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	Orthogonal Quadratic Discriminant Functions for Face Recognition
	Gu, Suicheng ; Tan, Ying ; He, Xhigui
	2009
关键词	Orthogonal quadratic discriminant functions (OQDF) modified quadratic discriminant function (MQDF) small sample size (SSS) face recognition (FR) Laplacian Smoothing Transform(LST) Fisher&apos CLASSIFICATION s linear discriminant(FLD)
英文摘要	Small sample size (SSS) problem is usually a limit, to the robustness of learning methods hi face recognition. Especially in the quadratic discriminant functions (QDF), too many parameters need to be estimated and covariance matrix Of a Class is usually singular. In order to overcome the SSS problems, we proposed a, novel approach called orthogonal quadratic discriminate functions (C)QDF). The OQDF assumes probability distribution Functions of each two classes of face images have a uniform shape. Then, three OQDF models are developed. The Laplacian smoothing transform (LST) and Fisher's linear discriminant (FLD) are employed to preprocess the face images for the OQDF classifier. Finally, we evaluate, our proposed algorithms on two face databases, ORL and Yale.; http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000268029200051&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701 ; Computer Science, Artificial Intelligence; Computer Science, Theory & Methods; EI; CPCI-S(ISTP); 1
语种	英语
DOI标识	10.1007/978-3-642-01513-7_51
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/293218]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Gu, Suicheng,Tan, Ying,He, Xhigui. Orthogonal Quadratic Discriminant Functions for Face Recognition. 2009-01-01.

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