Title :
Real-time drowsiness detection system for an intelligent vehicle
Author :
Flores, Marco Javier ; Armingol, José María ; Escalera, A.
Author_Institution :
Dept. of Syst. Eng. & Autom., Univ. Carlos III de Madrid, Leganes
Abstract :
In the last years, the traffic accidents study is become important because they produce several died and hurt around the world. To help in reducing this fatality, in this paper, a new advanced driver assistance system (ADAS) for automatic driver´s drowsiness detection based on visual information and artificial intelligent is presented. This system works on several stages to be fully automatic. In addition, the aim of this algorithm is to locate and to track the face and the eyes to compute a drowsiness index. Examples of different driver´s images taken over real vehicle are shown to validate the algorithm that works in real time.
Keywords :
artificial intelligence; driver information systems; road safety; road traffic; advanced driver assistance system; artificial intelligent; intelligent vehicle; real-time drowsiness detection system; traffic accidents; visual information; Eyes; Face detection; Fatigue; Frequency; Infrared detectors; Intelligent vehicles; Lighting; Real time systems; Road accidents; Vehicle detection;
Conference_Titel :
Intelligent Vehicles Symposium, 2008 IEEE
Conference_Location :
Eindhoven
Print_ISBN :
978-1-4244-2568-6
Electronic_ISBN :
1931-0587
DOI :
10.1109/IVS.2008.4621125