Photosensor Oculography: Survey and Parametric Analysis of Designs Using Model-Based Simulation

This paper presents a renewed overview of photosensor oculography (PSOG), an eye-tracking technique based on the use of simple photosensors (usually infrared) to measure the overall amount of reflected light while the eye rotates. PSOG can provide high spatial and temporal resolution, low tracking latency, and reduced power consumption. The deeper examination of this technique is particularly important, given the current needs for efficient eye-tracking mechanisms by the emerging interaction devices, e.g., augmented and virtual reality headsets. In our investigation, we employ an adjustable simulation framework to examine the eye-tracking performance when changing the parameters of different PSOG designs. We focus our examination on eye-tracking accuracy and crosstalk, two crucial characteristics for the seamless interaction via eye-tracking. Our experiments demonstrate the parameter values (or ranges) that lead to different levels of performance for accuracy and crosstalk. We also show that the optimization of accuracy and crosstalk is often driven by competing conditions, and thus, we perform a multi-objective optimization procedure and estimate the respective trade-off parameters. Finally, we present the effects from sensor shifts and evaluate the resulting increase in accuracy error. Our results and analysis can be used to facilitate the selection of parameters in future PSOG systems.