Practical implementation of OpenCV Kalman filter w/python?

Question

I'm neither an expert in OpenCV or python but after far too much messing around with poor c# implementations of cv libraries I decided to take the plunge.

Thus far I've got 'blob' (read-contour) tracking working the way I want - my problem now is occlusion, a problem which, as I (and myriad youtube videos) understand it, the Kalman filter can solve. The problem is, relevant examples in python don't seem to exist and the example code is largely devoid of comments, ergo how a red and yellow line running all over the shop solve my problem is a mystery to me.

What I want to achieve is something like this http://www.youtube.com/watch?v=lvmEE_LWPUc or this http://www.youtube.com/watch?v=sG-h5ONsj9s.

I'd be very grateful if someone could point me in the direction of (or provide) an example using actual images pulled from a webcam or video.

Thanks in Advance.

Answer 1

You can take a look at: https://github.com/dajuric/accord-net-extensions

It implements Kalman filtering, particle filtering, Joint Probability Data Association Filter (for multi-object tracking) along with motion models.

Samples included!