Driver drowsiness detection using ANN image processing

CAR2017 International Congress of Automotive and Transport Engineering - Mobility Engineering and Environment

工业技术;运输工程

Vesselenyi, T.^1 ; Moca, S.^1 ; Rus, A.^1 ; Mitran, T.^1 ; Ttaru, B.^1

University of Oradea, Romania^1

关键词: Auto encoders;    Car driver;    Driver drowsiness;    Drowsiness detection;    EOG signal;    Hidden layer networks;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/252/1/012097/pdf
DOI  :  10.1088/1757-899X/252/1/012097

学科分类：工业工程学

来源: IOP

【 摘 要 】

The paper presents a study regarding the possibility to develop a drowsiness detection system for car drivers based on three types of methods: EEG and EOG signal processing and driver image analysis. In previous works the authors have described the researches on the first two methods. In this paper the authors have studied the possibility to detect the drowsy or alert state of the driver based on the images taken during driving and by analyzing the state of the driver's eyes: opened, half-opened and closed. For this purpose two kinds of artificial neural networks were employed: a 1 hidden layer network and an autoencoder network.