Fast communication: Dominant singular value decomposition representation for face recognition

Authors:
Jiwen Lu;Yongwei Zhao
Affiliations:
School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore;Department of Information Science, Xi'an University of Technology, Xi'an 710048, China
Venue:
Signal Processing
Year:
2010

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Abstract

We propose in this paper a new dominant singular value decomposition representation (DSVDR) method for face recognition. Motivated by the fact that each grayscale face image can be decomposed into a composition of a set of bases by the well-known singular value decomposition (SVD) technique and each basis contains different discriminative and reconstructive information for face representation, we present a new face representation method to select a subset of important bases and regulate their singular values (SVs) according to their discriminative and reconstructive power simultaneously for face recognition. Experimental results demonstrate the efficacy of the proposed method.