Linear discriminant analysis using rotational invariant L-1 norm

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	Linear discriminant analysis using rotational invariant L-1 norm
	Li, Xi 1,4; Hu, Weiming1 ; Wang, Hanzi 2; Zhang, Zhongfei 3
发表期刊	NEUROCOMPUTING
	2010-08-01
卷号	73 期号:13-15 页码:2571-2579
文章类型	Article
摘要	Linear discriminant analysis (LDA) is a well-known scheme for supervised subspace learning. It has been widely used in the applications of computer vision and pattern recognition. However, an intrinsic limitation of LDA is the sensitivity to the presence of outliers, due to using the Frobenius norm to measure the inter-class and intra-class distances. In this paper, we propose a novel rotational invariant L-1 norm (i.e., R-1 norm) based discriminant criterion (referred to as DCL1), which better characterizes the intra-class compactness and the inter-class separability by using the rotational invariant L-1 norm instead of the Frobenius norm. Based on the DCL1, three subspace learning algorithms (i.e., 1DL(1), 2DL(1), and TDL1) are developed for vector-based, matrix-based, and tensor-based representations of data, respectively. They are capable of reducing the influence of outliers substantially, resulting in a robust classification. Theoretical analysis and experimental evaluations demonstrate the promise and effectiveness of the proposed DCL1 and its algorithms. (C) 2010 Elsevier B.V. All rights reserved.
关键词	Linear Discriminant Analysis Face Classification R-1 Norm
WOS标题词	Science & Technology ; Technology
关键词[WOS]	FACE RECOGNITION
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:000281612300030
引用统计	被引频次：64[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/173211/9728
专题	多模态人工智能系统全国重点实验室_视频内容安全
作者单位	1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China 2.Univ Adelaide, Dept Comp Sci, Adelaide, SA 5005, Australia 3.SUNY Binghamton, Binghamton, NY 13902 USA 4.TELECOM ParisTech, CNRS, Paris, France
第一作者单位	模式识别国家重点实验室
推荐引用方式 GB/T 7714	Li, Xi,Hu, Weiming,Wang, Hanzi,et al. Linear discriminant analysis using rotational invariant L-1 norm[J]. NEUROCOMPUTING,2010,73(13-15):2571-2579.
APA	Li, Xi,Hu, Weiming,Wang, Hanzi,&Zhang, Zhongfei.(2010).Linear discriminant analysis using rotational invariant L-1 norm.NEUROCOMPUTING,73(13-15),2571-2579.
MLA	Li, Xi,et al."Linear discriminant analysis using rotational invariant L-1 norm".NEUROCOMPUTING 73.13-15(2010):2571-2579.