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Computer Input with Human Eyes-Only Using Two Purkinje Images Which Works in a Real-Time Basis without Calibration
Kohei Arai, Makoto Yamaura
Pages - 71 - 82     |    Revised - 30-11-2010     |    Published - 20-12-2010
Volume - 1   Issue - 3    |    Publication Date - December 2010  Table of Contents
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KEYWORDS
gaze estimation, cornea curvature, eyeball rotation, Purkinje image, computer input with human eyes only
ABSTRACT
A method for computer input with human eyes-only using two Purkinje images which works in a real time basis without calibration is proposed. Experimental results shows that cornea curvature can be estimated by using two light sources derived Purkinje images so that no calibration for reducing person-to-person difference of cornea curvature. It is found that the proposed system allows usersf movements of 30 degrees in roll direction and 15 degrees in pitch direction utilizing detected face attitude which is derived from the face plane consisting three feature points on the face, two eyes and nose or mouth. Also it is found that the proposed system does work in a real time basis.
CITED BY (18)  
1 Arai, K. (2016). Computer Input Just by Sight and Its Applications in Particular for Disable Persons. In Information Technology: New Generations (pp. 995-1007). Springer International Publishing.
2 張超. (2016). Study on Environmental Control System for People with Serious Disabilities.
3 Zhang, C., Ishimatsu, T., Yu, J., Murray, L., & Shi, L. (2015, August). Vision-based displacement sensor for people with serious spinal cord injury. In Mechatronics and Automation (ICMA), 2015 IEEE International Conference on (pp. 772-777). IEEE.
4 Zhang, C., Shibata, M., Takashima, K., Yu, J., Ishimatsu, T., & Palomino, J. (2015). An Environmental Control System for ALS Patient Using Finger Movement. Modern Mechanical Engineering, 5(04), 122.
5 Arai, K. (2015). Psychological Status Monitoring with Cerebral Blood Flow, Electroencephalogram and Electro-oculogram Measurements.
6 Arai, K. (2015). Computer Input by Human Eyes Only and It’s Applications. In Intelligent Systems in Science and Information 2014 (pp. 1-22). Springer International Publishing.
7 Arai, K. Psychological Status Monitoring with Cerebral Blood Flow: CBF, Electroencephalogram: EEG and Electro-Oculogram: EOG Measurements.
8 Arai, K., & Mardiyanto, R. (2013). Method for psychological status estimation by gaze location monitoring using eye-based human-computer interaction. Editorial Preface, 4(3).
9 Ghani, M. U., Chaudhry, S., Sohail, M., & Geelani, M. N. (2013, December). GazePointer: A real time mouse pointer control implementation based on eye gaze tracking. In Multi Topic Conference (INMIC), 2013 16th International (pp. 154-159). IEEE.
10 Arai, K. (2013). Method for 3D Rendering Based on Intersection Image Display Which Allows Representation of Internal Structure of 3D objects. INTERNATIONAL JOURNAL OF ADVANCED RESEARCH IN ARTIFICIAL INTELLIGENCE, 2(6).
11 Kulkarni, S., & Gala, S. (2013). A Simple Algorithm for Eye Detection and Cursor Control. International Journal of Computer Technology and Applications, 4(6), 880.
12 Arai, K. (2013). Lecturer’s e-Table (Server Terminal) Which Allows Monitoring the Location at Where Each Student is Looking During Lessons with e-Learning Contents Through Client Terminals. INTERNATIONAL JOURNAL OF ADVANCED RESEARCH IN ARTIFICIAL INTELLIGENCE, 2(6).
13 Kohei Arai. (2012). Human-computer interaction and its application system based on the line-of-sight. Image e-Journal, 41 (3), 296-301.
14 Kohei Arai, & Mardiyanto, R. (2012). Helper robot. Image e-Journal with the voice communication capabilities and line-of-sight cruise control function, 41 (5), 535-542.
15 Kohei Arai, & Mardiyanto, R. (2012). Robot arm control and feeding support system based on the line-of-sight input. The Institute of Electrical Engineers Journal C (Electronics and Information Systems Division magazine), 132 (3), 416-423.
16 Arai, K., & XiaoYu, G. (2012). Method for 3D Object of Content Representation and Manipulation on 2D Display Using Human Eyes Only. 한국콘텐츠학회 2012 추계종합학술대회, 49-50.
17 Arai, K. (2012). Method for leaning efficiency improvements based on gaze location notifications on e-learning content screen display. International Journal of Advanced Research in Artificial Intelligence, 1(3), 1-6.
18 Arai, K., & Mardiyanto, R. (2011). Autonomous control of eye based electric wheel chair with obstacle avoidance and shortest path finding based on Dijkstra algorithm. International Journal of Advanced Computer Science and Applications, 2(12), 19-25.
1 Google Scholar 
2 CiteSeerX 
3 refSeek 
4 Scribd 
5 SlideShare 
6 PDFCAST 
7 PdfSR 
1 Carpenter, R. H. S. (1988). Movements of the eyes. London: Pion.
2 Collewijn, H. (1999). Eye movement recording. In R. H. S. Carpenter & J. G. Robson (Eds.), Vision research: A practical guide to laboratory methods (pp. 245-285). Oxford: Oxford University Press.
3 Crane, H. D., & Steele, C. M. (1985). Generation-V dual-Purkinje-image eyetracker. Applied Optics, 24, 527-537.
4 Deubel, H., & Bridgeman, B. (1995a). Fourth Purkinje image signals reveal eye-lens deviations and retinal image distortions during saccades. Vision Research, 35, 529-538.
5 Deubel, H., & Bridgeman, B. (1995b). Perceptual consequences of ocular lens overshoot during saccadic eye movements. Vision Research, 35, 2897-2902.
6 Van Rensbergen, J., De Troy, A., Cavegn, D., De Graef, P., van Diepen, P. M. J., & Fias, W. (1993). The consequences of eye-lens movement during saccades for a stable retinal image. Poster presented at the Seventh European Conference on Eye Movements. Durham, UK.
7 K. Matsuda, T. Nagami and S. Yamane, Development of gaze measurement system, Technical Report of the Institute of Electronics, Information and Communication Engineers, TL2002-2, 2000.
8 T. Ohno, N. Takegawa, and A. Yoshikawa, Gaze estimation method based on eyeball shape model, Proc. of the 8 th Image Sensing Symposium, pp.307-312, 2002.
9 Y. Ebisawa, 3D gaze measurement equipment, Japanese Patent No.2005-198743, 2005.
10 . H. Tanaka, S. Hikita, K. Kasai, and A. Takeda, Gaze estimation method based on cornea curvature center estimation with two light sources, Journal of the Institute of Electronics, Information and Communication Engineers, 108, 479, MBE2008-128, 117-180, 2009.
11 J. Canny: A Computational Approach to Edge Detection, IEEE Trans. Pattern Analysis and Machine Intelligence, .8, 6, .679-698, 1986.
12 Intel Crop.: OpenCV (Inte Open Computer Vision Library), http://www.intel.com/technology/computing/opencv/
Professor Kohei Arai
Saga University - Japan
arai@is.saga-u.ac.jp
Mr. Makoto Yamaura
- Japan