Real time implementation of a face tracking

This paper describes a system capable of realizing a face detection and tracking in video sequences. In developing this system, we have used a RBFneural network to locate and categorize faces of different dimensions. The face tracker can be applied to a video communication system which allows the users to move freely in front of the camera while communicating. The system works at several stages. At first, we extract useful parameters by a low-pass filtering to compress data and we compose our codebook vectors. Then, the RBFneural network realizes a face detection and tracking on a specific board.