A model-based gait recognition method with body pose and human prior knowledge

doi:10.1016/j.patcog.2019.107069

CORC > 自动化研究所 > 中国科学院自动化研究所 > 智能感知与计算研究中心

	A model-based gait recognition method with body pose and human prior knowledge
	Liao, Rijun 4,5; Yu, Shiqi 1,5; An, Weizhi 4,5; Huang, Yongzhen 2,3
刊名	PATTERN RECOGNITION
	2020-02-01
卷号	98 页码:11
关键词	Gait recognition Human body pose Spatio-temporal feature
ISSN号	0031-3203
DOI	10.1016/j.patcog.2019.107069
通讯作者	Yu, Shiqi(yusq@sustech.edu.cn)
英文摘要	We 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.
资助项目	National Natural Science Foundation of China[61976144] ; Science Foundation of Shenzhen[20170504160426188]
WOS关键词	IMAGE ; TRANSFORMATION ; BIOMETRICS
WOS研究方向	Computer Science ; Engineering
语种	英语
出版者	ELSEVIER SCI LTD
WOS记录号	WOS:000497600300005
资助机构	National Natural Science Foundation of China ; Science Foundation of Shenzhen
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/29375]
专题	自动化研究所_智能感知与计算研究中心
通讯作者	Yu, Shiqi
作者单位	1.Southern Univ Sci & Technol, Dept Comp Sci & Engn, Shenzhen, Guangdong, Peoples R China 2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China 3.Watrix Technol Ltd Co Ltd, Beijing, Peoples R China 4.Shenzhen Univ, Coll Comp Sci & Software Engn, Shenzhen, Guangdong, Peoples R China 5.Shenzhen Inst Artificial Intelligence & Robot Soc, Shenzhen, Guangdong, Peoples R China
推荐引用方式 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.