| Data Uncertainty in Face Recognition | |
Xu, Yong1,2; Fang, Xiaozhao1; Li, Xuelong3 ; Yang, Jiang4; You, Jane5; Liu, Hong6; Teng, Shaohua7
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| 作者部门 | 光学影像学习与分析中心 |
| 2014-10-01 | |
| 发表期刊 | IEEE TRANSACTIONS ON CYBERNETICS
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| ISSN | 2168-2267 |
| 卷号 | 44期号:10页码:1950-1961 |
| 摘要 | The image of a face varies with the illumination, pose, and facial expression, thus we say that a single face image is of high uncertainty for representing the face. In this sense, a face image is just an observation and it should not be considered as the absolutely accurate representation of the face. As more face images from the same person provide more observations of the face, more face images may be useful for reducing the uncertainty of the representation of the face and improving the accuracy of face recognition. However, in a real world face recognition system, a subject usually has only a limited number of available face images and thus there is high uncertainty. In this paper, we attempt to improve the face recognition accuracy by reducing the uncertainty. First, we reduce the uncertainty of the face representation by synthesizing the virtual training samples. Then, we select useful training samples that are similar to the test sample from the set of all the original and synthesized virtual training samples. Moreover, we state a theorem that determines the upper bound of the number of useful training samples. Finally, we devise a representation approach based on the selected useful training samples to perform face recognition. Experimental results on five widely used face databases demonstrate that our proposed approach can not only obtain a high face recognition accuracy, but also has a lower computational complexity than the other state-of-the-art approaches. |
| 文章类型 | Article |
| 关键词 | Computer Vision Face Recognition Machine Learning Pattern Recognition Uncertainty |
| WOS标题词 | Science & Technology ; Technology |
| DOI | 10.1109/TCYB.2014.2300175 |
| 收录类别 | SCI ; EI |
| 关键词[WOS] | SPARSE REPRESENTATION ; IMAGE ; CLASSIFICATION ; RESTORATION ; VECTOR ; POSE |
| 语种 | 英语 |
| WOS研究方向 | Computer Science |
| WOS类目 | Computer Science, Artificial Intelligence ; Computer Science, Cybernetics |
| WOS记录号 | WOS:000342228100020 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.opt.ac.cn/handle/181661/22370 |
| 专题 | 光谱成像技术研究室 |
| 作者单位 | 1.Harbin Inst Technol, Shenzhen Grad Sch, Biocomp Res Ctr, Shenzhen 518055, Peoples R China 2.Key Lab Network Oriented Intelligent Computat, Shenzhen 518055, Peoples R China 3.Chinese Acad Sci, Ctr Opt Imagery Anal & Learning, Xian Inst Opt & Precis Mech, State Key Lab Transient Opt & Photon, Xian 710119, Shaanxi, Peoples R China 4.Nanjing Univ Sci Sci & Technol, Sch Comp Sci & Technol, Nanjing 210094, Jiangsu, Peoples R China 5.Hong Kong Polytech Univ, Dept Comp, Kowloon, Hong Kong, Peoples R China 6.Peking Univ, Shenzhen Grad Sch, Engn Lab Intelligent Percept Internet Things, Shenzhen 518055, Peoples R China 7.Guangdong Univ Technol, Guangzhou 51006, Guangdong, Peoples R China |
| 推荐引用方式 GB/T 7714 | Xu, Yong,Fang, Xiaozhao,Li, Xuelong,et al. Data Uncertainty in Face Recognition[J]. IEEE TRANSACTIONS ON CYBERNETICS,2014,44(10):1950-1961. |
| APA | Xu, Yong.,Fang, Xiaozhao.,Li, Xuelong.,Yang, Jiang.,You, Jane.,...&Teng, Shaohua.(2014).Data Uncertainty in Face Recognition.IEEE TRANSACTIONS ON CYBERNETICS,44(10),1950-1961. |
| MLA | Xu, Yong,et al."Data Uncertainty in Face Recognition".IEEE TRANSACTIONS ON CYBERNETICS 44.10(2014):1950-1961. |
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| 文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
| Data Uncertainty in （17191KB） | 期刊论文 | 出版稿 | 限制开放 | CC BY | 请求全文 | |
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