CASIA OpenIR  > 智能感知与计算研究中心
Learning Predictable Binary Codes for Face Indexing
Ran He(赫然)1,2; Yinghao Cai3; Tieniu Tan1,2; Larry Davis4,5
Source PublicationPATTERN RECOGNITION
2015-10-01
Volume48Issue:10Pages:3160-3168
SubtypeArticle
AbstractHigh dimensional dense features have been shown to be useful for face recognition, but result in high query time when searching a large-scale face database. Hence binary codes are often used to obtain fast query speeds as well as reduce storage requirements. However, binary codes for face features can become unstable and unpredictable due to face variations induced by pose, expression and illumination. This paper proposes a predictable hash code algorithm to map face samples in the original feature space to Hamming space. First, we discuss the 'predictability' of hash codes for face indexing. Second, we formulate the predictable hash coding problem as a non-convex combinatorial optimization problem, in which the distance between codes for samples from the same class is minimized while the distance between codes for samples from different classes is maximized. An Expectation Maximization method is introduced to iteratively find a sparse and predictable linear mapping. Lastly, a deep feature representation is learned to further enhance the predictability of binary codes. Experimental results on three commonly used face databases demonstrate the superiority of our predictable hash coding algorithm on large-scale problems. (C) 2015 Elsevier Ltd. All rights reserved.
KeywordBinary Codes Hashing Face Index Large Scale Feature Learning
WOS HeadingsScience & Technology ; Technology
WOS KeywordSPARSE REPRESENTATION ; RECOGNITION ; RETRIEVAL ; ALGORITHM
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS IDWOS:000357246100018
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Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/7901
Collection智能感知与计算研究中心
Affiliation1.Chinese Acad Sci, Ctr Res Intelligent Percept & Comp, Beijing 100190, Peoples R China
2.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100190, Peoples R China
3.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
4.Univ Maryland, Inst Adv Comp Studies, College Pk, MD 20742 USA
5.Univ Maryland, Dept Comp Sci, College Pk, MD 20742 USA
Recommended Citation
GB/T 7714
Ran He,Yinghao Cai,Tieniu Tan,et al. Learning Predictable Binary Codes for Face Indexing[J]. PATTERN RECOGNITION,2015,48(10):3160-3168.
APA Ran He,Yinghao Cai,Tieniu Tan,&Larry Davis.(2015).Learning Predictable Binary Codes for Face Indexing.PATTERN RECOGNITION,48(10),3160-3168.
MLA Ran He,et al."Learning Predictable Binary Codes for Face Indexing".PATTERN RECOGNITION 48.10(2015):3160-3168.
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