Real-Time Driver-Drowsiness Detection System Using Facial Features

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Aim:

This paper aim to detect Real time driver’s fatigue state using Convolutional Neural Network (CNN)

Existing System:

The driver facial features is identified by various Algorithms. But it is not accuracy and some major problems are occurred. Facial landmarks on the detected face are pointed and subsequently the eye aspect ratio and mouth opening ratio are not properly. So we will move to the proposed system

Proposed System:

In the proposed system, a webcam records the video and driver’s face is detected in each frame employing image processing techniques. A novel system for evaluating the driver’s level of fatigue based on face tracking and facial key point detection. In order to track the driver’s face using CNN (Convolution Neural Network) and then the facial regions of detection based on facial key points. Then the eyes and mouth will be detected if the eye is closed the alert system will be displayed.