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

CORC > 西安光学精密机械研究所 > 中国科学院西安光学精密机械研究所 > 光学影像学习与分析中心

	Aging Face Recognition: A Hierarchical Learning Model Based on Local Patterns Selection
	Li, Zhifeng 1; Gong, Dihong 1; Li, Xuelong2 ; Tao, Dacheng3,4
刊名	ieee transactions on image processing
	2016-05-01
卷号	25 期号:5 页码:2146-2154
关键词	Face recognition aging faces feature descriptor
ISSN号	1057-7149
产权排序	2
英文摘要	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.
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]	automatic age estimation ; discriminant-analysis ; binary patterns ; verification ; simulation ; descriptor ; regression ; classification ; representation ; information
收录类别	SCI ; EI
语种	英语
WOS记录号	WOS:000373131000014
内容类型	期刊论文
源URL	[http://ir.opt.ac.cn/handle/181661/28080]
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.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.