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LPP solution schemes for use with face recognition
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DOI：10.1016/j.patcog.2010.06.016.png)
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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. (C) 2010 Elsevier Ltd. All rights reserved.
Keyword:
Face recognition
Feature extraction
Locality preserving projection
Small sample size problems
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7.6
论文数:
1.3W
被引数:
4.5W
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