Bootstrapping Joint Bayesian Model for Robust Pace Verification
文献类型:会议论文
作者 | Cheng, Cheng; Xing, Junliang; Feng, Youji; Li, Deling; Zhou, Xiang-Dong |
出版日期 | 2016 |
会议日期 | JUN 13-16, 2016 |
会议地点 | Halmstad Univ, Halmstad, SWEDEN |
通讯作者 | Cheng, C (reprint author), Chinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Beijing 100864, Peoples R China. |
英文摘要 | Generative Bayesian models have exhibited good performance on the face verification problem, i.e., determining whether two faces are from the same person. As one of the most representative methods, the Joint Bayesian (JB) model represents two faces jointly by introducing some appropriate priors, providing better separability between different face classes. The EM-like learning algorithm of the JB model, however, are occasionally observed to have unsatisfactory converge property during the iterative training process. In this paper, we present a Bootstrapping Joint Bayesian (BJB) model which demonstrates good converging behavior. The BJB model explicitly addresses the classification difficulties of different classes by gradually re weighting the training samples and driving the Bayesian models to pay more attentions to the hard training samples. Experiments on a new challenging benchmark demonstrate promising results of the proposed model, compared to the baseline Bayesian models. |
会议录 | 2016 INTERNATIONAL CONFERENCE ON BIOMETRICS (ICB) |
语种 | 英语 |
ISSN号 | 2376-4201 |
WOS记录号 | WOS:000390841200042 |
源URL | [http://119.78.100.138/handle/2HOD01W0/379] |
专题 | 智能安全技术研究中心 |
作者单位 | (1) Chinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Beijing 100864, Peoples R China; (2) Chinese Acad Sci, Inst Automat, Beijing 100864, Peoples R China |
推荐引用方式 GB/T 7714 | Cheng, Cheng,Xing, Junliang,Feng, Youji,et al. Bootstrapping Joint Bayesian Model for Robust Pace Verification[C]. 见:. Halmstad Univ, Halmstad, SWEDEN. JUN 13-16, 2016. |
入库方式: OAI收割
来源:重庆绿色智能技术研究院
浏览0
下载0
收藏0
其他版本
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。