步态识别研究综述

doi:10.3778/j.issn.1002-8331.2410-0291

摘要/Abstract

摘要： 步态识别是一种生物识别技术，通过摄像头对人的行走方式分析来进行身份识别，具有远距离、难以欺骗和在低分辨率下也可以工作的优点。近年来，随着深度学习技术的迅速发展，步态识别技术在与深度学习技术的融合中得到了显著的发展，特别是卷积神经网络、循环神经网络、自编码器和生成对抗网络在步态识别中的应用大大提高了步态识别的效率与准确率。综述了步态识别技术的发展，包括步态识别的独特特征、发展历史以及近年来的研究文献。列出了不同的数据集并对其特点进行了讨论，提出了一种对步态识别技术的分类方法，包括基于身体表征和基于模板的方法。探讨了步态识别在一些场景中的应用以及存在的一些问题，包括容易丢失时间和细粒度的空间信息等缺陷，并对步态识别的未来发展方向进行了进一步的探讨。

关键词: 步态识别, 深度学习, 身体表征, 步态模板

Abstract: Gait recognition is a biometric technology, which is used to identify people by analyzing their walking patterns through cameras. It has the advantages of long-distance operation, being difficult to spoof, and working at low resolution. In recent years, with the rapid development of deep learning technology, gait recognition technology has been significantly developed in the integration with deep learning technology, especially the application of convolutional neural networks, circular neural networks, self-encoder, and generative confrontation networks in gait recognition has greatly improved the efficiency and accuracy of gait recognition. This paper summarizes the development of gait recognition technology, including its unique characteristics, development history, and literature review in recent years. The paper lists different data sets and discusses their different characteristics, and proposes a classification method of gait recognition technology, including body representation-based and template-based methods. In addition, it discusses the application of gait recognition in some scenes and the existing problems, including the defects of easy loss of time and fine-grained spatial information, and further discusses the future development direction of gait recognition.

Key words: gait recognition, deep learning, physical representation, gait template

史晓国, 云静, 张钰莹, 刘雪颖. 步态识别研究综述[J]. 计算机工程与应用, 2025, 61(14): 65-87.

SHI Xiaoguo, YUN Jing, ZHANG Yuying, LIU Xueying. Review of Gait Recognition Research[J]. Computer Engineering and Applications, 2025, 61(14): 65-87.

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