Gaze Estimation Interpolation Methods Based on Binocular Data

Video oculography (VOG) is one of the most commonly used techniques for gaze tracking because it enables non-intrusive eye detection and tracking. Improving the eye tracking's accuracy and tolerance to user head movements is a common task in the field of gaze tracking; thus, a thorough study of how binocular information can improve a gaze tracking system's accuracy and tolerance to user head movements has been carried out. The analysis is focused on interpolation-based methods and systems with one and two infrared lights. New mapping features are proposed based on the commonly used pupil-glint vector using different distances as the normalization factor. For this study, an experimental procedure with six users based on a real VOG gaze tracking system was performed, and the results were contrasted with an eye simulator. Important conclusions have been obtained in terms of configuration, equation, and mapping features, such as the out performance of the interglint distance as the normalization factor. Furthermore, the binocular gaze tracking system was found to have a similar or improved level of accuracy compared to that of the monocular gaze tracking system.