Human eye sclera detection and tracking using a modified time-adaptive self-organizing map

Pattern Recognition

Volumn 41, Issue 8, 2008, Pages 2571-2593

  Khosravi, Mohammad Hossein ^a,b   Safabakhsh, Reza ^a  

^a AMIRKABIR UNIVERSITY OF TECHNOLOGY   (Iran)

^b UNIVERSITY OF BIRJAND   (Iran)

Author keywords

Active contour modeling; Eye sclera motion tracking; GVF snake; Human eye detection; TASOM; Time adaptive SOM

Indexed keywords

ALGORITHMS; FEATURE EXTRACTION; MATHEMATICAL MODELS; NEURONS;

ACTIVE CONTOUR MODELING; EYE SCLERA MOTION TRACKING; GVF SNAKE; HUMAN EYE DETECTION; TASOM; TIME-ADAPTIVE SOM;

TRACKING (POSITION);

EID: 42749087701     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2008.01.012     Document Type: Article

References (53)

1. Brunelli R., and Poggio T. Face recognition: features versus templates. IEEE Trans. Pattern Anal. Mach. Intell. 15 10 (1993) 1042-1052
2. Craw I., Ellis H., and Lishman J. Automatic extraction of face features. Pattern Recognition Lett. 5 (1987) 183-187
3. Sung K.K., and Poggio T. Example-based learning for viewbase human face detection. IEEE Trans, Pattern Anal. Mach. Intell. 20 1 (1998) 39-51
4. Rowley H.A., Baluja S., and Kanade T. Neural network-based face detection. IEEE Trans. Pattern Anal. Mach. Intell. 20 1 (1998) 23-38
5. Rowley H.A., Baluja S., and Kanade T. Rotation invariant neural network-based face detection. Proceedings of Computer Vision and Pattern Recognition (1998)
6. Lam K.M., and Yan H. An analytic-to holistic approach for face recognition based on a single frontal view. IEEE Trans. Pattern Anal. Mach. Intell. 20 7 (1998) 673-686
7. Feng G.C., and Yuen P.C. Variance projection function and its application to eye detection for human face recognition. Pattern Recognition Lett. 19 (1998) 899-906
8. Waite J.B., and Welsh W.J. Head boundary location using snakes. Br. Telecom Technol. J. 8 3 (1990) 127-136
9. Gunn S.R., and Nixon M.S. Active contours for head boundary extraction by global and local energy minimisation, Department of Electronics and Computer Science (1997), University of Southampton
10. Turk M., and Pentland A. Eigenfaces for recognition. J. Cognit. Neurosci. 3 1 (1991) 71-86
11. Moghaddam B., and Pentland A. Probabialistic visual learning for object recognition. IEEE Trans. Pattern Anal. Mach. Intell. 19 7 (1997) 696-710
12. Yang M.-H., Ahuja N., and Kriegman D. Mixtures of linear subspaces for face detection. Proceedings of the Fourth International Conference on Automatic Face and Gesture Recognition (2000) 70-76
13. Z. Ghahramani, G.E. Hinton, The EM algorithm for mixture of factor analyzers, Technical Report CRG-TR-96-1, Department of Computer Science, University of Toronto, 1996.
14. R. Kjeldsen, J. Kender, Finding skin in color images, in: Proceedings of the Second International Conference on Automatic Face and Gesture Recognition, Killington, VT, 1996, pp. 312-317.
15. Yang J., Lu W., and Waibel A. Skin-color modelling and adaptation. Proceedings of the ACCV (1998) 687-694
16. S.H. Kim, N.K. Kim, S.C. Ahn, H.G. Kim, Object oriented face detection using range and color information, in: Proceedings of the Third International Conference on Automatic Face and Gesture Recognition, Nara, Japan, 1998, pp. 76-81.
17. J.C. Terrillon, M. David, S. Akamatsu, Automatic detection of human faces in natural scene images by use of a skin color model and invariant moments, in: Proceedings of the Third International Conference on Automatic Face and Gesture Recognition, Nara, Japan, 1998, pp. 112-117.
18. Schiele B., and Waibel A. Gaze tracking based on face color. Proceedings of the International Wrokshop on Automatic Face and Gesture Recognition (1995) 344-349
19. Q.B. Sun, W.M. Huang, J.k. Wu, Face detection based on color and local symmetry information, in: Proceedings of the Third International Conference on Automatic Face and Gesture Recognition, Nara, Japan, 1998, pp. 130-135.
20. Jebara T.S., and Pentland A. Parametrized structure from motion for 3d adaptative feedback tracking of faces. Proceedings of the Computer Vision and Pattern Recognition (1997) 144-150
21. McKenna S.J., Gong S., and Raja Y. Modelling face color and identity with gaussian mixtures. Pattern Recognition 31 12 (1998) 1883-1892
22. Raja R., McKenna S., and Gong D. Tracking and segmenting people in varying lighting conditions using colour. Proceedings of FG'98 (1998)
23. Yang J., and Waibel A. A real-time face tracker. Proceedings of the Third IEEE Workshop on Applications of Computer Vision (1996) 142-147
24. Parmar N., and Hiscocks P. Drowsy driver detection system design project, Department of Electrical and Computer Engineering (2002), Ryerson University
25. Dowdall J., Pavlidis I., and Bebis G. Face detection in the near-ir spectrum. Image Vision Comput. 21 7 (2001) 565-578
26. Zhou Z.-H., and Geng X. Projection functions for eye detection. Pattern Recognition 37 5 (2004) 1049-1056
27. Baskan S., Mete Bulut M., and Atalay V. Projection based method for segmentation of human face and its evaluation. Pattern Recognition Lett. 23 (2002) 1623-1629
28. Gutta S., Huang J., Takacs B., and Wechsler H. Face recognition using ensembles of networks. International Conference on Pattern Recognition (ICPR) (1996), Vienna, Austria
29. Jain A.K., Zhong Y., and Dubuisson-Jolly M.-P. Deformable template models: a review. Signal Process 71 2 (1998) 109-129
30. Yuille A.L. Deformable templates for face recognition. J. Cognit. Neurosci 3 (1991) 59-70
31. Tian Y., Kanade T., and Cohn J.F. Dual-state parametric eye tracking. Proceedings of the Conference on Automatic Face and Gesture Recognition (2000)
32. Xie X., Sudhakar R., and Zhuang H. On improving eye feature extraction using deformable templates. Pattern Recognition 27 (1994) 791-799
33. Colombo C., and Bimbo A.D. Real-time head tracking from the deformation of eye contours using a piecewise affine camera. Pattern Recognition Lett. 20 (1999) 721-730
34. Huang C.L., and Chen C.W. Human facial feature extraction for face interpretation and recognition. Pattern Recognition 25 12 (1992) 1435-1444
35. Balya D., and Roska T. Face and eye detection by CNN algorithms. J. VLSI Signal Process. 23 (1999) 497-511
36. Ryu Y.S., and Oh S.Y. Automatic extraction of eye and mouth fields from a face image using eigenfeatures and multilayer perceptrons. Pattern Recognition 34 (2001) 2459-2466
37. Betke M., and Kawai J. Gaze Detection via Self-Organizing Gray-Scale Units. IEEE (1999) 70-76
38. Y.S. Chenyz, C.H. Suyz, J.H. Chenz, Video-based realtime eye tracking technique for autostereoscopic displays, in: Proceedings of the Fifth Conference on Artificial Intelligence and Applications, Taipei, Taiwan, 2000, pp. 188-193.
39. Bernogger S., Yin L., Basu A., and Pinz A. Eye tracking and animation for mpeg-4 coding. IEEE Trans. Syst. Man Cybern. 28 (1998) 1281-1284
40. Abd-Almageed W., and Smith C.E. Mixture models for dynamic statistical pressure snakes. IEEE International Conference on Pattern Recognition (2002)
41. Kapoor A., and Picard R.W. Real-time, fully automatic upper facial feature tracking. Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition FGR02 (2002)
42. S. Kawato, J. Ohya, Real-time detection of nodding and head-shaking by directly detecting and tracking the 'between-eyes', in: The Fourth International Conference on Automatic Face and Gesture Recognition, 28-30 March 2000, pp. 40-45.
43. Ji Q., and Yang X. Real-time eye gaze and face pose tracking for monitoring driver vigilance. Real-Time Imaging 8 (2002) 357-377
44. Ivins J.P., and Porrill J. A deformable model of the human iris for measuring small three-dimensional eye movements. Mach. Vision Appl. 11 (1998) 42-51
45. C. Morimoto, D. Koons, A. Amir, M. Flickner, Pupil detection and tracking using multiple light sources, Technical Report, IBM Almaden Research Center, 1998.
46. A. Haro, I. Essa, M. Flickner, Detecting and tracking eyes by using their physiological properties, in: Proceedings of the Conference on Computer Vision and Pattern Recognition, June 2000.
47. Xie X., Sudhakar R., and Zhuang H. Real-time eye feature tracking from a video image sequence using Kalman Elter. IEEE Trans. Syst. Man Cybern. 25 (1995) 1568-1577
48. Sirohey S., Rosenfeld A., and Duric Z. A method of detecting and tracking irises and eyelids in video. Pattern Recognition 35 (2002) 1389-1401
49. C. Xu, J.L. Prince, Gradient vector flow: a new external force for snakes, IEEE Proc. Conf. On Comp. Vis. Patt. Recog., pp. 66-71 (CVPR 97).
50. Shah-Hosseini H., and Safabakhsh R. TASOM: a new time adaptive self-organizing map. IEEE Trans. Syst. Man Cybern. Part B 32 2 (2003)
51. Shah-Hosseini H., and Safabakhsh R. A TASOM-based algorithm for active contour modeling. Pattern Recognition Lett. 24 9 (2003)
52. M. Kamali Moghaddam, R. Safabakhsh, TASOM-based lip tracking using the color and geometry of the face, in: Proceedings of the International Conference Machine Learning and Applications (ICMLA'05), California, LA, December 2005.
53. M.H. Khosravi, R. Safabakhsh, Human eye inner boundary detection using a modified time-adaptive self-organizing map, in: Proceedings of the IEEE International Conference on Image Processing (ICIP'05), Genova, Italy, September 2005.