Cross-Modality Face Recognition via Heterogeneous Joint Bayesian
Shi, Hailin1; Wang, Xiaobo1; Yi, Dong2; Lei, Zhen3; Zhu, Xiangyu1; Li, Stan Z.1
2017
发表期刊IEEE SIGNAL PROCESSING LETTERS
卷号24期号:1页码:81-85
文章类型Article
摘要In many face recognition applications, the modalities of face images between the gallery and probe sets are different, which is known as heterogeneous face recognition. How to reduce the feature gap between images from different modalities is a critical issue to develop a highly accurate face recognition algorithm. Recently, joint Bayesian (JB) has demonstrated superior performance on general face recognition compared to traditional discriminant analysis methods like subspace learning. However, the original JB treats the two input samples equally and does not take into account the modality difference between them and may be suboptimal to address the heterogeneous face recognition problem. In this work, we extend the original JB by modeling the gallery and probe images using two different Gaussian distributions to propose a heterogeneous joint Bayesian (HJB) formulation for cross-modality face recognition. The proposed HJB explicitly models the modality difference of image pairs and, therefore, is able to better discriminate the same/different face pairs accurately. Extensive experiments conducted in the case of visible-near-infrared and ID photo versus spot face recognition problems show the superiority of the HJB over previous methods.
关键词Cross Modality Heterogeneous Face Recognition Joint Bayesian (Jb)
WOS标题词Science & Technology ; Technology
DOI10.1109/LSP.2016.2637400
收录类别SCI
语种英语
项目资助者National Key Research and Development Plan(2016YFC0801002) ; Chinese National Natural Science Foundation(61473291 ; AuthenMetric RD Funds ; 61572501 ; 61502491 ; 61572536)
WOS研究方向Engineering
WOS类目Engineering, Electrical & Electronic
WOS记录号WOS:000393813700003
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/14379
专题模式识别国家重点实验室_生物识别与安全技术研究
作者单位1.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
2.Alibaba Grp, Hangzhou 311121, Peoples R China
3.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
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GB/T 7714
Shi, Hailin,Wang, Xiaobo,Yi, Dong,et al. Cross-Modality Face Recognition via Heterogeneous Joint Bayesian[J]. IEEE SIGNAL PROCESSING LETTERS,2017,24(1):81-85.
APA Shi, Hailin,Wang, Xiaobo,Yi, Dong,Lei, Zhen,Zhu, Xiangyu,&Li, Stan Z..(2017).Cross-Modality Face Recognition via Heterogeneous Joint Bayesian.IEEE SIGNAL PROCESSING LETTERS,24(1),81-85.
MLA Shi, Hailin,et al."Cross-Modality Face Recognition via Heterogeneous Joint Bayesian".IEEE SIGNAL PROCESSING LETTERS 24.1(2017):81-85.
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