Comparitive study on photometric normalization algorithms for an innovative, robust and real-time eye gaze tracker

Eye gaze trackers (EGTs) are generally developed for scientific exploration in controlled environments or laboratories and data have been used in ophthalmology, neurology, psychology, and related areas to study oculomotor characteristics and abnormalities, and their relation to cognition and mental states. The illumination is one of the most restrictive limitation of the EGTs, due to a problem of pupil center estimation during illumination changes. Most of the current systems, indeed, work under controlled illumination conditions either in dark or indoor environments, e.g. using infrared sources or conforming the sources of light to fixed levels or pointing directions. This work is focused on exploring and comparing several photometric normalization techniques to improve EGT systems during light changes. In particular, a new wearable and wireless eye tracking system (HATCAM) is used for testing the different techniques in terms of real-time capability, eye tracking and pupil area detection. Embedding real-time image enhancement into the HATCAM can make it an innovative and robust system for eye tracking in different lighting conditions, i.e. darkness, sunlight, indoor and outdoor environments.