Feature extraction using maximum variance sparse mapping

CASIA OpenIR > 中科院工业视觉智能装备工程实验室 > 精密感知与控制

	Feature extraction using maximum variance sparse mapping
	Liu, Jin 1,3; Li, Bo 1,2,3; Zhang, Wen-Sheng3
发表期刊	NEURAL COMPUTING & APPLICATIONS
	2012-11-01
卷号	21 期号:8 页码:1827-1833
文章类型	Article
摘要	In this paper, a multiple sub-manifold learning method-oriented classification is presented via sparse representation, which is named maximum variance sparse mapping. Based on the assumption that data with the same label locate on a sub-manifold and different class data reside in the corresponding sub-manifolds, the proposed algorithm can construct an objective function which aims to project the original data into a subspace with maximum sub-manifold distance and minimum manifold locality. Moreover, instead of setting the weights between any two points directly or obtaining those by a square optimal problem, the optimal weights in this new algorithm can be approached using L1 minimization. The proposed algorithm is efficient, which can be validated by experiments on some benchmark databases.
关键词	Mvsm Sub-manifold Sparse Representation
WOS标题词	Science & Technology ; Technology
关键词[WOS]	UNSUPERVISED DISCRIMINANT PROJECTION ; DIMENSIONALITY REDUCTION ; FACE RECOGNITION ; PALM BIOMETRICS ; REPRESENTATION
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:000309878400002
引用统计	被引频次：10[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/173211/10742
专题	中科院工业视觉智能装备工程实验室_精密感知与控制
作者单位	1.Wuhan Univ, State Key Lab Software Engn, Wuhan 430072, Peoples R China 2.Wuhan Univ Sci & Technol, Coll Comp Sci & Technol, Wuhan 430081, Peoples R China 3.Chinese Acad Sci, Inst Automat, Key Lab Complex Syst & Intelligence Sci, Beijing 100190, Peoples R China
第一作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Liu, Jin,Li, Bo,Zhang, Wen-Sheng. Feature extraction using maximum variance sparse mapping[J]. NEURAL COMPUTING & APPLICATIONS,2012,21(8):1827-1833.
APA	Liu, Jin,Li, Bo,&Zhang, Wen-Sheng.(2012).Feature extraction using maximum variance sparse mapping.NEURAL COMPUTING & APPLICATIONS,21(8),1827-1833.
MLA	Liu, Jin,et al."Feature extraction using maximum variance sparse mapping".NEURAL COMPUTING & APPLICATIONS 21.8(2012):1827-1833.