Robust linear representation via exploiting structure prior
文献类型：期刊论文
| 作者 | Wang, Dong ; He, Ran; Wang, Liang; Tan, Tieniu
|
| 刊名 | PATTERN RECOGNITION
 |
| 出版日期 | 2018-04-01 |
| 卷号 | 76期号:NA页码:560-568 |
| 关键词 | Linear Representation Half-quadratic Optimization Occlusion Prior |
| DOI | 10.1016/j.patcog.2017.08.027 |
| 文献子类 | Article |
| 英文摘要 | Over the past few years, linear representation models have seen a lot of successful applications such as face recognition in computer vision. In the context of face recognition, occlusion is a key factor that often curbs the performance of practical face recognition systems. In this paper, we propose to alleviate such negative influence of the occlusion noises by explicitly encoding the spatial continuity prior of the occlusion. Given the fact that many real-world occlusions such as sunglasses and scarves are contiguous, taking such prior into account can help build a more accurate model and achieve higher recognition rates. Besides, a general framework has also been proposed in which many off-the-shelf linear representation models can be nicely incorporated. And the minimization objectives of all these models can be solved via the same Half-Quadratic optimization procedure. Therefore the robustness of these models to occlusions can be comprehensively evaluated on a fair platform. Extensive experiments on the AR and Extended Yale B face databases corroborate that the proposed algorithms can improve the model robustness to contiguous occlusions. (C) 2017 Elsevier Ltd. All rights reserved. |
| WOS关键词 | FACE RECOGNITION ; SPARSE REPRESENTATION ; SUBSPACES |
| WOS研究方向 | Computer Science ; Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:000424853800041 |
| 资助机构 | National Basic Research Program of China(2012CB316302) |
| 源URL | [http://ir.ia.ac.cn/handle/173211/21078]  |
| 专题 | 自动化研究所_智能感知与计算研究中心 |
| 作者单位 | Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Ctr Res Intelligent Percept & Comp, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang, Dong,He, Ran,Wang, Liang,et al. Robust linear representation via exploiting structure prior[J]. PATTERN RECOGNITION,2018,76(NA):560-568. |
| APA | Wang, Dong,He, Ran,Wang, Liang,&Tan, Tieniu.(2018).Robust linear representation via exploiting structure prior.PATTERN RECOGNITION,76(NA),560-568. |
| MLA | Wang, Dong,et al."Robust linear representation via exploiting structure prior".PATTERN RECOGNITION 76.NA(2018):560-568. |
入库方式： OAI收割
来源：自动化研究所
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