Letters: Optimal locality preserving projection for face recognition

Authors:
Yu Chen;Xiao-hong Xu;Jian-huang Lai
Affiliations:
School of Mathematics and Computational Science, SunYat-Sen University, Guangzhou, Guangdong 510275, China and Department of Applied Mathematics, South China Agricultural University, Guangzhou, Gu ...;Department of Applied Mathematics, South China Agricultural University, Guangzhou, Guangdong 510642, China;School of Information Science and Technology, SunYat-Sen University, Guangzhou, Guangdong 510275, China
Venue:
Neurocomputing
Year:
2011

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Abstract

In face recognition, when the number of images in the training set is much smaller than the number of pixels in each image, Locality Preserving Projections (LPP) often suffers from the singularity problem. To overcome singularity problem, principal component analysis is applied as a preprocessing step. But this procession may discard some important discriminative information. In this paper, a novel algorithm called Optimal Locality Preserving Projections (O-LPP) is proposed. The algorithm transforms the singular eigensystem computation to eigenvalue decomposition problems without losing any discriminative information, which can reduce the computation complexity. And the theoretical analysis related to the algorithm is also obtained. Extensive experiments on face databases demonstrate the proposed algorithm is superior to the traditional LPP algorithm.