Hybrid computer vision system for drivers' eye recognition and fatigue monitoring

This paper presents a hybrid visual system for monitoring driver's states of fatigue, sleepiness and inattention based on driver's eye recognition. Safe operation in car conditions and processing in daily and night conditions are obtained thanks to the custom setup of two cameras operating in the visible and near infra-red spectra, respectively. In each of these spectra image processing is performed by a cascade of two classifiers. The first classifier in a cascade is responsible for detection of eye regions based on the proposed eye models specific to each spectrum. The second classifier in each cascade is responsible for eye verification. It is based on the higher order singular value decomposition of the tensors of geometrically deformed versions of real eye prototypes, specific to the visible and NIR spectra. Experiments were performed in real car conditions in which four volunteer drivers participated. The obtained results show high recognition accuracy and real-time processing in software implementation. Thanks to these the system can become a part of the advanced driver’s assisting system.