespace std;using namespace cv;int main(int argc, char** argv) {    // show help    /*    if (argc<2) {        cout <<            " Usage: tracker <video_name>\n"            " examples:\n"            " example_tracking_kcf Bolt/img/%04d.jpg\n"            " example_tracking_kcf faceocc2.webm\n"            << endl;        return 0;    }    */    // declares all required variables    Rect2d roi;    Mat frame;    // create a tracker object    Ptr<Tracker> tracker = Tracker::create("KCF");    // set input video//  std::string video = argv[1];    VideoCapture cap("dount.avi");    // get bounding box    cap >> frame;    roi = selectROI("tracker", frame);    //quit if ROI was not selected    if (roi.width == 0 || roi.height == 0)        return 0;    // initialize the tracker    tracker->init(frame, roi);    // perform the tracking process    printf("Start the tracking process, press ESC to quit.\n");    for (;; ) {        // get frame from the video        cap >> frame;        // stop the program if no more images        if (frame.rows == 0 || frame.cols == 0)            break;        // update the tracking result        tracker->update(frame, roi);        // draw the tracked object        rectangle(frame, roi, Scalar(255, 0, 0), 2, 1);        // show image with the tracked object        imshow("tracker", frame);        //quit on ESC button        if (waitKey(1) == 27)break;    }    return 0;}

#include <opencv2/core/utility.hpp>

#include <opencv2/tracking.hpp>

#include <opencv2/videoio.hpp>

#include <opencv2/highgui.hpp>

#include <iostream>

#include <cstring>

using namespace std;

using namespace cv;

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

// show help

if(argc<2){

cout<<

" Usage: tracker <video_name>\n"

" examples:\n"

" example_tracking_kcf Bolt/img/%04d.jpg\n"

" example_tracking_kcf faceocc2.webm\n"

<< endl;

return 0;

}

// declares all required variables

Rect2d roi;

Mat frame;

// create a tracker object

Ptr<Tracker> tracker = Tracker::create("KCF" );

// set input video

std::string video = argv[1];

VideoCapture cap(video);

// get bounding box

cap >> frame;

roi=selectROI("tracker",frame);

//quit if ROI was not selected

if(roi.width==0 || roi.height==0)

return 0;

// initialize the tracker

tracker->init(frame,roi);

// perform the tracking process

printf("Start the tracking process, press ESC to quit.\n");

for ( ;; ){

// get frame from the video

cap >> frame;

// stop the program if no more images

if(frame.rows==0 || frame.cols==0)

break;

// update the tracking result

tracker->update(frame,roi);

// draw the tracked object

rectangle( frame, roi,Scalar( 255, 0, 0 ), 2, 1 );

// show image with the tracked object

imshow("tracker",frame);

//quit on ESC button

if(waitKey(1)==27)break;

}

return 0;

}