Application of Vehicle Driver Fatigue Detection Based on YOLOv8
Fatigue driving is the main cause of traffic accidents.Due to the complexity and real-time requirements of fatigue driving detection scenarios,a vehicle driver fatigue detection and warning design method based on YOLOv8 is proposed.The YOLOv8 algorithm is improved in attention mechanism,data augmentation,lightweight network,etc.to improve the recognition accuracy and detection rate of vehicle driver fatigue detection.Mean while,key facial points are extracted to calculate the eye aspect ratio(EAR),and a fatigue evaluation classification model is established to achieve comprehensive judgment and warning of fatigue driving.A vehicle driver fatigue detection experimental platform is built to verify it.The results show that this approach can accurately obtain fatigue detection results,with an accuracy rate of 94％.
YOLOv8fatigue testingattention mechanismeye aspect ratio
国家科技期刊平台
NSTL
万方数据
