Real-time Driver Drowsiness Detection based on Eye Movement and Yawning using Facial Landmark

• Published in: 2021 International Conference on Computer Communication and Informatics (ICCCI) pp. 1 - 4
• Main Authors: Al-madani, Ali Mansour, Gaikwad, Ashok T., Mahale, Vivek, Ahmed, Zeyad A.T., Shareef, Ahmed Abdullah A.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 27.01.2021
• Subjects: dlib; drowsiness detection; eye detection; face detection; facial landmark; Informatics; Mouth; Python; Real-time systems; Road accidents; Sensor systems; Sensors; Sleep; yawning
• DOI: 10.1109/ICCCI50826.2021.9457005

The drowsiness of the drivers might increase road accidents. Nowadays, computer vision and image processing technology can solve the problem and decrease the number of accidents by detecting the driver's drowsiness and gives an alert to beware of sleep that leads to an accident. This study has developed a real-time driver drowsiness detection based on eye movement and yawning using facial landmarks and dlib. This system helps to avoid accidents caused by drowsiness by detecting eye movements and yawning of the driver. The advantages of this system are low cost and minimized the requires the resource. The behavioral analysis method monitor results from the driver's facial landmark while driving without the need to place sensors in the driver's body.