Cross-Modality Face Recognition via Heterogeneous Joint Bayesian
文献类型：期刊论文
| 作者 | Shi, Hailin1 ; Wang, Xiaobo1; Yi, Dong2; Lei, Zhen3; Zhu, Xiangyu1; Li, Stan Z.1
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| 刊名 | IEEE SIGNAL PROCESSING LETTERS
 |
| 出版日期 | 2017 |
| 卷号 | 24期号:1页码:81-85 |
| 关键词 | Cross Modality Heterogeneous Face Recognition Joint Bayesian (Jb) |
| DOI | 10.1109/LSP.2016.2637400 |
| 文献子类 | Article |
| 英文摘要 | 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. |
| WOS研究方向 | Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:000393813700003 |
| 资助机构 | National Key Research and Development Plan(2016YFC0801002) ; Chinese National Natural Science Foundation(61473291 ; AuthenMetric RD Funds ; 61572501 ; 61502491 ; 61572536) |
| 源URL | [http://ir.ia.ac.cn/handle/173211/14379]  |
| 专题 | 自动化研究所_模式识别国家重点实验室_生物识别与安全技术研究中心 |
| 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 |
| 推荐引用方式 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. |
入库方式： OAI收割
来源：自动化研究所
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