Abstract
In this paper, a deep-learning based pupil tracking technique is developed for the application of visible-light wearable eye trackers. By applying You only look once (YOLO) based deep learning object detection technology, the proposed pupil tracking method estimates and predicts the centers of pupils effectively in the visible-light mode. By testing the pupil tracking performance with the developed inference model, the precision is up to 80%, and the recall is close to 83%. Besides, the average horizontal and vertical pupil tracking errors of the deep-learning based design are only 4 pixels, which are much less than those of the previous ellipse fitting based design at the same visible-light conditions.
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