A real-time driver visual attention monitoring system

Abstract

This paper describes a framework for analyzing video sequences of a driver and determining his level of attention. The proposed system deals with the computation of eyelid movement parameters and head (face) orientation estimation. The system relies on pupil detection to robustly track the driver's head pose and monitoring its level of fatigue. Visual information is acquired using a specially designed solution combining a CCD video camera with an NIR illumination system. The system is fully automatic and classifies rotation in all-view direction, detects eye blinking and eye closure and recovers the gaze of the eyes. Experimental results using real images demonstrates the accuracy and robustness of the proposed solution. © Springer-Verlag Berlin Heidelberg 2005.