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Paper data
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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
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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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A PDF version is available here

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