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Gait recognition using multichannel convolution neural networks

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Abstract

Human gait recognition has a wide range of applications in multiple fields, such as video surveillance, digital security, and forensics. In this paper, we investigate the challenging problem of cross-view gait recognition and propose a novel gait recognition scheme by utilizing the strong expression of convolution neural networks (CNN). First, instead of using gait energy images in traditional gait recognition, we will design a new gait feature representation, trituple gait silhouettes, constructed by using consecutive gait silhouette pictures. Second, we will construct a multichannel CNN network to tackle a set of sequential images in parallel. Each of the image datasets is treated as one input channel, and a different convolutional kernel is used. Finally, the proposed approach is evaluated extensively based on the CASIA gait dataset A/B for cross-view gait recognition, and further on the OU-ISIR large population gait dataset to verify its generalization capability with large-scale data. To the best of our knowledge, this is the first time that this gait recognition scheme is presented. All our experimental results show that the proposed method obtains better performance when compared to those existing methods.

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Acknowledgements

This work was supported in part by the National Natural Science Foundation of China (NSFC) under Grant Nos. 61303146 and 61602431 as well as a scholarship of the China Scholarship Council (CSC) (Gran No. 201708330459). We thank reviewers for their constructive suggestions and valuable comments.

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Authors and Affiliations

  1. No. 258, Xueyuan Street, Hangzhou, 310018, China

    Xiuhui Wang & Jiajia Zhang

  2. No. 2-14, Wakefiled Street, Auckland, 1010, New Zealand

    Wei Qi Yan

Authors
  1. Xiuhui Wang
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  2. Jiajia Zhang
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  3. Wei Qi Yan
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Correspondence to Xiuhui Wang.

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We declare that we have not financial and personal relationships with other people or organizations that can inappropriately influence our work, there is no professional or other personal interest of any nature or kind in any product, service and/or company that could be construed as influencing the position presented in, or the review of, the manuscript entitled “Gait Recognition Using Multichannel Convolution Neural Networks”.

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This work was completed when the Xiuhui Wang was a visiting scholar with the Auckland University of Technology, New Zealand.

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Wang, X., Zhang, J. & Yan, W.Q. Gait recognition using multichannel convolution neural networks. Neural Comput & Applic 32, 14275–14285 (2020). https://doi.org/10.1007/s00521-019-04524-y

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