CASIA OpenIR  > 模式识别国家重点实验室  > 生物识别与安全技术研究
Perturbation LDA: Learning the difference between the class empirical mean and its expectation
Zheng, Wei-Shi2,3; Lai, J. H.1,3; Yuen, Pong C.4; Lie, Stan Z.5,6
Source PublicationPATTERN RECOGNITION
2009-05-01
Volume42Issue:5Pages:764-779
SubtypeArticle
AbstractFisher's linear discriminant analysis (LDA) is popular for dimension reduction and extraction of discriminant features in many pattern recognition applications, especially biometric learning. In deriving the Fisher's LDA formulation, there is an assumption that the class empirical mean is equal to its expectation. However, this assumption may not be valid in practice. In this paper, from the "perturbation" perspective, we develop a new algorithm, called perturbation LDA (P-LDA), in which perturbation random vectors are introduced to learn the effect of the difference between the class empirical mean and its expectation in Fisher criterion. This perturbation learning in Fisher criterion would yield new forms of within-class and between-class covariance matrices integrated with some perturbation factors. Moreover, a method is proposed for estimation of the covariance matrices of perturbation random vectors for practical implementation. The proposed P-LDA is evaluated on both synthetic data sets and real face image data sets. Experimental results show that P-LDA outperforms the popular Fisher's LDA-based algorithms in the undersampled case. (C) 2008 Elsevier Ltd. All rights reserved.
KeywordFisher Criterion Perturbation Analysis Face Recognition
WOS HeadingsScience & Technology ; Technology
WOS KeywordLINEAR DISCRIMINANT-ANALYSIS ; FACE-RECOGNITION ; TRANSFORMATION ; REDUCTION ; ALGORITHM ; SAMPLES ; PCA
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS IDWOS:000263431200016
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/9717
Collection模式识别国家重点实验室_生物识别与安全技术研究
Affiliation1.Sun Yat Sen Univ, Sch Informat Sci & Technol, Dept Elect & Commun Engn, Guangzhou 510275, Guangdong, Peoples R China
2.Sun Yat Sen Univ, Sch Math & Computat Sci, Guangzhou 510275, Guangdong, Peoples R China
3.Guangdong Prov Key Lab Informat Secur, Guangzhou, Guangdong, Peoples R China
4.Hong Kong Baptist Univ, Dept Comp Sci, Hong Kong, Hong Kong, Peoples R China
5.Chinese Acad Sci, Ctr Biometr & Secur Res, Beijing, Peoples R China
6.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Zheng, Wei-Shi,Lai, J. H.,Yuen, Pong C.,et al. Perturbation LDA: Learning the difference between the class empirical mean and its expectation[J]. PATTERN RECOGNITION,2009,42(5):764-779.
APA Zheng, Wei-Shi,Lai, J. H.,Yuen, Pong C.,&Lie, Stan Z..(2009).Perturbation LDA: Learning the difference between the class empirical mean and its expectation.PATTERN RECOGNITION,42(5),764-779.
MLA Zheng, Wei-Shi,et al."Perturbation LDA: Learning the difference between the class empirical mean and its expectation".PATTERN RECOGNITION 42.5(2009):764-779.
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