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

2019 ◽  
pp. 262-271
Author(s):  
Fuzail Khan ◽  
Sandeep Sharma
Keyword(s):  
Real Time ◽  
Detection System ◽  
Low Cost ◽  
Drowsiness Detection ◽  
Driver Drowsiness

scholarly journals Driver Drowsiness Detection System using Machine Learning

2021 ◽  
Vol 9 (VI) ◽  
pp. 2270-2272
Author(s):  
Charan M
Keyword(s):  
Real Time ◽  
Web Application ◽  
Detection System ◽  
Smart Phone ◽  
Learning Approaches ◽  
Drowsiness Detection ◽  
Driver Drowsiness ◽  
The Face ◽  
Bounding Boxes ◽  
Traditional Image

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.

Visual-based Real Time Driver Drowsiness Detection System Using CNN

2021 ◽  
Author(s):  
Jonathan Flores-Monroy ◽  
Mariko Nakano-Miyatake ◽  
Gabriel Sanchez-Perez ◽  
Hector Perez-Meana
Keyword(s):  
Real Time ◽  
Detection System ◽  
Drowsiness Detection ◽  
Driver Drowsiness

scholarly journals Real-Time Driver-Drowsiness Detection System Using Facial Features

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 118727-118738 ◽  
Author(s):  
Wanghua Deng ◽  
Ruoxue Wu
Keyword(s):  
Real Time ◽  
Detection System ◽  
Facial Features ◽  
Drowsiness Detection ◽  
Driver Drowsiness

Real-Time Driver Drowsiness Detection System Using Eye Aspect Ratio and Eye Closure Ratio

2019 ◽  
Author(s):  
Sukrit Mehta ◽  
Sharad Dadhich ◽  
Sahil Gumber ◽  
Arpita Jadhav Bhatt
Keyword(s):  
Aspect Ratio ◽  
Real Time ◽  
Detection System ◽  
Drowsiness Detection ◽  
Driver Drowsiness ◽  
Eye Closure
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