Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/18938
Title: LPP solution schemes for use with face recognition
Authors: Xu, Y
Zhong, A
Yang, J
Zhang, D 
Keywords: Face recognition
Feature extraction
Locality preserving projection
Small sample size problems
Issue Date: 2010
Publisher: Elsevier
Source: Pattern recognition, 2010, v. 43, no. 12, p. 4165-4176 How to cite?
Journal: Pattern recognition 
Abstract: Locality preserving projection (LPP) is a manifold learning method widely used in pattern recognition and computer vision. The face recognition application of LPP is known to suffer from a number of problems including the small sample size (SSS) problem, the fact that it might produce statistically identical transform results for neighboring samples, and that its classification performance seems to be heavily influenced by its parameters. In this paper, we propose three novel solution schemes for LPP. Experimental results also show that the proposed LPP solution scheme is able to classify much more accurately than conventional LPP and to obtain a classification performance that is only little influenced by the definition of neighbor samples.
URI: http://hdl.handle.net/10397/18938
ISSN: 0031-3203
EISSN: 1873-5142
DOI: 10.1016/j.patcog.2010.06.016
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