Object Tracking In Real Time Via Opencv And Python

I'm looking for good algorithm to do object tracking in real time. the best one I found so far was camshift but the problem with that is that I need to object detection will come f

Solution 1:

I don't know camshift very well, but i'm guessing you are using opencv implementation. The below code is a snippet from the opencv example:

        hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
        dst = cv2.calcBackProject([hsv],[0],roi_hist,[0,180],1)

        # apply meanshift toget the new location
        ret, track_window = cv2.CamShift(dst, track_window, term_crit)

For the first image, choosing the dst as large as the frame size should solve your problem. Otherwise you can use a sliding window approach to locate the target in the first frame.

On the other hand, the term real time really depends on your requirements and deployment environment in such aspects:

• frame rate of input video
• resolution of the frames
• color scheme of the frame (rgb, yuv, gray, hsv, ...)
• maximum/minimum target size
• maximum target speed (pixels/frame)
• should it be robust to occlusions?
• what's the most specific properties of your targets: cars, human/animals, solid objects, changing shape, turning, ...
• are you using a CPU, DSP or GPU?
• ...

Since all of the considerations above would be really effective on your choice, i cannot recommend you a specific one. This one may be useful for example.

I would dig into IEEE explore and make a search such as real time object tracking. I did one for you :) Here is your best start point, i guess.

Hope this helps. Gokhan.