Noise in the Machine: Sources of Physical and Computation Error in Eye Tracking with Pupil Core Wearable Eye Tracker

Publication Type: Conference Paper
Publication: ACM Symposium on Eye Tracking Research and Applications, Association for Computing Machinery, Number 20, New York, NY, USA, p.1-3 (2021)

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.

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