Gait recognition using a few gait frames

Author:

Yao Lingxiang1,Kusakunniran Worapan2,Wu Qiang1,Zhang Jian1

Affiliation:

1. School of Electrical and Data Engineering, University of Technology Sydney, Sydney, Australia

2. Faculty of Information and Communication Technology, Mahidol University, Nakhon Pathom, Thailand

Abstract

Gait has been deemed as an alternative biometric in video-based surveillance applications, since it can be used to recognize individuals from a far distance without their interaction and cooperation. Recently, many gait recognition methods have been proposed, aiming at reducing the influence caused by exterior factors. However, most of these methods are developed based on sufficient input gait frames, and their recognition performance will sharply decrease if the frame number drops. In the real-world scenario, it is impossible to always obtain a sufficient number of gait frames for each subject due to many reasons, e.g., occlusion and illumination. Therefore, it is necessary to improve the gait recognition performance when the available gait frames are limited. This paper starts with three different strategies, aiming at producing more input frames and eliminating the generalization error cause by insufficient input data. Meanwhile, a two-branch network is also proposed in this paper to formulate robust gait representations from the original and new generated input gait frames. According to our experiments, under the limited gait frames being used, it was verified that the proposed method can achieve a reliable performance for gait recognition.

Funder

Faculty of Information and Communication Technology, Mahidol University

Publisher

PeerJ

Subject

General Computer Science

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