A neural system for eye detection in a driver vigilance application

Abstract

The problem of eye detection for a driver vigilance system is very important in order to monitor driver fatigue, inattention, and lack of sleep. A neural classifier has been applied to recognize the eyes in the image, selecting the couple of regions candidate to contain the eyes by using iris geometrical information and symmetry. The novelty of this work is that the algorithm works on complex images without constraints on the background, skin color segmentation and so on. Different experiments have been carried out on images of subjects with different eyes colors, some of them wearing glasses. Tests showed robustness with respect to situations such as eyes partially occluded. In particular when applied to images where people have the eyes closed the proposed algorithm correctly reveals the absence of eyes. Eyes tracking in an image sequence is applied to detect eye closure that can be dangerous if persists for a long period.