Knowledge Commons of Institute of Automation,CAS
Maximum Correntropy Criterion for Robust Face Recognition | |
Ran He(赫然)1; Weishi Zheng2,3; 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 | |
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. |
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