Using MultiTracker

Goal

In this tutorial you will learn how to

• Create a MultiTracker object.
• Track several objects at once using the MultiTracker object.

Source Code

/*----------------------------------------------
 * Usage:
 * example_tracking_multitracker <video_name> [algorithm]
 *
 * example:
 * example_tracking_multitracker Bolt/img/%04d.jpg
 * example_tracking_multitracker faceocc2.webm KCF
 *--------------------------------------------------*/

#include <opencv2/core/utility.hpp>
#include <opencv2/tracking.hpp>
#include <opencv2/videoio.hpp>
#include <opencv2/highgui.hpp>
#include <iostream>
#include <cstring>
#include <ctime>

using namespace std;
using namespace cv;

int main( int argc, char** argv ){
  // show help
  if(argc<2){
    cout<<
      " Usage: example_tracking_multitracker <video_name> [algorithm]\n"
      " examples:\n"
      " example_tracking_multitracker Bolt/img/%04d.jpg\n"
      " example_tracking_multitracker faceocc2.webm MEDIANFLOW\n"
      << endl;
    return 0;
  }

  // set the default tracking algorithm
  std::string trackingAlg = "KCF";

  // set the tracking algorithm from parameter
  if(argc>2)
    trackingAlg = argv[2];

  // create the tracker
  MultiTracker trackers(trackingAlg);

  // container of the tracked objects
  vector<Rect2d> objects;

  // set input video
  std::string video = argv[1];
  VideoCapture cap(video);

  Mat frame;

  // get bounding box
  cap >> frame;
  selectROI("tracker",frame,objects);

  //quit when the tracked object(s) is not provided
  if(objects.size()<1)
    return 0;

  // initialize the tracker
  trackers.add(frame,objects);

  // do the tracking
  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
    trackers.update(frame);

    // draw the tracked object
    for(unsigned i=0;i<trackers.objects.size();i++)
      rectangle( frame, trackers.objects[i], Scalar( 255, 0, 0 ), 2, 1 );

    // show image with the tracked object
    imshow("tracker",frame);

    //quit on ESC button
    if(waitKey(1)==27)break;
  }

}

Explanation

1. Create the MultiTracker object

     MultiTracker trackers(trackingAlg);

   You can create the MultiTracker object and use the same tracking algorithm for all tracked object as shown in the snippet. If you want to use different type of tracking algorithm for each tracked object, you should define the tracking algorithm whenever a new object is added to the MultiTracker object.

2. Selection of multiple objects

     selectROI("tracker",frame,objects);

   You can use cv::selectROI to select multiple objects with the result stored in a vector of cv::Rect2d as shown in the code. You can also use another kind of selection scheme, please refer to cv::selectROI for detailed information.

3. Adding the tracked object to MultiTracker

     trackers.add(frame,objects);

   You can add all tracked objects at once to the MultiTracker as shown in the code. In this case, all objects will be tracked using same tracking algorithm as specified in decaration of MultiTracker object. If you want to use different tracker algorithms for each tracked object, You should add the tracked objects one by one and specify their tracking algorithm using the variant of cv::MultiTracker::add.

   See also

   cv::MultiTracker::add( const String& trackerType, const Mat& image, const Rect2d& boundingBox )

4. Obtaining the result

       // draw the tracked object
       for(unsigned i=0;i<trackers.objects.size();i++)
         rectangle( frame, trackers.objects[i], Scalar( 255, 0, 0 ), 2, 1 );

   You can access the result from the public variable cv::MultiTracker::objects provided by the MultiTracker class as shown in the code.