Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/19090
Title: Improvement on null space LDA for face recognition : a symmetry consideration
Authors: Zuo, W
Wang, K
Zhang, D 
Issue Date: 2006
Publisher: Springer
Source: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics), 2006, v. 3832 LNCS, p. 78-84 How to cite?
Journal: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics) 
Abstract: The approximate bilateral symmetry of human face has been explored to improve the recognition performance of some face recognition algorithms such as Linear Discriminant Analysis (LDA) and Direct-LDA (D-LDA). In this paper we summary the ways to generate virtual sample using facial symmetry, and investigate the three strategies of using facial symmetric information in the Null Space LDA (NLDA) framework. The results of our experiments indicate that, the use of facial symmetric information can further improve the recognition accuracy of conventional NLDA.
Description: International Conference on Biometrics, ICB 2006, Hong Kong, 5-7 January 2006
URI: http://hdl.handle.net/10397/19090
ISBN: 3540311114
9783540311119
ISSN: 0302-9743 (print)
1611-3349 (online)
Appears in Collections:Conference Paper

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