BORE: boosted-oriented edge optimization for robust, real time remote pupil center detection

Undoubtedly, eye movements contain an immense amount of information, especially when looking to fast eye movements, namely time to the fixation, saccade, and micro-saccade events. While, modern cameras support recording of few thousand frames per second, to date, the majority of studies use eye trackers with the frame rates of about 120 Hz for head-mounted and 250 Hz for remote-based trackers. In this study, we aim to overcome the challenge of the pupil tracking algorithms to perform real time with high speed cameras for remote eye tracking applications. We propose an iterative pupil center detection algorithm formulated as an optimization problem. We evaluated our algorithm on more than 13,000 eye images, in which it outperforms earlier solutions both with regard to runtime and detection accuracy. Moreover, our system is capable of boosting its runtime in an unsupervised manner, thus we remove the need for manual annotation of pupil images.