The Influence that the Complexity of the Three-Dimensional Eye Model Used to Generate Simulated Eye-tracking Data Has on the Gaze Estimation Errors Achieved Using the Data

Abstract

Simulated eye-tracking data are an integral tool in the development of eye-tracking methods. Most of the simulated data used in eye-tracking-related research has been generated using low-complexity eye models that include a single spherical corneal surface. This study investigated the influence of eye model complexity on the ability of simulated eye-tracking data to predict real-world outcomes. The experimental procedures of two pertinent comparative eye-tracking studies were replicated in a simulated environment using various eye model complexities. The simulated outcomes were then evaluated against the findings of the comparative studies that were derived from real-world outcomes. The simulated outcomes of both comparative studies were significantly influenced by the eye model complexity. Eye models that included an aspheric corneal surface best replicated experimental eye-tracking outcomes, while including a posterior corneal surface did not improve the ability of simulated data to replicate real-world outcomes. Using a wide-angle eye model that accurately replicates the peripheral optics of the eye did not improve simulated outcomes relative to a paraxial eye model.