Building a self-learning eye gaze model from user interaction data

MM 2014 - Proceedings of the 2014 ACM Conference on Multimedia

Volumn , Issue , 2014, Pages 1017-1020

  Huang, Michael Xuelin ^a   Kwok, Tiffany C K ^a   Ngai, Grace ^a   Leong, Hong Va ^a   Chan, Stephen C F ^a  

^a HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

Author keywords

Data validation; Gaze estimation; Implicit modeling; Supervised learning

Indexed keywords

LEARNING SYSTEMS; SUPERVISED LEARNING;

COMPUTER INTERACTION; DATA VALIDATION; EXPERIMENTAL EVALUATION; GAZE ESTIMATION; IMPLICIT MODEL; INCREMENTAL DATA; STRONG CORRELATION; USER INTERACTION;

LEARNING ALGORITHMS;

EID: 84913526109     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2647868.2655031     Document Type: Conference Paper

References (16)

1. Alnajar, F., Gevers, T., Valenti, R. and Ghebreab, S. Calibration-Free Gaze Estimation Using Human Gaze Patterns. In IEEE ICCV, 2013, 137-144.
2. Bennett, K. P. Nonlinear Eye Gaze Mapping Function Estimation via Support Vector Regression. In ICPR, 2006, 1132-1135.
3. Cerrolaza, J. J., Villanueva, A. and Cabeza, R. Study of Polynomial Mapping Functions in Video-Oculography Eye Trackers. ACM Trans. on Computer-Human Interaction. 19, 2, 2012, 1-25.
4. Cootes, T. F., Edwards, G. J. and Taylor, C. J. Active appearance models. IEEE Trans on Pattern Analysis and Machine Intelligence. 23, 6, 2001, 681-685.
5. Cootes, T. F. and Taylor, C. J. Active Shape Models - "Smart Snakes." BMVC, 1992, 266-275.
6. Drucker, H., Burges, C. J. C., Kaufman, L., Smola, A. and Vapnik, V. Support vector regression machines. In NIPS, 1997, 155-161.
7. Duchowski, A. T. Eye Tracking Methodology: Theory and Practice. Springer London. 2003.
8. Hansen, D. W. and Ji, Q. In the eye of the beholder: a survey of models for eyes and gaze. IEEE Trans on Pattern Analysis and Machine Intelligence. 32, 3, 2010, 478-500.
9. Judd, T., Ehinger, K., Durand, F. and Torralba, A. Learning to predict where humans look. IEEE ICCV, 2009, 2106-2113.
10. Leo Breiman 2001. Random Forests. Machine Learning. 45, 1. 2001, 5-32.
11. Lu, F., Okabe, T., Sugano, Y. and Sato, Y. Learning gaze biases with head motion for head pose-free gaze estimation. Image and Vision Computing. 32, 3, 2014, 169-179.
12. Lu, F., Sugano, Y, Okabe, T. and Sato, Y. Inferring Human Gaze from Appearance via Adaptive Linear Regression. IEEE Trans on Pattern Analysis and Machine Intelligence. 2014, 1-1.
13. Paul Viola, M. J. Robust Real-time Object Detection. Int. J. Computer Vision. 2001.
14. Saragih, J. M., Lucey, S. and Cohn, J. F. Face alignment through subspace constrained mean-shifts. ICCV. 2009, 1034-1041.
15. Sugano, Y, Matsushita, Y, Sato, Y. and Koike, H. An Incremental Learning Method for Unconstrained Gaze Estimation. In ECCV, 2008, 656-667.
16. Xiong, X. and De La Torre, F. Supervised Descent Method and Its Applications to Face Alignment. CVPR, 2013, 532-539.