Blink Detection


Blinks are an indicator for fatigue or drowsiness and can assist in the diagnose of mental disorders, such as schizophrenia. Additionally, a blink that obstructs the pupil impairs the performance of other eye-tracking algorithms, such as pupil detection, and often results in noise to the gaze estimation. The algorithm presented here, is tailored towards head-mounted eye trackers and is robust to calibration-based variations like translation or rotation of the eye. The proposed approach reached 96,35% accuracy for a realistic and challenging data set and in real-time even on low-end devices, rendering the proposed method suited for pervasive eye tracking.

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Citation:
Tobias Appel, Thiago Santini, and Enkelejda Kasneci. 2016. Brightness- and motion-based blink detection for head-mounted eye trackers. In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct (UbiComp '16). ACM, New York, NY, USA, 1726-1735. DOI: http://dx.doi.org/10.1145/2968219.2968341