Paper data
Title:
Real time implementation of a face tracking Author(s): Malasne Nicolas, University of Burgundy, LE2I Laboratory Yang Fan, University of Burgundy, LE2I Laboratory Paindavoine Michel, University of Burgundy, LE2I Laboratory Page numbers in the proceedings: Volume II pp 237-240 Session: Implementation
Paper abstract
This paper describes a system capable of realizing a face detection and tracking in video sequences. In developing this system, we have used a RBF neural 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 RBF neural network realizes a face detection and tracking on a specific board.
Paper
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