×

A robust eye detection method using combined binary edge and intensity information. (English) Zbl 1096.68730

Summary: A new eye detection method is presented. The method consists of three steps: (1) extraction of Binary Edge Images (BEIs) from the grayscale face image based on multi-resolution wavelet transform, (2) extraction of eye regions and segments from BEIs and (3) eye localization based on light dots and intensity information. In the paper, an improved face region extraction algorithm and a light dots detection algorithm are proposed for better eye detection performance. Also a multi-level eye detection scheme is adopted. Experimental results show that a correct eye detection rate of 98.7% can be achieved on 150 Bern images with variations in views and gaze directions and 96.6% can be achieved on 564 AR images with different facial expressions and lighting conditions.

MSC:

68T10 Pattern recognition, speech recognition
68U10 Computing methodologies for image processing

Software:

FERET; AR face
PDFBibTeX XMLCite
Full Text: DOI

References:

[1] Yang, M.-H.; Kriegman, D. J.; Ahuja, N., Detecting faces in images: a survey, IEEE Trans. Pattern Anal. Mach. Intell., 24, 1, 34-58 (2002)
[2] Hsu, R.-L.; Abdel-Mottaleb, M.; Jain, A. K., Face detection in color images, IEEE Trans. Pattern Anal. Mach. Intell., 24, 5, 696-706 (2002)
[3] Samal, A.; Iyengar, P. A., Automatic recognition and analysis of human faces and facial expressions: a survey, Pattern Recognition, 25, 1, 65-77 (1992)
[4] Brunelli, R.; Poggio, T., Face Recognition: features versus templates, IEEE Trans. Pattern Anal. Mach. Intell., 15, 10, 1042-1052 (1993)
[5] Gao, Y.; Maylor, K. H., Face recognition using line edge map, IEEE Trans. Pattern Anal. Mach. Intell., 24, 6, 764-779 (2002)
[6] Fasel, B.; Luettin, J., Automatic facial expression analysis: a survey, Pattern Recognition, 36, 259-275 (2003) · Zbl 1007.68947
[7] Tian, Y.; Kanade, T.; Cohn, J. F., Recognizing action units for facial expression analysis, IEEE Trans. Pattern Anal. Mach. Intell., 23, 2, 97-115 (2001)
[8] Han, C. C.; Liao, H. Y.M.; Yu, G. J.; Chen, L. H., Fast face detection via morphology-based pre-processing, Pattern Recognition, 33, 1701-1712 (2000)
[9] Wu, J.; Zhou, Z. H., Efficient face candidates selector for face detection, Pattern Recognition, 36, 1175-1186 (2003)
[10] Huang, J.; Wechsler, H., Visual routines for eye location using learning and evolution, IEEE Trans. Evol. Comput., 4, 1, 73-82 (2000)
[11] Phillips, P. J.; Moon, H.; Rizvi, S. A.; Rauss, P. J., The FERET evaluation methodology for face recognition algorithms, IEEE Trans. Pattern Anal. Mach. Intell., 22, 10, 1090-1104 (2000)
[12] Z. Zhu, K. Fujimura, Q. Ji, Real-time eye detection and tracking under various light conditions, in: ACM SIGCHI symposium on eye tracking research and applications, New Orleans, LA, USA, 2002.; Z. Zhu, K. Fujimura, Q. Ji, Real-time eye detection and tracking under various light conditions, in: ACM SIGCHI symposium on eye tracking research and applications, New Orleans, LA, USA, 2002.
[13] A Haro, M. Flickner, I. Essa, Detecting and tracking eyes by using their physiological properties, dynamics, and appearance, in: IEEE Proceedings of the International Conference on Computer Vision and Pattern Recognition (CVPR 2000), South Carolina, USA, 2000, pp. 163-168.; A Haro, M. Flickner, I. Essa, Detecting and tracking eyes by using their physiological properties, dynamics, and appearance, in: IEEE Proceedings of the International Conference on Computer Vision and Pattern Recognition (CVPR 2000), South Carolina, USA, 2000, pp. 163-168.
[14] Morimoto, C. H.; Koons, D.; Amir, A.; Flickner, M., Pupil detection and tracking using multiple light sources, Image and Vis. Comput., 18, 331-335 (2000)
[15] Beymer, D. J., Face recognition under varying pose, (IEEE Proceedings of the International Conference on Computer Vision and Pattern Recognition (CVPR’94) (1994), Seattle: Seattle Washington, USA), 756-761
[16] Pentland, A.; Moghanddam, B.; Starner, T., View-based and modular eigenspaces for face recognition, (IEEE Proceedings of the International Conference on Computer Vision and Pattern Recognition (CVPR’94) (1994), Seattle: Seattle Washington, USA), 84-91
[17] Yuille, A. L.; Hallinan, P. W.; Cohen, D. S., Feature extraction from faces using deformable template, Int. J. Comput. Vis., 8, 2, 99-111 (1992)
[18] Lam, K. M.; Yan, H., Locating and extracting the eye in human face images, Pattern Recognition, 29, 5, 771-779 (1996)
[19] Kawaguchi, T.; Rizon, M., Iris detection using intensity and edge information, Pattern Recognition, 36, 549-562 (2003)
[20] Chow, G.; Li, X., Towards a system for automatic facial feature detection, Pattern Recognition, 26, 1739-1755 (1993)
[21] Feng, G. C.; Yuen, P. C., Multi-cues eye detection on gray intensity image, Pattern Recognition, 34, 1033-1046 (2001) · Zbl 1006.68855
[22] Feng, G. C.; Yuen, P. C., Variance projection function and its application to eye detection for human face recognition, Pattern Recognition Lett., 19, 899-906 (1998)
[23] Zhou, Z. H.; Geng, X., Projection functions for eye detection, Pattern Recognition, 37, 5, 1049-1056 (2004) · Zbl 1056.68585
[24] Sirohey, S. A.; Rosenfeld, A., Eye detection in a face image using linear and nonlinear filters, Pattern Recognition, 34, 1367-1391 (2001) · Zbl 0978.68119
[25] B. Achermann. The face database of University of Bern, http://iamwww.unibe.ch/ fkiwww/staff/achermann.html; B. Achermann. The face database of University of Bern, http://iamwww.unibe.ch/ fkiwww/staff/achermann.html
[26] A.M. Martinez, R. Benavente, The AR Face Database, CVC Technical Report #24, June 1998.; A.M. Martinez, R. Benavente, The AR Face Database, CVC Technical Report #24, June 1998.
[27] Lee, S. Y.; Ham, Y. K.; Park, R. H., Recognition of human faces using knowledge-based feature extraction and neuro-fuzzy algorithm, Pattern Recognition, 29, 11, 1863-1876 (1996)
[28] Jesorsky, O.; Kirchberg, K. J.; Frischholz, R. W., Robust Face detection using the Hausdorff distance, (Proceedings of the Third International Conference on Audio- and Video-based Biometric Person Authentication (2001), Halmstad: Halmstad Sweden), 90-95 · Zbl 0987.68966
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.