Abstract
In the coming ubiquitous-computing society, an eyegaze interface will be one of the key technologies as an input device. Most of the conventional eyegaze tracking algorithms require specific light sources, equipments, devices, etc. In a previous work, the authors developed a simple eye-gaze detection system using a monocular video camera. This paper proposes a fast eye-gaze detection algorithm using the parametric template matching. In our algorithm, the iris extraction by the parametric template matching is applied to the eye-gaze detection based on physiological eyeball model. The parametric template matching can carry out an accurate sub-pixel matching by interpolating a few template images of a user’s eye captured in the calibration process for personal error. So, a fast calculation can be realized with keeping the detection accuracy. We construct an eye-gaze communication interface using the proposed algorithm, and verified the performance through key typing experiments using visual keyboard on display.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Gips, J., Olivieri, C.P., Tecce, J.J.: Direct control of the computer through electrodes placed around the eyes. In: Smith, M.J., Salvendy, G. (eds.) Proc. 5th Int. Conf. on Human Computer Interaction, Orlando, FL. Published in Human-Computer Interaction: Applications and Case Studies, pp. 630–635. Elsevier, Amsterdam (1993)
Talmi, K., Liu, J.: Eye and gaze tracking for visually controlled interactive stereoscopic displays. Signal Processing: Image Communication 14, 799–810 (1999)
Hutchinson, T.E., White, K.P., Martin, W.N., Reichert, K.C., Frey, L.A.: Human-computer interaction using eyegaze input. IEEE Trans. Systems, Man & Cybernetics 19(6), 1527–1534 (1989)
Ohno, T., Mukawa, N., Kawato, S.: Just Blink Your Eyes: A Head-Free Gaze Tracking System. In: Int. Conf. for Human-Computer Interaction, Florida, USA, pp. 950–951 (2003)
Cornsweet, T.N., Crane, H.D.: Accurate two-dimensional eye tracker using first and forth Purkinje images. J. Opt. Soc. Am. 63(8), 921–928 (1973)
Kawato, S., Tetsutani, N.: Gaze Direction Estimation with a Single Camera Based on Four Reference Points and Three Calibration Images. In: Narayanan, P.J., Nayar, S.K., Shum, H-Y. (eds.) ACCV 2006. LNCS, vol. 3852, pp. 419–428. Springer, Heidelberg (2006)
Matsumoto, Y., Zelinsky, A.: An algorithm for real-time stereo vision implementation of head pose and gaze direction measurement. In: Proceedings of IEEE fourth Int. Conf. on Faze and Gesture Recognition, pp. 499–505 (2000)
Wang, J., Sung, E.: Gaze determination via images of irises. Image and Vision Computing 19(12), 891–911 (2001)
Kim, K.-N., Ramakrishna, R.S.: Vision-based Eyegaze Tracking for Human Computer Interface. In: IEEE Int. Conf. On Systems, Man, and Cybernetics, vol. 2, pp. 324–329 (1999)
Hammal, Z., Massot, C., Bedoya, G., Caplier, A.: Eyes Segmentation Applied to Gaze Direction and Vigilance Estimation. In: Singh, S., Singh, M., Apte, C., Perner, P. (eds.) ICAPR 2005. LNCS, vol. 3687, pp. 236–246. Springer, Heidelberg (2005)
Benoit, A., Caplier, A., Bonnaud, L.: Gaze direction estimation tool based on head motion analysis or iris position estimation. In: Proc. EUSIPCO2005, Antalya, Turkey (September 2005)
Ohtera, R., Horiuchi, T., Kotera, H.: Eye-gaze Detection from Monocular Camera Image Based on Physiological Eyeball Models. In: IWAIT2006. Proc. International Workshop on Advanced Image Technology, pp. 639–664 (2006)
Emsley, H.H.: Visual Optics, 5th edn. Hatton Press Ltd, London (1952)
Gullstrand, A.: Appendix II.3 The optical system of the eye, von Helmholtz H, Handbuch der physiologischen Optik (1909)
Tanaka, K., Sano, M., Ohara, S., Okudaira, M.: A parametric template method and its application to robust matching. Proc, Computer Vision and Pattern Recognition, IEEE, 620–627 (2000)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ohtera, R., Horiuchi, T., Tominaga, S. (2007). Eye-Gaze Detection from Monocular Camera Image Using Parametric Template Matching. In: Yagi, Y., Kang, S.B., Kweon, I.S., Zha, H. (eds) Computer Vision – ACCV 2007. ACCV 2007. Lecture Notes in Computer Science, vol 4843. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76386-4_67
Download citation
DOI: https://doi.org/10.1007/978-3-540-76386-4_67
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-76385-7
Online ISBN: 978-3-540-76386-4
eBook Packages: Computer ScienceComputer Science (R0)