Driver drowsiness detection system

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

12-15 May 2013

Firstpage

151

Lastpage

155

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 propose 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; face recognition; road safety; ADAS; PERCLOS; advanced driver assistance system; artificial intelligence; automatic driver drowsiness detection; driver drowsiness detection system; drivers fatigue; face detection; fatalities; injuries; road accidents; transportation safety; visual information; Cameras; Conferences; Face; Face detection; Image edge detection; Real-time systems; Vehicles; ADAS; Drowsiness detection; Eye state; Eyes Detection and Tracking; Face Detection and Tracking; PERCLOS;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Signal Processing and their Applications (WoSSPA), 2013 8th International Workshop on

Conference_Location

Algiers

Type

conf

DOI

10.1109/WoSSPA.2013.6602353

Filename

6602353