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

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...

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Bibliographic Details
Published in2021 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
LanguageEnglish
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
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Summary: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.
DOI:10.1109/ICCCI50826.2021.9457005