Driver drowsiness warning system using visual information for both diurnal and nocturnal illumination conditions

Authors:
Marco Javier Flores;José María Armingol;Arturo de la Escalera
Affiliations:
University Carlos III of Madrid, Leganés, Madrid, Spain;University Carlos III of Madrid, Leganés, Madrid, Spain;University Carlos III of Madrid, Leganés, Madrid, Spain
Venue:
EURASIP Journal on Advances in Signal Processing - Special title on vehicular ad hoc networks
Year:
2010

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Abstract

Every year, traffic accidents due to human errors cause increasing amounts of deaths and injuries globally. To help reduce the amount of fatalities, in the paper presented here, a new module for Advanced Driver Assistance System (ADAS) which deals with automatic driver drowsiness detection based on visual information and Artificial Intelligence is presented. The aim of this system is to locate, track, and analyze both the drivers face and eyes to compute a drowsiness index, where this real-time system works under varying light conditions (diurnal and nocturnal driving). Examples of different images of drivers taken in a real vehicle are shown to validate the algorithms used.