  This paper introduces and evaluates a hybrid technique that fuses efficiently
the eye-tracking principles of photosensor oculography (PSOG) and video
oculography (VOG). The main concept of this novel approach is to use a few fast
and power-economic photosensors as the core mechanism for performing high speed
eye-tracking, whereas in parallel, use a video sensor operating at low
sampling-rate (snapshot mode) to perform dead-reckoning error correction when
sensor movements occur. In order to evaluate the proposed method, we simulate
the functional components of the technique and present our results in
experimental scenarios involving various combinations of horizontal and
vertical eye and sensor movements. Our evaluation shows that the developed
technique can be used to provide robustness to sensor shifts that otherwise
could induce error larger than 5 deg. Our analysis suggests that the technique
can potentially enable high speed eye-tracking at low power profiles, making it
suitable to be used in emerging head-mounted devices, e.g. AR/VR headsets.
