驾驶员安全带检测方法研究综述

doi:10.3778/j.issn.1002-8331.2212-0108

摘要/Abstract

摘要： 驾驶员安全带检测作为计算机视觉的一个具体应用领域，目前基于计算机视觉相关技术的驾驶员安全带检测方法以节约人力、实时监督、高精度等优势逐渐成为研究热点。对近年来驾驶员安全带检测方法进行了系统性的分析和总结，对驾驶员安全带检测背景和传统传感器检测方法进行了简要说明；介绍了数字图像处理和机器学习的相关方法，分析总结其优缺点；重点分析和总结了深度学习的方法，从模型训练常用方法、卷积神经网络和衍生的目标检测算法的发展历程及其在驾驶员安全带检测中的应用三个方面进行介绍；对当前研究仍面临的问题以及进一步的研究方向进行了总结和展望。

关键词: 驾驶员安全带检测, 计算机视觉, 图像处理, 深度学习, 目标检测

Abstract: Driver safety belt detection is a specific application field of computer vision. At present, driver safety belt detection method based on computer vision related technology has become a research hotspot with the advantages of saving manpower, real-time supervision, high accuracy and so on. This paper systematically analyses and summarizes the methods of driver’s seat belt detection in recent years. Firstly, the background of driver’s seat belt detection and traditional sensor detection methods are briefly described. Secondly, the related methods of digital image processing and machine learning are introduced, and their advantages and disadvantages are analyzed and summarized. Then, the methods of in-depth learning are mainly analyzed and summarized, and the development of common model training methods, convolution neural network and derived target detection algorithms and their applications in driver’s seat belt detection are introduced. Finally, it summarizes and prospects the current research problems and further research directions.

Key words: driver seat belt detection, computer vision, image processing, deep learning, object detection

徐国新, 李雷孝, 何嘉彬, 高昊昱. 驾驶员安全带检测方法研究综述[J]. 计算机工程与应用, 2023, 59(17): 48-66.

XU Guoxin, LI Leixiao, HE Jiabin, GAO Haoyu. Review of Research on Driver Seat Belt Detection Methods[J]. Computer Engineering and Applications, 2023, 59(17): 48-66.

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