Enhancing Road Safety: A Driver Fatigue Detection and Behaviour Monitoring System using Advanced Computer Vision Techniques - Chadha, Ramneet Singh; Jugesh; Singh, Jasmehar (Journal of Ubiquitous Computing and Communication Technologies, 2024)
Driver drowsiness is a major hazard to road safety, necessitating the development of reliable detection technologies. This study describes a revolutionary driver fatigue detection system that uses cutting-edge computer vision technologies. This system uses the MediaPipe framework for accurate face and hand detection and the Eye Aspect Ratio (EAR) for drowsiness detection. Furthermore, it uses the OpenCV solvePnP function for estimating rotation vector, and converting it to a rotation angle of the head, to check driver attention. By continuously monitoring these indicators, when the system successfully detects any instances of driver tiredness or inattention, it records his or her behavior and delivers notifications to help prevent accidents. This study helps to improve road safety by utilizing cutting-edge computer vision techniques to prevent driver fatigue and boost attentive driving practices.
Keywords: Fatigue detection; Eye aspect ratio; Drowsiness detection; Head pose estimation; Hand detection; Mediapipe