Citation

Javier Flores M, Armingol JM, de la Escalera A. EURASIP J. Adv. Signal Process. 2010; 2010(online): ID 438205.

Copyright

(Copyright © 2010, The author(s), Publisher Holtzbrinck Springer Nature Publishing Group)

DOI

10.1155/2010/438205

PMID

unavailable

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.