A model-based gait recognition method with body pose and human prior knowledge
文献类型：期刊论文
| 作者 | Liao, Rijun1,3; Yu, Shiqi1,4; An, Weizhi1,3; Huang, Yongzhen2,5
|
| 刊名 | PATTERN RECOGNITION
 |
| 出版日期 | 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. |
| WOS关键词 | IMAGE ; TRANSFORMATION ; BIOMETRICS |
| 资助项目 | National Natural Science Foundation of China[61976144] ; Science Foundation of Shenzhen[20170504160426188] |
| WOS研究方向 | Computer Science ; Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:000497600300005 |
| 出版者 | ELSEVIER SCI LTD |
| 资助机构 | National Natural Science Foundation of China ; Science Foundation of Shenzhen |
| 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.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 |
| 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. |
入库方式： OAI收割
来源：自动化研究所
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