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	Sparse Representation Shape Models
	Li, Yuelong ; Feng, Jufu ; Meng, Li ; Wu, Jigang
	2014
关键词	Shape extraction Deformable shape model Morphological shape model Sparse representation Point distribution model Pose recognition FACE-RECOGNITION ALGORITHMS MIXTURE MODEL EIGENFACES FEATURES
DOI	10.1007/s10851-012-0394-3
英文摘要	It is well-known that, during shape extraction, enrolling an appropriate shape constraint model could effectively improve locating accuracy. In this paper, a novel deformable shape model, Sparse Representation Shape Models (SRSM), is introduced. Rather than following commonly utilized statistical shape constraints, our model constrains shape appearance based on a morphological structure, the convex hull of aligned training samples, i.e., only shapes that could be linearly represented by aligned training samples with the sum of coefficients equal to one, are defined as qualified. This restriction strictly controls shape deformation modes to reduce extraction errors and prevent extremely poor outputs. This model is realized based on sparse representation, which ensures during shape regularization the maximum valuable shape information could be reserved. Besides, SRSM is interpretable and hence helpful to further understanding applications, such as face pose recognition. The effectiveness of SRSM is verified on two publicly available face image datasets, the FGNET and the FERET.; http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000329234700006&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701 ; Computer Science, Artificial Intelligence; Computer Science, Software Engineering; Mathematics, Applied; SCI(E); 1; ARTICLE; liyuelong@pku.edu.cn; 1; 83-91; 48
语种	英语
内容类型	期刊论文
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/218660]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Li, Yuelong,Feng, Jufu,Meng, Li,et al. Sparse Representation Shape Models[J],2014.
APA	Li, Yuelong,Feng, Jufu,Meng, Li,&Wu, Jigang.(2014).Sparse Representation Shape Models..
MLA	Li, Yuelong,et al."Sparse Representation Shape Models".(2014).

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