Using Deep Learning to Increase Eye-Tracking Robustness, Accuracy, and Precision in Virtual Reality

arXiv:2403.19768v1 Announce Type: new
Abstract: Algorithms for the estimation of gaze direction from mobile and video-based eye trackers typically involve tracking a feature of the eye that moves through the eye camera image in a way that covaries with the shifting gaze direction, such as the center or boundaries of the pupil. Tracking these features using traditional computer vision techniques can be difficult due to partial occlusion and environmental reflections. Although recent efforts to use machine learning (ML) for pupil …

abstract accuracy algorithms arxiv center cs.cv deep learning feature image mobile precision reality robustness through tracking type video virtual virtual reality