Citation

Flores MJ, Armingol JM, Escalera A. J. Intell. Robotic Syst. 2010; 59(2): 103-125.

Copyright

(Copyright © 2010, Holtzbrinck Springer Nature Publishing Group)

DOI

10.1007/s10846-009-9391-1

PMID

unavailable

Abstract

Traffic accidents due to human errors cause many deaths and injuries around the world. To help in reducing this fatality, in this research, a new module for Advanced Driver Assistance System (ADAS) for automatic driver drowsiness detection based on visual information and Artificial Intelligence is presented. The aim of this system is to locate, to track and to analyze the face and the eyes to compute a drowsiness index, working under varying light conditions and in real time. Examples of different images of drivers taken in a real vehicle are shown to validate the algorithm.