Perturbation LDA: Learning the difference between the class empirical mean and its expectation

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 生物识别与安全技术

	Perturbation LDA: Learning the difference between the class empirical mean and its expectation
	Zheng, Wei-Shi 2,3; Lai, J. H.1,3; Yuen, Pong C.4; Lie, Stan Z.5,6
发表期刊	PATTERN RECOGNITION
	2009-05-01
卷号	42 期号:5 页码:764-779
文章类型	Article
摘要	Fisher'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.
关键词	Fisher Criterion Perturbation Analysis Face Recognition
WOS标题词	Science & Technology ; Technology
关键词[WOS]	LINEAR DISCRIMINANT-ANALYSIS ; FACE-RECOGNITION ; TRANSFORMATION ; REDUCTION ; ALGORITHM ; SAMPLES ; PCA
收录类别	SCI
语种	英语
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号	WOS:000263431200016
引用统计	被引频次：18[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/9717
专题	多模态人工智能系统全国重点实验室_生物识别与安全技术
作者单位	1.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
推荐引用方式 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.