A comprehensive study on gait biometrics using a joint CNN-based method

This paper gives a comprehensive study on gait biometrics via a joint CNN-based method. Gait is a kind of behavioral biometric feature with unique advantages, e.g., long-distance, cross-view and non-cooperative perception and analysis. In this paper, the definition of gait analysis includes gait rec...

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Bibliographic Details
Published in:Pattern recognition 2019-09, Vol.93, p.228-236
Main Authors: Zhang, Yuqi, Huang, Yongzhen, Wang, Liang, Yu, Shiqi
Format: Article
Language:English
Subjects:
Gait recognition
Joint learning
Network visualization
Soft biometrics
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Summary:This paper gives a comprehensive study on gait biometrics via a joint CNN-based method. Gait is a kind of behavioral biometric feature with unique advantages, e.g., long-distance, cross-view and non-cooperative perception and analysis. In this paper, the definition of gait analysis includes gait recognition and gait-based soft biometrics such as gender and age prediction. We propose to investigate these two problems in a joint CNN-based framework which has been seldom reported in the recent literature. The proposed method is efficient in terms of training time, testing time and storage. We achieve the state-of-the-art performance on several gait recognition and soft biometrics benchmarks. Also, we discuss which part of the human body is important and informative for a specific task by network visualization.
ISSN:0031-3203
1873-5142
DOI:10.1016/j.patcog.2019.04.023