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Maximum Correntropy Criterion for Robust Face Recognition
Ran He(赫然)1; Weishi Zheng2,3; Baogang Hu1; He, Ran
Source PublicationIEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
2011-08-01
Volume33Issue:8Pages:1561-1576
SubtypeArticle
AbstractIn 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.
KeywordInformation Theoretical Learning Correntropy Linear Least Squares Half-quadratic Optimization Sparse Representation M-estimator Face Recognition Occlusion And Corruption
WOS HeadingsScience & Technology ; Technology
WOS KeywordSPARSE REPRESENTATION ; ALGORITHMS ; EIGENFACES ; REGRESSION ; MODELS ; SIGNAL
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS IDWOS:000291807200006
Citation statistics
Cited Times:319[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/2806
Collection模式识别国家重点实验室_多媒体计算与图形学
Corresponding AuthorHe, Ran
Affiliation1.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
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
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.
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