Developments in wearable eye tracking devices make them an attractive solution for studies of eye movements during naturalistic head/body motion. However, before these systems’ potential can be fully realized, a thorough assessment of potential sources of error is needed. In this study, we examine three possible sources for the Pupil Core eye tracking goggles: camera motion during head/body motion, choice of calibration marker configuration, and eye movement estimation. In our data, we find that up to 36% of reported eye motion may be attributable to camera movement; choice of appropriate calibration routine is essential for minimizing error; and the use of a secondary calibration for eye position remapping can improve eye position errors estimated from the eye tracker.
Publication Type: Conference Paper
Authors: Anca Velisar; Natela Shanidze
Publication: ACM Symposium on Eye Tracking Research and Applications, Association for Computing Machinery, Number 20, New York, NY, USA, p.1-3 (2021)
Project URL: https://dl.acm.org/doi/10.1145/3450341.3458495
Keywords: calibration, eye tracking, homography