现代信息科技2026，Vol.10Issue(11)：126-132,137,8.DOI:10.19850/j.cnki.2096-4706.2026.11.022
基于面部多特征融合的疲劳驾驶检测系统设计
Design of Fatigue Driving Detection System Based on Facial Multi-feature Fusion
摘要
Abstract
To address the frequent traffic accidents caused by fatigue driving,this paper designs a fatigue driving detection system based on multi-feature fusion.The system utilizes Dlib and OpenCV to extract key features of drivers,including eye-opening degree,mouth action units,and head posture angles.These features are integrated with machine learning algorithms to construct a classification model for identifying fatigue states.Experimental results demonstrate that the method achieves an accuracy rate of 97.6％on a self-built dataset,significantly enhancing the robustness of fatigue detection.The research validates the application value of multi-feature fusion strategies in driving behavior monitoring and provides technical support for mitigating traffic accident risks.关键词
疲劳驾驶检测/面部特征/特征提取/多特征融合Key words
fatigue driving detection/facial feature/feature extraction/multi-feature fusion分类
信息技术与安全科学引用本文复制引用
武伟,李佳健,陈奕锦,王子荣,席梓晗..基于面部多特征融合的疲劳驾驶检测系统设计[J].现代信息科技,2026,10(11):126-132,137,8.基金项目
山西大同大学教学改革创新项目(XJG2023262) （XJG2023262）
大同市科技局应用基础研究项目(2024080) （2024080）
山西省高等学校教学改革创新项目(J20241141) （J20241141）
