Suitability of calibration polynomials for eye-tracking data with simulated fixation inaccuracies

Current video-based eye trackers are not suited for calibration of patients who cannot produce stable and accurate fixations. Reliable calibration is crucial in order to make repeatable recordings, which in turn are important to accurately measure the effects of a medical intervention. To test the suitability of different calibration polynomials for such patients, inaccurate calibration data were simulated using a geometric model of the EyeLink 1000 Plus desktop mode setup. This model is used to map eye position features to screen coordinates, creating screen data with known eye tracker data. This allows for objective evaluation of gaze estimation performance over the entire computer screen. Results show that the choice of calibration polynomial is crucial in order to ensure a high repeatability across measurements from patients who are hard to calibrate. Higher order calibration polynomials resulted in poor gaze estimation even for small simulated fixation inaccuracies.