  This paper presents a renewed overview of photosensor oculography (PSOG), an
eye-tracking technique based on the principle of using simple photosensors to
measure the amount of reflected (usually infrared) light when the eye rotates.
Photosensor oculography can provide measurements with high precision, low
latency and reduced power consumption, and thus it appears as an attractive
option for performing eye-tracking in the emerging head-mounted interaction
devices, e.g. augmented and virtual reality (AR/VR) headsets. In our current
work we employ an adjustable simulation framework as a common basis for
performing an exploratory study of the eye-tracking behavior of different
photosensor oculography designs. With the performed experiments we explore the
effects from the variation of some basic parameters of the designs on the
resulting accuracy and cross-talk, which are crucial characteristics for the
seamless operation of human-computer interaction applications based on
eye-tracking. Our experimental results reveal the design trade-offs that need
to be adopted to tackle the competing conditions that lead to optimum
performance of different eye-tracking characteristics. We also present the
transformations that arise in the eye-tracking output when sensor shifts occur,
and assess the resulting degradation in accuracy for different combinations of
eye movements and sensor shifts.
