Attribute Prototype Learning for Interactive Face Retrieval

doi:10.1109/TIFS.2021.3059274

CASIA OpenIR > 智能感知与计算研究中心

	Attribute Prototype Learning for Interactive Face Retrieval
	Fang, Yuchun 1; Xiao, Zhengye 1; Zhang, Wei 1; Huang, Yan2,3 ; Wang, Liang2,4,5 ; Boujemaa, Nozha 6; Geman, Donald 7,8
发表期刊	IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
ISSN	1556-6013
	2021
卷号	16 页码:2593-2607
通讯作者	Fang, Yuchun(ycfang@shu.edu.cn)
摘要	Interactive face retrieval aims at finding target subjects in face databases through human and machine interaction, which involves user feedback based on human perception and machine similarity measure in feature spaces. In this article, we propose an attribute prototype learning method to tackle the semantic gap between human and machine in face perception for fast interactive face retrieval. We reformulate the theoretical explanation of the interactive retrieval model and develop the algorithm of the heuristic solution of the model. Each module of the prototype model is learned with a set of identity-related facial attributes. The outputs of the prototype modules form the semantic representation. To adapt the prototype models across different databases, we propose a transfer selection algorithm based on the coherence measurements in interactive face retrieval. Coherence analysis proves that the proposed attribute prototype representation can effectively narrow down the semantic gap even in the case of cross-database transfer learning. The prototype representation can effectively reduce the feature dimension in the retrieval process. Real user retrieval with the Bayesian relevance feedback model shows that attribute prototype space is superior to low-level feature space and proves that interactive retrieval with attribute prototype representation can converge fast in large face databases.
关键词	Prototypes Faces Face recognition Databases Adaptation models Coherence Semantics Facial attribute prototype learning interactive retrieval
DOI	10.1109/TIFS.2021.3059274
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61976132] ; Natural Science Foundation of Shanghai[19ZR1419200]
项目资助者	National Natural Science Foundation of China ; Natural Science Foundation of Shanghai
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS记录号	WOS:000628908000001
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：4[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/44049
专题	智能感知与计算研究中心
通讯作者	Fang, Yuchun
作者单位	1.Shanghai Univ, Sch Comp Engn & Sci, Shanghai 200444, Peoples R China 2.Chinese Acad Sci CASIA, Inst Automat, Natl Lab Pattern Recognit NLPR, Ctr Res Intelligent Percept & Comp CRIPAC, Beijing 100049, Peoples R China 3.Univ Chinese Acad Sci UCAS, Beijing 100049, Peoples R China 4.Univ Chinese Acad Sci UCAS, Sch Artificial Intelligence, Beijing 100049, Peoples R China 5.Chinese Acad Sci CASIA, Inst Automat, Ctr Excellence Brain Sci & Intelligence Technol C, Beijing 100864, Peoples R China 6.Median Technol, F-06560 Valbonne, France 7.Johns Hopkins Univ, Dept Appl Math & Stat, Ctr Imaging Sci, Baltimore, MD 21218 USA 8.Johns Hopkins Univ, Inst Computat Med, Baltimore, MD 21218 USA
推荐引用方式 GB/T 7714	Fang, Yuchun,Xiao, Zhengye,Zhang, Wei,et al. Attribute Prototype Learning for Interactive Face Retrieval[J]. IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY,2021,16:2593-2607.
APA	Fang, Yuchun.,Xiao, Zhengye.,Zhang, Wei.,Huang, Yan.,Wang, Liang.,...&Geman, Donald.(2021).Attribute Prototype Learning for Interactive Face Retrieval.IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY,16,2593-2607.
MLA	Fang, Yuchun,et al."Attribute Prototype Learning for Interactive Face Retrieval".IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY 16(2021):2593-2607.