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matlabopencvvideo-tracking

How to convert opencv functions to mexopencv functions useable in matlab?


My Problem:

I want to use functions of opencv like the MIL-Tracker or MedianFlow-Tracker in Matlab (these functions are not in mexopencv). But I don't know how or understand how to do this. The documentation of opencv/mexopencv doesn't help me. This doesn't help: how do OpenCV shared libraries in matlab? - because the link in the answer is down.

So is there a way to use these functions in Matlab? And if- How?

Why?: As a part of my bachelor thesis I have to compare different already implemented ways to track people.


Solution

  • If you would like to use these functions specifically in MATLAB you could always write your own MEX file in C/C++ and send the data back/forward between the two calls, however this would require some basic C++ knowledge and understanding creating MEX files.

    Personally I would definately recommend trying this with Python and the OpenCV Python interface since its so widely used and more supported than using the calls in MATLAB (plus its always a useful skill to be able to switch between Python and MATLAB as and when needed).

    There is a full example with the MIL-Tracker and the MedianFlow-Tracker (and others) here (Which demonstrates using them in C++ and Python!).


    Python Example :

    import cv2
    import sys
    
    (major_ver, minor_ver, subminor_ver) = (cv2.__version__).split('.')
    
    if __name__ == '__main__' :
    
        # Set up tracker.
        # Instead of MIL, you can also use
    
        tracker_types = ['BOOSTING', 'MIL','KCF', 'TLD', 'MEDIANFLOW', 'GOTURN']
        tracker_type = tracker_types[2]
    
        if int(minor_ver) < 3:
            tracker = cv2.Tracker_create(tracker_type)
        else:
            if tracker_type == 'BOOSTING':
                tracker = cv2.TrackerBoosting_create()
            if tracker_type == 'MIL':
                tracker = cv2.TrackerMIL_create()
            if tracker_type == 'KCF':
                tracker = cv2.TrackerKCF_create()
            if tracker_type == 'TLD':
                tracker = cv2.TrackerTLD_create()
            if tracker_type == 'MEDIANFLOW':
                tracker = cv2.TrackerMedianFlow_create()
            if tracker_type == 'GOTURN':
                tracker = cv2.TrackerGOTURN_create()
    
        # Read video
        video = cv2.VideoCapture("videos/chaplin.mp4")
    
        # Exit if video not opened.
        if not video.isOpened():
            print "Could not open video"
            sys.exit()
    
        # Read first frame.
        ok, frame = video.read()
        if not ok:
            print 'Cannot read video file'
            sys.exit()
    
        # Define an initial bounding box
        bbox = (287, 23, 86, 320)
    
        # Uncomment the line below to select a different bounding box
        bbox = cv2.selectROI(frame, False)
    
        # Initialize tracker with first frame and bounding box
        ok = tracker.init(frame, bbox)
    
        while True:
            # Read a new frame
            ok, frame = video.read()
            if not ok:
                break
    
            # Start timer
            timer = cv2.getTickCount()
    
            # Update tracker
            ok, bbox = tracker.update(frame)
    
            # Calculate Frames per second (FPS)
            fps = cv2.getTickFrequency() / (cv2.getTickCount() - timer);
    
            # Draw bounding box
            if ok:
                # Tracking success
                p1 = (int(bbox[0]), int(bbox[1]))
                p2 = (int(bbox[0] + bbox[2]), int(bbox[1] + bbox[3]))
                cv2.rectangle(frame, p1, p2, (255,0,0), 2, 1)
            else :
                # Tracking failure
                cv2.putText(frame, "Tracking failure detected", (100,80), cv2.FONT_HERSHEY_SIMPLEX, 0.75,(0,0,255),2)
    
            # Display tracker type on frame
            cv2.putText(frame, tracker_type + " Tracker", (100,20), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (50,170,50),2);
    
            # Display FPS on frame
            cv2.putText(frame, "FPS : " + str(int(fps)), (100,50), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (50,170,50), 2);
    
            # Display result
            cv2.imshow("Tracking", frame)
    
            # Exit if ESC pressed
            k = cv2.waitKey(1) & 0xff
            if k == 27 : break
    

    I would definately try it using Python (if this is an option). Otherwise if MATLAB is a must then probably try implementing the C++ example code shown in the link before as a MEX file and linking openCV during the compilation i.e.

    mex trackerMexOpenCV.cpp 'true filepath location to openCV lib'
    

    I hope this helps!