A Comprehensive Study on the Evaluation of Silhouette-based Gait Recognition

Hou，Saihui1; Fan，Chao2; Cao，Chunshui3; Liu，Xu3; Huang，Yongzhen1

2022

10.1109/TBIOM.2022.3216857

IEEE Transactions on Biometrics, Behavior, and Identity Science   Impact Factor & Quartile

2637-6407

2637-6407

Recently the methods based on silhouettes achieve significant improvement for gait recognition. The performance, e.g., 96.4% on the largest OUMVLP, indicates that a promising gait system is around the corner. However, we argue that the observation is not true. Firstly, we find that there exists a non-negligible gap of gait evaluation between academic research and practical applications. To validate the assumption, we conduct a comprehensive study on the evaluation for silhouette-based gait recognition and provide new insights into the limitations of the current methods. Our key findings include: (a) The current evaluation protocol is excessively simplified and ignores a lot of hard cases. (b) The current methods are sensitive to the noise caused by rotation and occlusion. Secondly, we observe that the data scarcity largely hinders the development of gait recognition and some crucial covariates (e.g., camera heights) are not thoroughly investigated. To address the issue, we propose a new dataset called Multi-Height Gait (MHG). It collects 200 subjects of normal walking, walking with bags and walking in different clothes. Particularly, it collects the sequences recorded by the cameras at different heights. We hope this work would inspire more advanced research for gait recognition. The project page is available at https://hshustc.github.io/TBIOM-Metric-Gait/.

Behavioral sciences Cameras Gait Dataset Gait Evaluation Gait Recognition Gait recognition Gait Silhouettes Legged locomotion Measurement Probes Protocols

English

Others

2-s2.0-85141538672

Scopus

1.School of Artificial Intelligence, Beijing Normal University, Beijing, China
2.Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China
3.Watrix Technology Limited Co. Ltd, Beijing, China

Hou，Saihui,Fan，Chao,Cao，Chunshui,et al. A Comprehensive Study on the Evaluation of Silhouette-based Gait Recognition[J]. IEEE Transactions on Biometrics, Behavior, and Identity Science,2022,PP(99):1-1.

Hou，Saihui,Fan，Chao,Cao，Chunshui,Liu，Xu,&Huang，Yongzhen.(2022).A Comprehensive Study on the Evaluation of Silhouette-based Gait Recognition.IEEE Transactions on Biometrics, Behavior, and Identity Science,PP(99),1-1.

Hou，Saihui,et al."A Comprehensive Study on the Evaluation of Silhouette-based Gait Recognition".IEEE Transactions on Biometrics, Behavior, and Identity Science PP.99(2022):1-1.