The analysis of eye blinking pattern using high-frame-rate camera

The purpose of this study is to analyze eye blinking patterns using high-speed camera without additional instructions and illuminations. The experimental video clips are taken at 240 frames per second, which is twice the flickering rate of room light. The eye blinking sequences are segmented from the whole video clip after reducing noise and baseline wander. The shapes and positions of the upper eyelid in blinking sequences are evaluated by a polynomial curve fitting algorithm and visualized to the eyelid position graph. The graph made it easy to recognize the eye blinking patterns. In order to analyze patterns, eye blinking parameters are calculated, and an eye blinking cycle is divided into three phases as ‘Closing phase’, ‘Closed phase’, and ‘Opening phase’. In the experiments with forty volunteers, proposed method can analyze eye blinking patterns qualitatively.

[1]  Kongqiao Wang,et al.  Eye blink detection based on eye contour extraction , 2009, Electronic Imaging.

[2]  D. Schroeder,et al.  Blink Rate: A Possible Measure of Fatigue , 1994, Human factors.

[3]  Lihong V. Wang,et al.  Label-free photoacoustic ophthalmic angiography. , 2010, Optics letters.

[4]  Kang Ryoung Park,et al.  Blink detection robust to various facial poses , 2010, Journal of Neuroscience Methods.

[5]  Mati Joshua,et al.  A noninvasive, fast and inexpensive tool for the detection of eye open/closed state in primates , 2009, Journal of Neuroscience Methods.

[6]  David Mas,et al.  Noninvasive measurement of eye retraction during blinking. , 2010, Optics letters.

[7]  Antoine Picot,et al.  Comparison between EOG and high frame rate camera for drowsiness detection , 2009, 2009 Workshop on Applications of Computer Vision (WACV).

[8]  Heiko Pult,et al.  A new perspective on spontaneous blinks. , 2013, Ophthalmology.