Maximum Correntropy Criterion for Robust Face Recognition

	Maximum Correntropy Criterion for Robust Face Recognition
	Ran He(赫然)1 ; Weishi Zheng 2,3; Baogang Hu1 ; He, Ran
发表期刊	IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
	2011-08-01
卷号	33 期号:8 页码:1561-1576
文章类型	Article
摘要	In this paper, we present a sparse correntropy framework for computing robust sparse representations of face images for recognition. Compared with the state-of-the-art l(1) norm-based sparse representation classifier ( SRC), which assumes that noise also has a sparse representation, our sparse algorithm is developed based on the maximum correntropy criterion, which is much more insensitive to outliers. In order to develop a more tractable and practical approach, we in particular impose nonnegativity constraint on the variables in the maximum correntropy criterion and develop a half-quadratic optimization technique to approximately maximize the objective function in an alternating way so that the complex optimization problem is reduced to learning a sparse representation through a weighted linear least squares problem with nonnegativity constraint at each iteration. Our extensive experiments demonstrate that the proposed method is more robust and efficient in dealing with the occlusion and corruption problems in face recognition as compared to the related state-of-the-art methods. In particular, it shows that the proposed method can improve both recognition accuracy and receiver operator characteristic (ROC) curves, while the computational cost is much lower than the SRC algorithms.
关键词	Information Theoretical Learning Correntropy Linear Least Squares Half-quadratic Optimization Sparse Representation M-estimator Face Recognition Occlusion And Corruption
WOS标题词	Science & Technology ; Technology
关键词[WOS]	SPARSE REPRESENTATION ; ALGORITHMS ; EIGENFACES ; REGRESSION ; MODELS ; SIGNAL
收录类别	SCI
语种	英语
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号	WOS:000291807200006
引用统计	被引频次：532[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/173211/2806
专题	多模态人工智能系统全国重点实验室_多媒体计算离退休人员
通讯作者	He, Ran
作者单位	1.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 2.Sun Yat Sen Univ, Sch Informat Sci & Technol, Guangzhou 510275, Guangdong, Peoples R China 3.Queen Mary Univ London, Dept Comp Sci, London, England
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	Ran He,Weishi Zheng,Baogang Hu,et al. Maximum Correntropy Criterion for Robust Face Recognition[J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,2011,33(8):1561-1576.
APA	Ran He,Weishi Zheng,Baogang Hu,&He, Ran.(2011).Maximum Correntropy Criterion for Robust Face Recognition.IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,33(8),1561-1576.
MLA	Ran He,et al."Maximum Correntropy Criterion for Robust Face Recognition".IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 33.8(2011):1561-1576.

条目包含的文件		下载所有文件
文件名称/大小	文献类型	版本类型	开放类型	使用许可
final- Maximum Corre（2109KB）	期刊论文	作者接受稿	开放获取	CC BY-NC-SA	浏览下载