Partie interactive du site pédagogique ELECINF344/ELECINF381 de Télécom ParisTech (occurrence 2011).


[Casper] Face tracking

We now have our face tracking algorithm running on BeagleBoard. Since a tracking only based on face detection was to slow and not very intuitive (you always have to look the camera), we decided to use a blob tracking algorithm, which we initialize with the face detection algorithm.

First, Casper looks for a face. When it finds one, it learns the associated color histogram. After what it tracks the histogram (with the OpenCV Camshift function), for a few tens of frames. If it does not find a face again during the blob tracking, it stops at the end of the frames. Otherwise, it keeps tracking the « blob » face.

We adopt a multithread program : a thread looks for a face every second, and a thread is responsible for blob tracking when a face is found. The first thread is used to set a counter which is decremented by the second thread.