基于高精度dlib疲劳检测技术的汽车安全系统模型  

Vehicle Safety System Model Based on High-precision Dlib Fatigue Detection Technology

作　　者：徐江和 韩桂明 李嘉伟 张永强 叶梅玉 XU Jianghe;HAN Guiming;LI Jiawei;ZHANG Yongqiang;YE Meiyu(Guilin University of Information Technology,Guilin 541214,China)

机构地区：[1]桂林信息科技学院,广西桂林541214

出　　处：《电子质量》2025年第3期57-60,共4页Electronics Quality

基　　金：2023年度广西高校中青年教师科研基础能力提升项目——基于高精度dlib疲劳检测技术的汽车安全系统模型(202313644004)资助。

摘　　要：随着汽车行业的快速发展,道路安全问题日益受到重视,疲劳驾驶是导致交通事故的主要因素之一。提出了一种基于高精度dlib疲劳检测技术的汽车安全系统模型,利用深度学习和图像处理技术,通过分析驾驶员面部特征来实时监测其疲劳状态。采用dlib库进行面部特征点的检测,通过计算眼睛的闭合程度、打哈欠频率和头部姿态变化,结合驾驶行为分析,准确评估驾驶员的疲劳程度。当检测到驾驶员疲劳时,系统会通过视觉和声音信号进行警告,提醒驾驶员采取措施,如休息或更换驾驶员,以保证行车安全。实验结果表明,该模型能够有效地识别疲劳驾驶行为,对于提高道路交通安全具有重要的意义。With the rapid development of the automobile industry,road safety has been paid more and more atten-tion.Fatigue driving is one of the main factors leading to traffic accidents.A vehicle safety system model based on high-precision dlib fatigue detection technology is proposed,which utilizes deep learning and image processing technology to monitor the fatigue state of drivers in real time by analyzing their facial features.The dlib library is used to detect facial feature points,and the fatigue degree of drivers is accurately assessed by calculating the degree of eye closure,yawning frequency and head posture changes,and analyzing driving behavior.When driver fatigue is detected,the system will warn through visual and sound signals to remind the driver to take measures,such as rest or replacement of the driver,to ensure driving safety.The experimental results show that the model can effectively identify fatigue driving behavior,which is of great significance for improving road traffic safety.

关 键 词：疲劳检测 深度学习 图像处理 驾驶员监测 交通安全 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论] U491.6[自动化与计算机技术—计算机科学与技术]