Development of Low-Cost Real-Time Driver Drowsiness Detection System Using Eye Centre Tracking and Dynamic Thresholding

Author(s):  
Fuzail Khan ◽  
Sandeep Sharma
Author(s):  
Charan M

We propose a Driver drowsiness detection system, the purposes of which are to prevent from dangerous cause and to avoid accidents. Since all the processes on image recognition performed on a smart phone, the system does not need to send images to a server and runs on an android smart phone in a real-time way. Automatic image-based recognition is a particularly challenging task. Traditional image analysis approaches have achieved low classification accuracy in the past, whereas deep learning approaches without human supervision real-time drowsiness detection. This model classifies whether the person’s eyes are opened or closed. To recognize the face, a user should have to adjust camera such a way that it covers his face first, and then the system starts recognition within the indicated bounding boxes. In addition, the system estimates the actions of the person. This recognition process is performed repeatedly about every second. We will implement this system as Web application effectively for real-time recognition.


2021 ◽  
Author(s):  
Jonathan Flores-Monroy ◽  
Mariko Nakano-Miyatake ◽  
Gabriel Sanchez-Perez ◽  
Hector Perez-Meana

Sign in / Sign up

Export Citation Format

Share Document