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Robust linear representation via exploiting structure prior
Wang, Dong; He, Ran; Wang, Liang; Tan, Tieniu
2018-04-01
发表期刊PATTERN RECOGNITION
卷号76期号:NA页码:560-568
文章类型Article
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.
关键词Linear Representation Half-quadratic Optimization Occlusion Prior
WOS标题词Science & Technology ; Technology
DOI10.1016/j.patcog.2017.08.027
关键词[WOS]FACE RECOGNITION ; SPARSE REPRESENTATION ; SUBSPACES
收录类别SCI
语种英语
项目资助者National Basic Research Program of China(2012CB316302)
WOS研究方向Computer Science ; Engineering
WOS类目Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号WOS:000424853800041
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/21078
专题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
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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.
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