Journal of Applied Optics, Volume. 44, Issue 1, 71(2023)

Gait recognition method of infrared human body images based on improved ViT

Yanchen YANG1, Lijun YUN1,2、*, Jianhua MEI1, and Lin LU3
Author Affiliations
  • 1College of Information, Yunnan Normal University, Kunming 650500, China
  • 2Yunnan Provincial Key Laboratory of Optoelectronic Information Technology, Kunming 650500, China
  • 3Department of Equipment Information, Yunnan Tobacco Leaf Company, Kunming 650218, China
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    References(8)

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    [4] [4] WANG H, YUAN H. Gait Recognition based on lightweight CNNs[C]//Proceedings of the 2021 international workshop on modern science and technology. [S. l. ]: The International Center of National University Corporation Kitami Institute of Technology, 2021: 185-190.

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    [8] [8] DOSOVITSKIY A, BEYER L, KOLESNIKOV A, et al. An image is worth 16×16 words: transformers for image recognition at scale[EB/OL]. (2021-06-03)[2022-03-21]. https://arxiv.org/abs/2010.11929.

    [16] [16] HE K, ZHANG X, REN S, et al. Identity mappings in deep residual networks[C]//European conference on computer vision. Switzerland: Springer, Cham, 2016: 630-645.

    [18] [18] STEINER A, KOLESNIKOV A, ZHAI X, et al. How to train your ViT? data, augmentation, and regularization in vision transformers[EB/OL]. (2021-06-18)[2022-03-21]. https://arxiv.org/abs/2106.10270v1.

    [19] [19] ZHAI X, KOLESNIKOV A, HOULSBY N, et al. Scaling vision transformers[EB/OL]. (2021-06-08)[2022-03-21].https://arxiv.org/abs/2106.04560.

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    Yanchen YANG, Lijun YUN, Jianhua MEI, Lin LU. Gait recognition method of infrared human body images based on improved ViT[J]. Journal of Applied Optics, 2023, 44(1): 71

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    Paper Information

    Category: Research Articles

    Received: Mar. 21, 2022

    Accepted: --

    Published Online: Feb. 22, 2023

    The Author Email: Lijun YUN (yunlijun@ynnu.edu.cn)

    DOI:10.5768/JAO202344.0102002

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