By applying YOLOv3 based deep learning object detection technology, the proposed visible-light pupil tracking method predicts the centers of pupils effectively.  For testing the pupil tracking performance with the inference model, the precision is up to 80,the recall is 83.  Besides, the average pupil tracking errors of the proposed deep-learning based design are only 4 pixels.

By using the YOLOv3 inference model to track the centers of pupils, the precision is up to 80,the recall is 83.  Besides, the average horizontalvertical pupil tracking errors of the proposed deep-learning based design are only 4 pixels, which are much less than the pupil tracking errors of the previous ellipse fitting design at visible-light conditions.

This developed technology can be applied to human-machine interactive interfaces, eye trackers, gaze tracking,driving safety assistance systems.