Distracted Driver Monitoring with Computer Vision(Dlib,EAR,MAR)
Keywords:
Driver Drowsiness Detection, Driver Fatigue Monitoring, Computer Vision, Visual Behavior Analysis, Eye Aspect Ratio (EAR), Yawning Detection, Machine Learning, Real-Time Monitoring, Webcam Based Detection, Adaptive Thresholding, Facial Landmark Detection, Non-Invasive System, Road Safety, Driver Distraction, Python Implementation, Support Vector Machine (SVM), Blink Rate Monitoring, Head Pose Estimation, Intelligent Transportation Systems, Accident Prevention).Abstract
Driver Drowsiness and Distraction Detection System Using Computer Vision and Machine Learning. Road safety is a
major concern worldwide, and many accidents happen becausedrivers feel sleepy or get distracted while driving. This is especially dangerous for people who drive long distances
References
[[1] T. Soukupová and J. Čech, Real-Time Eye Blink Detection Using Facial Landmarks, Technical Report, Center for Machine Perception, Czech Technical University, Prague, 2016
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Published
2024-11-20
How to Cite
Dr.Vadali Srinivas,T. Sai Lalith Prasad ,M.Ashok Reddy ,M.Varshitha,K.Saiprakash,Dr. O. Shravani. (2024). Distracted Driver Monitoring with Computer Vision(Dlib,EAR,MAR) . Journal of Computational Analysis and Applications (JoCAAA), 33(08), 2459–2464. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/4360
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