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Supervised regularization locality-preserving projection method for face recognition
WEN-SHENG CHEN1; WEI WANG1; JIAN-WEI YANG2; YUAN YAN TANG3
2012-11-01
Source PublicationInternational Journal of Wavelets, Multiresolution and Information Processing
ISSN0219-6913
Volume10Issue:6
Other Abstract

Locality-preserving projection (LPP) is a promising manifold-based dimensionality reduction and linear feature extraction method for face recognition. However, there exist two main issues in traditional LPP algorithm. LPP does not utilize the class label information at the training stage and its performance will be affected for classification tasks. In addition, LPP often suffers from small sample size (3S) problem, which occurs when the dimension of input pattern space is greater than the number of training samples. Under this situation, LPP fails to work. To overcome these two limitations, this paper presents a novel supervised regularization LPP (SRLPP) approach based on a supervised graph and a new regularization strategy. It theoretically proves that regularization matrix S approaches to the original one as the regularized parameter tends to zero. The proposed SRLPP method is subsequently applied to face recognition. The experiments are conducted on two publicly available face databases, namely ORL database and FERET database. Compared with some existing LDA-based and LPP-based linear feature extraction approaches, experimental results show that our SRLPP approach gives superior performance. 

KeywordFace Recognition Locality-preserving Projections Regularization. Small Sample Size Problem Supervised Learning
DOIhttp://doi.org/10.1142/S0219691312500531
URLView the original
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Mathematics
WOS SubjectComputer Science, Software Engineering ; Mathematics, Interdisciplinary Applications
WOS IDWOS:000314539000003
PublisherWORLD SCIENTIFIC PUBL CO PTE LTD, 5 TOH TUCK LINK, SINGAPORE 596224, SINGAPORE
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Cited Times [WOS]:7   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Corresponding AuthorWEN-SHENG CHEN; WEI WANG; JIAN-WEI YANG; YUAN YAN TANG
Affiliation1.College of Mathematics and Computational Science Shenzhen University, Shenzhen 518060, P. R. China
2.College of Mathematics and Physics Nanjing University of Information Science and Technology Nanjing 210044, P. R. China
3.Department of Computer and Information Science University of Macau, Macau, P. R. China
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
WEN-SHENG CHEN,WEI WANG,JIAN-WEI YANG,et al. Supervised regularization locality-preserving projection method for face recognition[J]. International Journal of Wavelets, Multiresolution and Information Processing,2012,10(6).
APA WEN-SHENG CHEN,WEI WANG,JIAN-WEI YANG,&YUAN YAN TANG.(2012).Supervised regularization locality-preserving projection method for face recognition.International Journal of Wavelets, Multiresolution and Information Processing,10(6).
MLA WEN-SHENG CHEN,et al."Supervised regularization locality-preserving projection method for face recognition".International Journal of Wavelets, Multiresolution and Information Processing 10.6(2012).
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