Biview face recognition in the shape-texture domain | |
Xiao, Bing1,2; Gao, Xinbo1; Tao, Dacheng3![]() ![]() | |
刊名 | pattern recognition
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2013-07-01 | |
卷号 | 46期号:7页码:1906-1919 |
关键词 | Face recognition Texture model Shape topology Graph edit distance Active appearance model |
英文摘要 | face recognition is one of the biometric identification methods with the highest potential. the existing face recognition algorithms relying on the texture information of face images are affected greatly by the variation of expression, scale and illumination. whereas the algorithms based on the shape topology weaken the influence of illumination to some extent, but the impact of expression, scale and illumination on face recognition is still unsolved. to this end, we propose a new method for face recognition by integrating texture information with shape information, called biview face recognition algorithm. the texture models are constructed by using subspace learning methods and shape topologies are formed by building graphs for face images. the proposed biview face recognition method is compared with recognition algorithms merely based on texture or shape information. experimental results of recognizing faces under the variation of illumination, expression and scale demonstrate that the performance of the proposed biview face recognition outperforms texture-based and shape-based algorithms. (c) 2012 elsevier ltd. all rights reserved. |
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] | graph edit distance ; tensor discriminant-analysis ; active appearance models ; subspace selection ; component analysis ; projections ; eigenfaces ; algorithms |
收录类别 | SCI ; EI |
语种 | 英语 |
WOS记录号 | WOS:000317886600017 |
公开日期 | 2015-06-30 |
内容类型 | 期刊论文 |
源URL | [http://ir.opt.ac.cn/handle/181661/23484] ![]() |
专题 | 西安光学精密机械研究所_光学影像学习与分析中心 |
作者单位 | 1.Xidian Univ, Sch Elect Engn, Xian 710071, Peoples R China 2.Shaanxi Normal Univ, Sch Comp Sci, Xian 710062, Peoples R China 3.Univ Technol Sydney, Fac Engn & Informat Technol, Ctr Quantum Computat & Intelligent Syst, Ultimo, NSW 2007, Australia 4.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Ctr OPT IMagery Anal & Learning OPTIMAL, State Key Lab Transient Opt & Photon, Xian 710119, Shaanxi, Peoples R China |
推荐引用方式 GB/T 7714 | Xiao, Bing,Gao, Xinbo,Tao, Dacheng,et al. Biview face recognition in the shape-texture domain[J]. pattern recognition,2013,46(7):1906-1919. |
APA | Xiao, Bing,Gao, Xinbo,Tao, Dacheng,&Li, Xuelong.(2013).Biview face recognition in the shape-texture domain.pattern recognition,46(7),1906-1919. |
MLA | Xiao, Bing,et al."Biview face recognition in the shape-texture domain".pattern recognition 46.7(2013):1906-1919. |
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