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 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. (C) 2019 Elsevier Ltd. All rights reserved.