中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
A model-based gait recognition method with body pose and human prior knowledge

文献类型:期刊论文

AuthorLiao, Rijun1,3; Yu, Shiqi1,4; An, Weizhi1,3; Huang, Yongzhen2,5
SourcePATTERN RECOGNITION
Issued Date2020-02-01
Volume98Pages:11
KeywordGait recognition Human body pose Spatio-temporal feature
ISSN0031-3203
DOI10.1016/j.patcog.2019.107069
Corresponding AuthorYu, Shiqi(yusq@sustech.edu.cn)
English AbstractWe propose in this paper a novel model-based gait recognition method, PoseGait. Gait recognition is a challenging and attractive task in biometrics. Early approaches to gait recognition were mainly appearance-based. The appearance-based features are usually extracted from human body silhouettes, which are easy to compute and have shown to be efficient for recognition tasks. Nevertheless silhouettes shape is not invariant to changes in clothing, and can be subject to drastic variations, due to illumination changes or other external factors. An alternative to silhouette-based features are model-based features. However, they are very challenging to acquire especially for low image resolution. In contrast to previous approaches, our model PoseGait exploits human 3D pose estimated from images by Convolutional Neural Network as the input feature for gait recognition. The 3D pose, defined by the 3D coordinates of joints of the human body, is invariant to view changes and other external factors of variation. We design spatio-temporal features from the 3D pose to improve the recognition rate. Our method is evaluated on two large datasets, CASIA B and CASIA E. The experimental results show that the proposed method can achieve state-of-the-art performance and is robust to view and clothing variations. (C) 2019 Elsevier Ltd. All rights reserved.
Funding ProjectNational Natural Science Foundation of China[61976144] ; Science Foundation of Shenzhen[20170504160426188]
WOS KeywordIMAGE ; TRANSFORMATION ; BIOMETRICS
WOS Research AreaComputer Science ; Engineering
Language英语
PublisherELSEVIER SCI LTD
WOS IDWOS:000497600300005
Funding OrganizationNational Natural Science Foundation of China ; Science Foundation of Shenzhen
源URL[http://ir.ia.ac.cn/handle/173211/29375]  
Collection中国科学院自动化研究所
Corresponding AuthorYu, Shiqi
Affiliation1.Shenzhen Inst Artificial Intelligence & Robot Soc, Shenzhen, Guangdong, Peoples R China
2.Watrix Technol Ltd Co Ltd, Beijing, Peoples R China
3.Shenzhen Univ, Coll Comp Sci & Software Engn, Shenzhen, Guangdong, Peoples R China
4.Southern Univ Sci & Technol, Dept Comp Sci & Engn, Shenzhen, Guangdong, Peoples R China
5.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Liao, Rijun,Yu, Shiqi,An, Weizhi,et al. A model-based gait recognition method with body pose and human prior knowledge[J]. PATTERN RECOGNITION,2020,98:11.
APA Liao, Rijun,Yu, Shiqi,An, Weizhi,&Huang, Yongzhen.(2020).A model-based gait recognition method with body pose and human prior knowledge.PATTERN RECOGNITION,98,11.
MLA Liao, Rijun,et al."A model-based gait recognition method with body pose and human prior knowledge".PATTERN RECOGNITION 98(2020):11.

入库方式: OAI收割

来源:自动化研究所

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