Aging Face Recognition: A Hierarchical Learning Model Based on Local Patterns Selection | |
Li, Zhifeng1; Gong, Dihong1; Li, Xuelong2![]() ![]() | |
作者部门 | 光学影像学习与分析中心 |
2016-05-01 | |
发表期刊 | IEEE TRANSACTIONS ON IMAGE PROCESSING
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ISSN | 1057-7149 |
卷号 | 25期号:5页码:2146-2154 |
产权排序 | 2 |
摘要 | Aging face recognition refers to matching the same person's faces across different ages, e.g., matching a person's older face to his (or her) younger one, which has many important practical applications, such as finding missing children. The major challenge of this task is that facial appearance is subject to significant change during the aging process. In this paper, we propose to solve the problem with a hierarchical model based on two-level learning. At the first level, effective features are learned from low-level microstructures, based on our new feature descriptor called local pattern selection (LPS). The proposed LPS descriptor greedily selects low-level discriminant patterns in a way, such that intra-user dissimilarity is minimized. At the second level, higher level visual information is further refined based on the output from the first level. To evaluate the performance of our new method, we conduct extensive experiments on the MORPH data set (the largest face aging data set available in the public domain), which show a significant improvement in accuracy over the state-of-the-art methods. |
文章类型 | Article |
关键词 | Face Recognition Aging Faces Feature Descriptor |
WOS标题词 | Science & Technology ; Technology |
DOI | 10.1109/TIP.2016.2535284 |
收录类别 | SCI ; EI |
关键词[WOS] | AUTOMATIC AGE ESTIMATION ; DISCRIMINANT-ANALYSIS ; BINARY PATTERNS ; VERIFICATION ; SIMULATION ; DESCRIPTOR ; REGRESSION ; CLASSIFICATION ; REPRESENTATION ; INFORMATION |
语种 | 英语 |
WOS研究方向 | Computer Science ; Engineering |
项目资助者 | Natural Science Foundation of Guangdong Province(2014A030313688) ; Key Laboratory of Human-Machine Intelligence-Synergy Systems through the Chinese Academy of Sciences ; Australian Research Council(DP-140102164 ; National Natural Science Foundation of China(61103164) ; Shenzhen Basic Research Program(JCYJ20120617114614438) ; Shun Hing Institute of Advanced Engineering, The Chinese University of Hong Kong(MMT-8115038) ; FT-130101457) |
WOS类目 | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic |
WOS记录号 | WOS:000373131000014 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.opt.ac.cn/handle/181661/28080 |
专题 | 光谱成像技术研究室 |
作者单位 | 1.Chinese Acad Sci, Shenzhen Inst Adv Technol, Shenzhen 518055, Peoples R China 2.Chinese Acad Sci, Ctr OPT IMagery Anal & Learning OPTIMAL, State Key Lab Transient Opt & Photon, Xian Inst Opt & Precis Mech, Xian 710119, Peoples R China 3.Univ Technol Sydney, Ctr Quantum Computat & Intelligent Syst, 81 Broadway St, Ultimo, NSW 2007, Australia 4.Univ Technol Sydney, Fac Engn & Informat Technol, 81 Broadway St, Ultimo, NSW 2007, Australia |
推荐引用方式 GB/T 7714 | Li, Zhifeng,Gong, Dihong,Li, Xuelong,et al. Aging Face Recognition: A Hierarchical Learning Model Based on Local Patterns Selection[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2016,25(5):2146-2154. |
APA | Li, Zhifeng,Gong, Dihong,Li, Xuelong,&Tao, Dacheng.(2016).Aging Face Recognition: A Hierarchical Learning Model Based on Local Patterns Selection.IEEE TRANSACTIONS ON IMAGE PROCESSING,25(5),2146-2154. |
MLA | Li, Zhifeng,et al."Aging Face Recognition: A Hierarchical Learning Model Based on Local Patterns Selection".IEEE TRANSACTIONS ON IMAGE PROCESSING 25.5(2016):2146-2154. |
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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 | ||
Aging Face Recogniti(1960KB) | 期刊论文 | 作者接受稿 | 限制开放 | CC BY-NC-SA | 请求全文 |
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