Vision based system for driver drowsiness detection

Author

Alshaqaqi, Belal ; Baquhaizel, Abdullah Salem ; El Amine Ouis, Mohamed ; Boumehed, Meriem ; Ouamri, Abdelaziz ; Keche, Mokhtar

Author_Institution

Lab. signals & images (LSI), Univ. of Sci. & Technol. of Oran Mohamed Boudiaf (USTO-MB), Oran, Algeria

fYear

2013

fDate

22-24 April 2013

Firstpage

103

Lastpage

108

Abstract

Drowsiness of drivers is amongst the significant causes of road accidents. Every year, it increases 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

artificial intelligence; computer vision; driver information systems; face recognition; human factors; object tracking; road accidents; road safety; ADAS; PERCLOS; advanced driver assistance system; artificial intelligence; automatic driver drowsiness detection; deaths; driver eye localisation; driver eye tracking; driver face localisation; driver face tracking; driver fatigue; fatal injuries; road accidents; slow eye closure; transportation safety; vision-based system; visual information; Accidents; Face; Face detection; Image color analysis; Labeling; Skin; Vehicles; ADAS; Drowsiness detection; Eye state; Eyes Detection and Tracking; Face Detection and Tracking; PERCLOS;

fLanguage

English

Publisher

ieee

Conference_Titel

Programming and Systems (ISPS), 2013 11th International Symposium on

Conference_Location

Algiers

Print_ISBN

978-1-4799-1152-3

Type

conf

DOI

10.1109/ISPS.2013.6581501

Filename

6581501