Models & Optimisation and Mathematical Analysis Journal
Volume 1, Numéro 2, Pages 27-31
2012-12-17
Driver Drowsiness Detection System Based On Visual Information
Authors : Alshaqaqi Belal . Baquhaizel Abdullah Salem . Ouis Mohamed El Amine .
Abstract
Drowsiness and Fatigue of drivers are amongst the significant causes of road accidents. Every year, they increase the amounts of deaths and fatalities injuries globally. In this paper, a module for Advanced Driver Assistance System (ADAS) is presented to reduce the number of accidents due to drivers fatigue and hence increase the transportation safety; this system deals with automatic driver drowsiness detection based on visual information and Artificial Intelligence. We proposed an algorithm to locate, track, and analyze both the drivers face and eyes to measure PERCLOS, a scientifically supported measure of drowsiness associated with slow eye closure.
Keywords
Drowsiness detection, ADAS, Face Detection and Tracking, Eyes Detection and Tracking, Eye state, PERCLOS.
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