热门
Maximum Correntropy Criterion for Robust Face Recognition
文献类型：期刊论文
| 作者 | He, Ran1; Zheng, Wei-Shi2,3; Hu, Bao-Gang1; Ran He(赫然) ; Baogang Hu
|
| 刊名 | IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
 |
| 出版日期 | 2011-08-01 |
| 卷号 | 33期号:8页码:1561-1576 |
| 关键词 | Information theoretical learning correntropy linear least squares half-quadratic optimization sparse representation M-estimator face recognition occlusion and corruption |
| 英文摘要 | 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. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic |
| 研究领域[WOS] | Computer Science ; Engineering |
| 关键词[WOS] | SPARSE REPRESENTATION ; ALGORITHMS ; EIGENFACES ; REGRESSION ; MODELS ; SIGNAL |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000291807200006 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/2806]  |
| 专题 | 自动化研究所_模式识别国家重点实验室_多媒体计算与图形学团队 离退休人员 |
| 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 |
| 推荐引用方式 GB/T 7714 | He, Ran,Zheng, Wei-Shi,Hu, Bao-Gang,et al. Maximum Correntropy Criterion for Robust Face Recognition[J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,2011,33(8):1561-1576. |
| APA | He, Ran,Zheng, Wei-Shi,Hu, Bao-Gang,Ran He,&Baogang Hu.(2011).Maximum Correntropy Criterion for Robust Face Recognition.IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,33(8),1561-1576. |
| MLA | He, Ran,et al."Maximum Correntropy Criterion for Robust Face Recognition".IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 33.8(2011):1561-1576. |
入库方式： OAI收割
来源：自动化研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。