Real-Time Warning System for Driver Drowsiness Detection Using Visual Information

被引:0
|
作者
Marco Javier Flores
José María Armingol
Arturo de la Escalera
机构
[1] Universidad Carlos III de Madrid,Intelligent Systems Laboratory
关键词
Driver’s drowsiness; Neural networks; Support vector machine; Gabor filter; Artificial intelligence; ADAS; Computer vision;
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中图分类号
学科分类号
摘要
Traffic accidents due to human errors cause many deaths and injuries around the world. To help in reducing this fatality, in this research, a new module for Advanced Driver Assistance System (ADAS) for automatic driver drowsiness detection based on visual information and Artificial Intelligence is presented. The aim of this system is to locate, to track and to analyze the face and the eyes to compute a drowsiness index, working under varying light conditions and in real time. Examples of different images of drivers taken in a real vehicle are shown to validate the algorithm.
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页码:103 / 125
页数:22
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