Aging Face Recognition: A Hierarchical Learning Model Based on Local Patterns Selection

doi:10.1109/TIP.2016.2535284

OPT OpenIR > 光谱成像技术研究室

	Aging Face Recognition: A Hierarchical Learning Model Based on Local Patterns Selection
	Li, Zhifeng 1; Gong, Dihong 1; Li, Xuelong2 ; Tao, Dacheng3,4
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
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	被引频次：61[WOS] [WOS记录] [WOS相关记录]
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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