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Multi object tracking with Haar cascade detection

asked 2014-10-27 17:02:50 -0500

_chris gravatar image

I have an unknown number of objects on a rotating table and the goal is to track them individually. I have a robust cascade classifier trained and I can recover the metric location of the objects fairly accurately, the only problem is how to leverage OpenCV to keep track of each object. To make it a bit harder, all the objects are basically the same.

What would my best approach be to 'lock on' to each object? Any suggestions would be appreciated.

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answered 2014-10-27 17:19:24 -0500

I suppose you are working on a video with high temporal resolution (at least 10 images / seconds). Indeed, below this, you will have a lot of problems to track your objects.

The solution you can implement depends also on the processing time you can spend to track objects. If you need a close-to-realtime solution, I suggest using sparse Lukas-Kanade tracking algorithm. You will first take point in the center of each objects detected by your classifier, then use calcopticalflowpyrlk to track those points along the sequence.

If you can spend more CPU, you can use dense optical-flow algorithm which are more robust. You will then have to compute the mean translation of the flow field inside the bounding box of each objects to have the movement of your object.

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answered 2014-10-27 18:09:02 -0500

Witek gravatar image

How about using the OpenTLD tracker? Since OpenTLD requires initialization of its target(s), you can use your classifiers to find the initial position of all your objects and pass it to the OpenTLD, which should do the rest. It's just a thought, I 've never used OpenTLD...

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Asked: 2014-10-27 17:02:50 -0500

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Last updated: Oct 27 '14