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A robust agorithm for eye detection on gray intensity face without spectacles
Keywords:
Eye detection, Face detection, Face recognition, Image processing, Pattern recognitionAbstract
This paper presents a robust eye detection algorithm for gray intensity images. The idea of our method is to combine the respective advantages of two existing techniques, feature based method and template based method, and to overcome their shortcomings. Firstly, after the location of face region is detected, a feature based method will be used to detect two rough regions of both eyes on the face. Then an accurate detection of iris centers will be continued by applying a template based method in these two rough regions. Results of experiments to the faces without spectacles show that the proposed approach is not only robust but also quite efficient.
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References
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[2] Y. Tian, T. Kanade, J.F. Cohn, Recognizing upper face action units for facial expression analysis, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Hilton Head Island, South Carolina, 2000, Vol. 1, pp. 294–301.
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[6] M. Nixon, Eye spacing measurement for facial recognition, in: Proc. of the Society of Photo-Optical Instrument Engineers, 1985.
[7] A. Pentland, B. Moghaddam, T. Starner, View-based and modular eigenspaces for face recognition, in: Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR’94), Seattle, WA, 1994.
[8] W. min Huang and R. Mariani, Face detection and precise eyes location, in: Proc. Int. Conf. on Pattern Recognition (ICPR’00), 2000.
[9] J. Huang, H. Wechsler, Eye detection using optimal wavelet packets and radial basis functions (rbfs), Int. J. Pattern Recognit. Artif. Intell. 13 (7) (1999) 1009–1025.
[10] G.C. Feng, P.C. Yuen, Variance projection function and its application to eye detection for human face recognition, Int. J. Comput. Vis. 19 (1998) 899–906.
[11] G.C. Feng, P.C. Yuen, Multi-cues eye detection on gray intensity image, Pattern Recognit. 34 (2001) 1033–1046.
[12] S. Kawato, J. Ohya, Real-time detection of nodding and head-shaking by directly detecting and tracking the between-eyes, in: Proc. 4th IEEE Int. Conf. on Automatic Face and Gesture Recognition, 2000, pp. 40–45.
[13] Y. Tian, T. Kanade, J.F. Cohn, Dual-state parametric eye tracking, in: Proc. 4th IEEE Int. Conf. On Automatic Face and Gesture Recognition, 2000.
[14] S.A. Sirohey, A. Rosenfeld, Eye detection in a face image using linear and nonlinear filters, Pattern Recognit. 34 (2001) 1367–1391.
[15] G. Chow, X. Li, Toward a system for automatic facial feature detection, Pattern Recognition 26 (1993) 1739–1755.
[16] K.M. Lam, H. Yan, Locating and extracting the eye in human face images, Pattern Recognition 29 (5) (1996) 771–779.
[17] H.A. Rowley, S. Baluja, T. Kanade, Neural network-based face detection, IEEE Trans. Pattern Anal. Mach. Intell. 20 (1) (1998) 23–38.
[18] K.K. Sung, T. Poggio, Example-based learning for viewbase human face detection, IEEE Trans, Pattern Anal. Mach. Intell. 20 (1) (1998) 39–51.
[19] P.C. Yuen, G.C. Feng, J.P. Zhou, A contour detection method: initialization and contour model, Pattern Recognition Lett. 20 (2) (1999) 141–148.
[2] Y. Tian, T. Kanade, J.F. Cohn, Recognizing upper face action units for facial expression analysis, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Hilton Head Island, South Carolina, 2000, Vol. 1, pp. 294–301.
[3] A.L. Yuille, P.W. Hallinan, D.S. Cohen, Feature extraction from faces using deformable templates, Int. J. Comput. Vision 8 (2) (1992) 99–111.
[4] X. Xie, R. Sudhakar, H. Zhuang, On improving eye feature extraction using deformable templates, Pattern Recognit. 27 (1994) 791–799.
[5] K.M. Lam, H. Yan, Locating and extracting the eye in human face images, Pattern Recognit. 29 (1996) 771–779.
[6] M. Nixon, Eye spacing measurement for facial recognition, in: Proc. of the Society of Photo-Optical Instrument Engineers, 1985.
[7] A. Pentland, B. Moghaddam, T. Starner, View-based and modular eigenspaces for face recognition, in: Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR’94), Seattle, WA, 1994.
[8] W. min Huang and R. Mariani, Face detection and precise eyes location, in: Proc. Int. Conf. on Pattern Recognition (ICPR’00), 2000.
[9] J. Huang, H. Wechsler, Eye detection using optimal wavelet packets and radial basis functions (rbfs), Int. J. Pattern Recognit. Artif. Intell. 13 (7) (1999) 1009–1025.
[10] G.C. Feng, P.C. Yuen, Variance projection function and its application to eye detection for human face recognition, Int. J. Comput. Vis. 19 (1998) 899–906.
[11] G.C. Feng, P.C. Yuen, Multi-cues eye detection on gray intensity image, Pattern Recognit. 34 (2001) 1033–1046.
[12] S. Kawato, J. Ohya, Real-time detection of nodding and head-shaking by directly detecting and tracking the between-eyes, in: Proc. 4th IEEE Int. Conf. on Automatic Face and Gesture Recognition, 2000, pp. 40–45.
[13] Y. Tian, T. Kanade, J.F. Cohn, Dual-state parametric eye tracking, in: Proc. 4th IEEE Int. Conf. On Automatic Face and Gesture Recognition, 2000.
[14] S.A. Sirohey, A. Rosenfeld, Eye detection in a face image using linear and nonlinear filters, Pattern Recognit. 34 (2001) 1367–1391.
[15] G. Chow, X. Li, Toward a system for automatic facial feature detection, Pattern Recognition 26 (1993) 1739–1755.
[16] K.M. Lam, H. Yan, Locating and extracting the eye in human face images, Pattern Recognition 29 (5) (1996) 771–779.
[17] H.A. Rowley, S. Baluja, T. Kanade, Neural network-based face detection, IEEE Trans. Pattern Anal. Mach. Intell. 20 (1) (1998) 23–38.
[18] K.K. Sung, T. Poggio, Example-based learning for viewbase human face detection, IEEE Trans, Pattern Anal. Mach. Intell. 20 (1) (1998) 39–51.
[19] P.C. Yuen, G.C. Feng, J.P. Zhou, A contour detection method: initialization and contour model, Pattern Recognition Lett. 20 (2) (1999) 141–148.
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Published
2005-10-03
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[1]
“A robust agorithm for eye detection on gray intensity face without spectacles”, JCS&T, vol. 5, no. 03, pp. p. 127–132, Oct. 2005, Accessed: Feb. 08, 2026. [Online]. Available: https://journal.info.unlp.edu.ar/JCST/article/view/861
