Optics and Precision Engineering, Volume. 31, Issue 2, 263(2023)

Gait recognition algorithm in dense occlusion scene

Yi GAO1 and Miao HE2、*
Author Affiliations
  • 1Key Laboratory of Impression Evidence Examination and Identification Technology (Criminal Investigation Police University of China), Ministry of Public Security, People's Republic of China, Shenyang0035, China
  • 2Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang110016, China
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    References(21)

    [1] DENG J K, GUO J, XUE N N et al. ArcFace: additive angular margin loss for deep face recognition[C], 4685-4694(2020).

    [2] YE M, SHEN J B, LIN G J et al. Deep learning for person re-identification: a survey and outlook[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44, 2872-2893(2022).

    [3] [3] 3高毅. 基于步态识别的跨场景多目标跟踪算法[J]. 控制工程, 2021, 28(7): 1375-1381.GAOY. Multi-camera multi-target tracking algorithm based on gait recognition[J]. Control Engineering of China, 2021, 28(7): 1375-1381.(in Chinese)

    [4] ZHENG J K, LIU X C, LIU W et al. Gait recognition in the wild with dense 3D representations and A benchmark[C], 20196-20205(2022).

    [5] SUN Y, BAO Q, LIU W et al. Monocular, one-stage, regression of multiple 3D people[C], 11159-11168(2022).

    [6] CHEN X, WENG J, LU W et al. Multi-gait recognition based on attribute discovery[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 40, 1697-1710(2018).

    [7] WU Z F, HUANG Y Z, WANG L et al. A comprehensive study on cross-view gait based human identification with deep CNNs[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39, 209-226(2017).

    [8] HE Y W, ZHANG J P, SHAN H M et al. Multi-task GANs for view-specific feature learning in gait recognition[J]. IEEE Transactions on Information Forensics and Security, 14, 102-113(2019).

    [9] LIAO R J, CAO C S, GARCIA E B et al. Pose-based Temporal-spatial Network PTSN for Gait Recognition with Carrying and Clothing Variations[M]. Biometric Recognition, 474-483(2017).

    [10] WOLF T, BABAEE M, RIGOLL G. Multi-view gait recognition using 3D convolutional neural networks[C], 4165-4169(2016).

    [11] WU X H, AN W Z, YU S Q et al[M]. Spatial-temporal graph attention network for video-based gait recognition(2020).

    [12] CHAO H Q, WANG K, HE Y W et al. GaitSet: cross-view gait recognition through utilizing gait As a deep set[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44, 3467-3478(2022).

    [13] YU S Q, TAN D L, TAN T N. A framework for evaluating the effect of view angle, clothing and carrying condition on gait recognition[C], 441-444(2006).

    [14] ZHONG Z, ZHENG L, KANG G L et al. Random erasing data augmentation[J]. Proceedings of the AAAI Conference on Artificial Intelligence, 34, 13001-13008(2020).

    [15] LIU R, LEHMAN J, MOLINO P et al. An intriguing failing of convolutional neural networks and the CoordConv solution[C], 9628-9639(2018).

    [16] [16] 16韩东岳, 桑海峰. 利用动态步态图进行步态识别[J]. 电子测量与仪器学报, 2022, 36(2): 139-145.HAND Y, SANGH F. Gait recognition based on dynamic gait image[J]. Journal of Electronic Measurement and Instrumentation, 2022, 36(2): 139-145.(in Chinese)

    [17] [17] 17曾维, 何刚强, 罗伟洋, 等. 基于ICNet模型的人体步态识别研究[J]. 电子测量技术, 2022, 45(4): 120-125.ZENGW, HEG Q, LUOW Y, et al. Research on gait recognition of human body based on ICNet model[J]. Electronic Measurement Technology, 2022, 45(4): 120-125.(in Chinese)

    [18] [18] 18周潇涵, 王修晖. 基于非对称双路识别网络的步态识别方法[J]. 计算机工程与应用, 2022, 58(4): 150-156. doi: 10.3778/j.issn.1002-8331.2008-0355ZHOUX H, WANGX H. Novel gait recognition method based on asymmetric two-path network[J]. Computer Engineering and Applications, 2022, 58(4): 150-156.(in Chinese). doi: 10.3778/j.issn.1002-8331.2008-0355

    [19] [19] 19胡少晖, 王修晖, 刘砚秋. 基于多支路残差深度网络的跨视角步态识别方法[J]. 模式识别与人工智能, 2021, 34(5): 455-462.HUSH H, WANGX H, LIUY Q. Cross-view gait recognition method based on multi-branch residual deep network[J]. Pattern Recognition and Artificial Intelligence, 2021, 34(5): 455-462.(in Chinese)

    [20] KOVAČ J, ŠTRUC V, PEER P. Frame-based classification for cross-speed gait recognition[J]. Multimedia Tools and Applications, 78, 5621-5643(2019).

    [21] [21] 21罗正平, 刘延钧, 杨天奇. 光流分量分解的步态识别[J]. 计算机科学, 2016, 43(9): 295-300. doi: 10.11896/j.issn.1002-137X.2016.09.059LUOZH P, LIUY J, YANGT Q. Gait recognition based on decomposition of optical flow components[J]. Computer Science, 2016, 43(9): 295-300.(in Chinese). doi: 10.11896/j.issn.1002-137X.2016.09.059

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    Paper Information

    Category: Information Sciences

    Received: Sep. 11, 2022

    Accepted: --

    Published Online: Feb. 9, 2023

    The Author Email: Miao HE (hemiao@sia.cn)

    DOI:10.37188/OPE.20233102.0263

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