Visible spectrum eye tracking for safety driving assistance

Abstract

Although many studies have proposed eye tracking methods to be used for driving assistance systems, these concepts have not been put into practical. The most considered issue to track drivers’ eyes is the effects of ambient infrared spectrum from the sunlight, making center of pupils and the corneal reflections from the tracker’s infrared light source undetectable. In this study, we propose a visible spectrum eye tracking to calculate the driver’s gaze points only if the gaze detection from the infrared spectrum eye tracking failed. The proposed eye tracking uses an automated facial landmark detection to calculate the head pose which enabling head movement compensation, and a learning-based calibration model to eliminate the calibration processes.