Supervised kernel locality preserving projections for face recognition

CASIA OpenIR > 09年以前成果

	Supervised kernel locality preserving projections for face recognition
	Cheng, J; Liu, QS; Lu, HQ; Chen, YW
发表期刊	NEUROCOMPUTING
	2005-08-01
卷号	67 页码:443-449
文章类型	Article
摘要	Subspace analysis is an effective approach for face recognition. Finding a suitable low-dimensional subspace is a key step of subspace analysis, for it has a direct effect on recognition performance. In this paper, a novel subspace method, named supervised kernel locality preserving projections (SKLPP), is proposed for face recognition, in which geometric relations are preserved according to prior class-label information and complex nonlinear variations of real face images are represented by nonlinear kernel mapping. SKLPP cannot only gain a perfect approximation of face manifold, but also enhance local within-class relations. Experimental results show that the proposed method can improve face recognition performance. (c) 2005 Elsevier B.V. All rights reserved.
关键词	Kernel Trick Subspace Analysis Locality Preserving Projection Face Recognition
WOS标题词	Science & Technology ; Technology
关键词[WOS]	NONLINEAR DIMENSIONALITY REDUCTION
收录类别	SCI
语种	英语
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:000231436300032
引用统计	被引频次：81[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/173211/9067
专题	09年以前成果
作者单位	Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100080, Peoples R China
推荐引用方式 GB/T 7714	Cheng, J,Liu, QS,Lu, HQ,et al. Supervised kernel locality preserving projections for face recognition[J]. NEUROCOMPUTING,2005,67:443-449.
APA	Cheng, J,Liu, QS,Lu, HQ,&Chen, YW.(2005).Supervised kernel locality preserving projections for face recognition.NEUROCOMPUTING,67,443-449.
MLA	Cheng, J,et al."Supervised kernel locality preserving projections for face recognition".NEUROCOMPUTING 67(2005):443-449.