Abstract
A multistage procedure to detect eye features is presented. Multiresolution and topographic classification are used to detect the iris center. The eye corner is calculated combining valley detection and eyelid curve extraction. The algorithm is tested in the BioID database and in a proprietary database containing more than 1200 images. The results show that the suggested algorithm is robust and accurate. Regarding the iris center our method obtains the best average behavior for the BioID database compared to other available algorithms. Additional contributions are that our algorithm functions in real time and does not require complex post processing stages.
- Asadifard, M. and Shanbezadeh, J. 2010. Automatic adaptive center of pupil detection using face detection and cdf analysis. In Proceedings of the International MultiConference of Engineers and Computer Scientists. Vol. I., Newswood Limited, 130--133.Google Scholar
- Asteriadis, S., Nikolaidis, N., Hajdu, A., and Pitas, I. 2006. An eye detection algorithm using pixel to edge information. In Proceedings of the 2nd International Conference on Communication and Signal Processing. EURASIP.Google Scholar
- Bailenson, J. N., Pontikakis, E. D., Mauss, I. B., Gross, J. J., Jabon, M. E., Hutcherson, C. A. C., Nass, C., and John, O. 2008. Real-time classification of evoked emotions using facial feature tracking and physiological responses. Int. J. Hum.-Comput. Stud. 66, 303--317. Google Scholar
Digital Library
- Behnke, S. 2002. Learning face localization using hierarchical recurrent networks. In Proceedings of the International Conference on Artificial Neural Networks. 1319--1324. Google Scholar
Digital Library
- Belhumeur, P. N., Jacobs, D. W., Kriegman, D. J., and Kumar, N. 2011. Localizing parts of faces using a consensus of exemplars. In Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition. Google Scholar
Digital Library
- Bertolino, P. and Montanvert, A. 1996. Multiresolution segmentation using the irregular pyramid. In Flexibility and Constraint in Behavioral Systems, R. J. Greenspan and C. P. Kyriacou, Eds., John Wiley and Sons, 257--260.Google Scholar
- Bicego, M., Lagorio, A., Grosso, E., and Tistarelli, M. 2006. On the use of sift features for face authentication. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. IEEE. Google Scholar
Digital Library
- Bolt, R. A. 1982. Eyes at the interface. In Proceedings of the 1982 conference on Human factors in computing systems. In Proceedings of the Conference on Human Factors in Computing Systems (CHI'82). ACM, New York, 360--362. Google Scholar
Digital Library
- Campadelli, P. and Lanzarotti, R. 2006. Precise eye localization through a general-to-specific model definition. In Proceedings of the British Machine Vision Conference.Google Scholar
- Chen, D., Tang, X., Ou, Z., and Xi, N. 2006. A hierarchical floatboost and mlp classifier for mobile phone embedded eye location system. In Proceedings of the 3rd International Conference on Advances in Neural Networks. Vol. 2., 20--25. Google Scholar
Digital Library
- Cristinacce, D., Cootes, T., and Scott, I. 2004. A multi-stage approach to facial feature detection. In Proceedings of the 15th British Machine Vision Conference. 277--286.Google Scholar
- Dibeklioglu, H., Salah, A. A., and Gevers, T. 2011. A statistical method for 2d facial landmarking. IEEE Trans. Image Process. Google Scholar
Digital Library
- Dyer, C. R. 1987. Parallel Computer Vision. Academic Press Professional, Inc., San Diego, CA, Chapter multiscale image understanding, 171--213. Google Scholar
Digital Library
- Ellis, S., Candrea, R., Misner, J., Craig, C. S., and Lankford, C. P. 1998. Windows to the soul? What eye movements tell us about software usability. In Proceedings of the 7th Annual Conference of the Usability Professionals' Association.Google Scholar
- Ferdowsi, S. and Ahmadyfard, A. 2008. Using statistical moments as invariants for eye detection. In Proceedings of the 16th European Signal Processing Conference (EUSIPCO'08). EURASIP.Google Scholar
- Fukuda, T., Morimoto, K., and Yamana, H. 2010. Model-based eye-tracking method for low-resolution eye-images. In Proceedings of the International Workshop on Eye Gaze in Intelligent Human Machine Interaction.Google Scholar
- Haiying, X. and Guoping, Y. 2009. A novel method for eye corner detection based on weighted variance projection function. In Proceedings of the 2nd International Congress on Image and Signal Processing (CISP'09). 1--4.Google Scholar
- Hamouz, M., Kittler, J., Kamarainen, J. K., Paalanen, P., Kalviainen, H., and Matas, J. 2005. Feature-based affine-invariant localization of faces. IEEE Trans. Pattern Anal. Mach. Intell. 27, 1490--1495. Google Scholar
Digital Library
- Hansen, D. W. and Ji, Q. 2010. In the eye of the beholder: A survey of models for eyes and gaze. IEEE Trans. Pattern Anal. Mach. Intell. 32, 3, 478--500. Google Scholar
Digital Library
- Ince, I. and Kim, J. 2011. A 2d eye gaze estimation system with low-resolution webcam images. EURASIP J. Adv. Sig. Proc.Google Scholar
- Ince, I. F. and Yang, T.-C. 2009. A new low-cost eye tracking and blink detection approach: extracting eye features with blob extraction. In Emerging Intelligent Computing Technology and Applications, Springer, 526--533. Google Scholar
Digital Library
- Jesorsky, O., Kirchberg, K. J., and Frischholz, R. 2001. Robust face detection using the hausdorff distance. In Proceedings of the International Conference on Audio- and Video-Based Biometric Person Authentication. 90--95. Google Scholar
Digital Library
- Kroon, B., Hanjalic, A., and Maas, S. M. P. 2008. Eye localization for face matching: is it always useful and under what conditions? In Proceedings of the International Conference on Image and Video Retrieval. 379--388. Google Scholar
Digital Library
- Lindeberg, T. 1994. Scale-space theory: A basic tool for analysing structures at different scales. J. Appl. Statist., 224--270.Google Scholar
Cross Ref
- Majaranta, P., Aoki, H., Donegan, M., Hansen, D. W., Hansen, J. P., Hyrskykari, A., and Raiha, K. 2011. Gaze Interaction and Applications of Eye Tracking: Advances in Assistive Technologies. IGI Global. Google Scholar
Digital Library
- Meer, P. and Weiss, I. 1992. Smoothed differentiation filters for images. J. Vis. Comun. Image Represent. 3, 58--72. Google Scholar
Digital Library
- Merchant, J., Morrissette, R., and Porterfield, J. 1974. Remote measurement of eye direction allowing subject motion over one cubic foot of space. IEEE Trans. Biomed. Eng. 21, 4, 309--317.Google Scholar
Cross Ref
- Min, R., Hadid, A., and Dugelay, J.-L. 2011. Improving the recognition of faces occluded by facial accessories. In Proceedings of the 9th IEEE Conference on Automatic Face and Gesture Recognition.Google Scholar
- Mitra, S. and Acharya, T. 2007. Gesture recognition: A survey. IEEE Trans. Syst. Man Cybern. Part C Appl. Rev. 37, 3, 311--324. Google Scholar
Digital Library
- Monty, R. and Senders, J., Eds. 1976. Eye Movements and Psychological Processes. Lawrence Erlbaum Associates.Google Scholar
- Morimoto, C. H. and Mimica, M. R. M. 2005. Eye gaze tracking techniques for interactive applications. Comput. Vis. Image Underst. 98, 4--24. Google Scholar
Digital Library
- Moriyama, T., Kanade, T., Xiao, J., and Cohn, J. F. 2006. Meticulously detailed eye region model and its application to analysis of facial images. IEEE Trans. Pattern Anal. Mach. Intell. 28, 738--752. Google Scholar
Digital Library
- Niu, Z., Shan, S., Yan, S., Chen, X., and Gao, W. 2006. 2d cascaded adaboost for eye localization. In Proceedings of the 18th International Conference on Pattern Recognition. Vol. 2, 1216--1219. Google Scholar
Digital Library
- Phillips, P. 1998. The FERET database and evaluation procedure for face-recognition algorithms. Image Vision Comput. 16, 5, 295--306.Google Scholar
Cross Ref
- Pong, T.-C., Shapiro, L. G., and Haralick, R. M. 1985. Shape estimation from topographic primal sketch. Pattern Recognit. 18, 5, 333--347.Google Scholar
Cross Ref
- Ponz, V., Villanueva, A., Sesma, L., Ariz, M., and Cabeza, R. 2011. Topography-based detection of the iris centre using multiple-resolution images. In Proceedings of the Irish Machine Vision and Image Processing Conference (IMVIP'11). 1--4. Google Scholar
Digital Library
- Poole, A. and Ball, L. J. 2005. Eye Tracking in Human-Computer Interaction and Usability Research: Current Status and Future Prospects. In Encyclopedia of Human Computer Interaction, C. Ghaoui, Ed., IGI Global.Google Scholar
- Research, B. T. 2001. The bioid face database. www.bioid.com.Google Scholar
- Sewell, W. and Komogortsev, O. 2010. Real-time eye gaze tracking with an unmodified commodity webcam employing a neural network. In Proceedings of the 28th International Conference Extended Abstracts on Human Factors in Computing Systems. (CHI EA'10). ACM, New York, 3739--3744. Google Scholar
Digital Library
- Shih, F. Y., Chuang, C.-F., and Wang, P. S. P. 2008. Performance comparisons of facial expression recognition in Jaffe database. Int. J. Patt. Recogn. Artif. Intell. 22, 3, 445--459.Google Scholar
Cross Ref
- Sigut, J. and Sidha, S.-A. 2011. Iris center corneal reflection method for gaze tracking using visible light. IEEE Trans. Biomed. Eng. 58, 2, 411--419.Google Scholar
Cross Ref
- Starker, I. and Bolt, R. A. 1990. A gaze-responsive self-disclosing display. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, New York, 3--10. Google Scholar
Digital Library
- Taheri, S., Turaga, P., and Chellappa, R. 2011. Towards view-invariant expression analysis using analytic shape manifolds. In Proceedings of the IEEE International Conference on Automatic Face & Gesture Recognition and Workshops (FG'11). IEEE.Google Scholar
- Tian, Y.-L., Kanade, T., and Cohn, J. F. 2000. Eye-state action unit detection by Gabor wavelets. In Proceedings of the 3rd International Conference on Advances in Multimodal Interfaces (ICMI'00). Springer, 143--150. Google Scholar
Digital Library
- Timm, F. and Barth, E. 2011. Accurate eye centre localisation by means of gradients. In Proceedings of the International Conference on Computer Theory and Applications. Vol. 1., INSTICC, 125--130.Google Scholar
- Türkan, M., Pardàs, M., and Çetin, A. E. 2007. Human eye localization using edge projections. In Proceedings of the International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. Vol. 1., 410--415.Google Scholar
- Valenti, R. and Gevers, T. 2008. Accurate eye center location and tracking using isophote curvature. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.Google Scholar
- Valenti, R., Staiano, J., Sebe, N., and Gevers, T. 2009. Webcam-based visual gaze estimation. In Proceedings of the International Conference on Image Analysis and Processing. 662--671. Google Scholar
Digital Library
- Vertegaal, R. 1999. The gaze groupware system: mediating joint attention in multiparty communication and collaboration. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI'99). ACM, New York, 294--301. Google Scholar
Digital Library
- Viola, P. and Jones, M. 2004. Robust real-time face detection. Int. J. Computer Vision 57, 137--154. Google Scholar
Digital Library
- Wang, J., Yin, L., and Moore, J. 2007. Using geometric properties of topographic manifold to detect and track eyes for human-computer interaction. ACM Trans. Multimedia Comput. Commun. Appl. 3, 4. Google Scholar
Digital Library
- Xu, C., Zheng, Y., and Wang, Z. 2008. Semantic feature extraction for accurate eye corner detection. In Proceedings of the 19th International Conference on Pattern Recognition (ICPR'08). IEEE, 1--4.Google Scholar
- Zhou, R., He, Q., Wu, J., Hu, C., and Meng, Q. H. 2011. Inner and outer eye corners detection for facial features extraction based on ctgf algorithm. Applied Mechanics and Materials Volume Information Technology for Manufacturing Systems II.Google Scholar
- Zhou, Z.-H. and Geng, X. 2004. Projection functions for eye detection. Pattern Recognit. 37, 5, 1049--1056.Google Scholar
Cross Ref
- Zhu, J. and Yang, J. 2002. Subpixel eye gaze tracking. In Proceedings of the 5th IEEE International Conference on Automatic Face and Gesture Recognition. 124--129. Google Scholar
Digital Library
Index Terms
Hybrid method based on topography for robust detection of iris center and eye corners
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