Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/33993
Title: Face representation based on the multiple-class maximum scatter difference
Authors: Song, FX
Yang, JY
Liu, SH
Zhang, D 
Keywords: Eigenvectors
Face recognition
Feature extraction
Fisher discriminant criterion
Maximum scatter difference
Issue Date: 2006
Publisher: 科學出版社
Source: 自动化学报 (Acta automatica sinica), 2006, v. 32, no. 3, p. 378-385 How to cite?
Journal: 自动化学报 (Acta automatica sinica) 
Abstract: In this paper we extend the maximum scatter difference discriminant criterion which is proposed for binary classification to the multiple-class maximum scatter difference discriminant criterion. Based on this new criterion we establish a novel face representation method. The facial feature extraction method based on the multiple-class maximum scatter difference discriminant criterion effectively avoids the small sample size problem which always brings troubles to conventional discriminant analysis methods when they are applied to face recognition tasks. Experimental results conducted on international benchmark datasets such as ORL, Yale, and FERET face image databases demonstrate that the novel face representation method is promising in comparison with Fisherfaces, eigenfaces, orthogonal complimentary space method, and null space method.
URI: http://hdl.handle.net/10397/33993
ISSN: 0254-4156
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