Survey of Eye Blink Detection Techniques

Volume: 4    Issue: 2

Year of Publication: 2017

Pages: (1-4)

Authors: Prathamesh Govardhane, Prof. M.V. Wyawahare

Download Full Text (PDF)

Abstract

Blinking is a phenomenon that maintains eye moisture and prevents it from drying out. If blinking is not at its normal rate it results in an eye disease namely dry eye syndrome, which causes redness and irritation in eyes. People especially in IT sector are more prone to this disease since they spend most of the time looking at the monitors which reduces the blink rate. Hence this disorder is also called as computer vision syndrome. Eye blink detection can help in preventing this disorder. The paper aims at presenting the overview of various eye blink detection techniques.

References

1. Yan, Z., Hu, L., Chen, H., and Lu, F. Computer Vision Syndrome: A widely spreading but largely unknown epidemic among computer users. Computers in Human Behavior 24, 5 (Sept. 2008), 2026âAS2042¸.

2. Hari Singh, Dr. Jaswinder Singh. Human Eye Tracking and Related Issues: A Review. International Journal of Scientific and Research Publications, Volume 2, Issue 9, September 2012 ISSN 2250-3153.

3. Zeynep Orman1, Abdulkadir Battal2 and Erdem Ke-mer3. A STUDY ON FACE, EYE DETECTION AND GAZE ESTIMATION. International Journal of Com-puter Science and Engineering Survey (IJCSES) Vol.2, No.3, August 2011.

4. S. Sirohey, A. Rosenfeld and Z. Duric. A method of de-tecting and tracking irises and eyelids in video. Pattern Recognition, vol. 35, num. 6, pp. 1389-1401, 2002.

5. Matjaz Divjak, Horst Bischof. Real-time video-based eye blink analysis for detection of low blink-rate dur-ing computer use. Institute for Computer Graphics and Vision Graz University of Technology, Austria divjak,bischof@icg.tu-graz.ac.at

6. T. Morris, P. Blenkhorn and F. Zaidi. Blink detection for real-time eye tracking. Journal of Network and Computer Applications, vol. 25, num. 2, pp. 129-143, April 2002.

7. Michael Chau and Margrit Betke. Real Time Eye Tracking and Blink Detection with USB Cameras. Boston University Computer Science Technical Report No. 2005-12, May 2005.

8. K Aai, and R Mardiyanto, âAIJComparative Study on Blink Detection and Gaze Estimation Methods for HCI, in Particular, Gabor Filter Utilized Blink Detection MethodâAI, 2011 8th International Conference on In-formation Technology: New generation, 2011, pp 441-446.

9. Rajpathaka. T, Kumarb, R, Schwartzb. E.: Eye Detec-tion Using Morphological and Color Image Processing, Proceeding of Florida Conference on Recent Advances in Robotics, (2009).

10. Lei Yunqi, Yuan Meiling, Song Xiaobing, Liu Xiuxia, Ouyang Jiangfan.: Recognition of Eye States in Real Time Video, Proceeding of IEEE International Conference on Computer Engineering and Technology, 554 âAS¸ 559, (2009)

11. Shafi. M, Chung. P. W. H.: A Hybrid Method for Eyes Detection in Facial Images, International Journal of Electrical, Computer, and Systems Engineering, pp 231236, (2009)

12. R.Brunelli, T.Poggio, Face Recognition.: Features ver-sus templates, IEEE Trans. Patt. Anal. Mach. Intell. 15(10), 1042-1052, (1993)

13. Lei Yunqi, Yuan Meiling, Song Xiaobing, Liu Xiuxia, Ouyang Jiangfan.: Recognition of Eye States in Real Time Video, Proceeding of IEEE International Conference on Computer Engineering and Technology, 554âAS¸ 559, (2009).

Keywords

blink detection, eye anatomy, electrooculography, Gabor filter.