Cross spread pupil tracking technique

Abstract

We present a fast and minimum delay algorithm for detecting the pupil center, called the “cross spread” tracking technique. This algorithm is meant for video eye trackers that estimate gaze direction from the position of the pupil center in the captured images. Contrary to other solutions, we do not try to make this technique robust to distractors such as reflections, distortions caused by glasses, or eyelids covering the pupil, but rather we assume eye tracking in stable light conditions. We argue that this approach is useful in many eye tracking applications, such as gaze tracking during psychophysical experiments in stable laboratory conditions, and that this approach can significantly reduce the eye tracker’s complexity while maintaining its accuracy and performance. The proposed cross spread technique estimates pupil by tracing rays in horizontal and vertical directions in the image, starting from a point in the pupil region and continuing to the pupil boundary. The found boundary points determine the next starting point and the procedure is iteratively repeated. Parallel processing can be efficiently used enabling accurate pupil center detection in <2 ms on typical laptops. We compare the proposed algorithm to other pupil detection algorithms.