Binocular eye tracking calibration during a virtual ball catching task using head mounted display

Abstract

When tracking the eye movements of an active observer, the quality of the tracking data is continuously affected by physical shifts of the eye-tracker on an observers head. This is especially true for eye-trackers integrated within virtual-reality (VR) helmets. These configurations modify the weight and inertia distribution well beyond that of the eye-tracker alone. Despite the continuous nature of this degradation, it is common practice for calibration procedures to establish eye-to-screen mappings, fixed over the time-course of an experiment. Even with periodic recalibration, data quality can quickly suffer due to head motion. Here, we present a novel post-hoc calibration method that allows for continuous temporal interpolation between discrete calibration events. Analysis focuses on the comparison of fixed vs. continuous calibration schemes and their effects upon the quality of a binocular gaze data to virtual targets, especially with respect to depth. Calibration results were applied to binocular eye tracking data from a VR ball catching task and improved the tracking accuracy especially in the dynamic case.