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Attribute Prototype Learning for Interactive Face Retrieval

文献类型：期刊论文

作者Fang, Yuchun2; Xiao, Zhengye2; Zhang, Wei2; Huang, Yan1,3; Wang, Liang1,4,5; Boujemaa, Nozha6; Geman, Donald7,8
刊名IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
出版日期2021
卷号16页码:2593-2607
关键词Prototypes Faces Face recognition Databases Adaptation models Coherence Semantics Facial attribute prototype learning interactive retrieval
ISSN号1556-6013
DOI10.1109/TIFS.2021.3059274
通讯作者Fang, Yuchun(ycfang@shu.edu.cn)
英文摘要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.
资助项目National Natural Science Foundation of China[61976132] ; Natural Science Foundation of Shanghai[19ZR1419200]
WOS研究方向Computer Science ; Engineering
语种英语
WOS记录号WOS:000628908000001
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
资助机构National Natural Science Foundation of China ; Natural Science Foundation of Shanghai
源URL[http://ir.ia.ac.cn/handle/173211/44048]  
专题自动化研究所_智能感知与计算研究中心
通讯作者Fang, Yuchun
作者单位1.Chinese Acad Sci CASIA, Inst Automat, Natl Lab Pattern Recognit NLPR, Ctr Res Intelligent Percept & Comp CRIPAC, Beijing 100049, Peoples R China
2.Shanghai Univ, Sch Comp Engn & Sci, Shanghai 200444, 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.

入库方式： OAI收割

来源：自动化研究所

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