Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/75302
Title: iJADE face recognizer – a multi-agent based pose and scale invariant human face recognition system
Authors: Ao Ieong, TWH 
Lee, RST 
Issue Date: 2004
Publisher: Springer
Source: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics), 2004, v. 3214 LNCS, no. , p. 594-601 How to cite?
Journal: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics) 
Abstract: A multi-agent based pose and scale invariant human face recognition system called iJADE Face Recognizer is presented. We focus on how neural networks are applied on face detection under cluttered scenes, and committee network handles detection of multi-pose faces. We also investigate how Gausssian mixture model of skin tone can narrow down the region of interest in complex image on detection. In feature extraction on faces, Gabor feature vector derived from Gabor wavelet representation of faces is adopted, which is robust to changes in illumination and facial expression, and we utilize template and feature-based face recognition methods in order to improve the recognition rate. In face identification process, we make use of agent technology to increase the scalability and efficient of the system. By using these techniques, we develop an accurate and efficient recognition system with invariant to different conditions on human faces under uncontrolled environment.
Description: International Conference on Knowledge-Based and Intelligent Information and Engineering Systems [KES], 20-25 September 2004, Wellington, New Zealand
URI: http://hdl.handle.net/10397/75302
ISSN: 0302-9743
EISSN: 1611-3349
DOI: 10.1007/978-3-540-30133-2_78
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