Geometric generative gaze estimation (G3E) for remote RGB-D cameras

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn , Issue , 2014, Pages 1773-1780

  Mora, Kenneth Alberto Funes ^a   Odobez, Jean Marc ^a,b  

^a IDIAP RESEARCH INSTITUTE   (Switzerland)

^b EPFL   (Switzerland)

Author keywords

gaze estimation; generative model; HCI; HHI; HRI; RGB D; segmentation

Indexed keywords

CAMERAS; HUMAN COMPUTER INTERACTION; IMAGE SEGMENTATION; PATTERN RECOGNITION; SEMANTICS; SOCIOLOGY;

AMBIENT CONDITIONS; GAZE ESTIMATION; GENERATIVE MODEL; GENERATIVE PROCESS; GEOMETRICAL APPROACHES; HIGH RESOLUTION IMAGE; SEMANTIC SEGMENTATION; STATE-OF-THE-ART METHODS;

GEOMETRY;

EID: 84911439384     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2014.229     Document Type: Conference Paper

References (18)

1. S. Baluja and D. Pomerleau. Non-Intrusive Gaze Tracking Using Artificial Neural Networks. Technical report, CMU, 1994.
2. C. M. Bishop. Pattern Recognition and Machine Learning (Information Science and Statistics). Springer, Oct. 2007.
3. K. A. Funes Mora and J.-M. Odobez. Gaze estimation from multimodal Kinect data. In Computer Vision and Pattern Recognition Workshops, pages 25-30, June 2012.
4. E. D. Guestrin and M. Eizenman. General theory of remote gaze estimation using the pupil center and corneal reflections. Trans. on bio-medical engineering, June 2006.
5. E. D. Guestrin and M. Eizenman. Listing's and Donders' laws and the estimation of the point-of-gaze. In Symp. on Eye Tracking Research & Applications, Austin, TX, 2010.
6. D. W. Hansen and Q. Ji. In the eye of the beholder: a survey of models for eyes and gaze. IEEE trans. on pattern analysis and machine intelligence, 32(3):478-500, Mar. 2010.
7. T. Ishikawa, S. Baker, I. Matthews, and T. Kanade. Passive Driver Gaze Tracking with Active Appearance Models. In Proc. World Congress on Intelligent Transportation Systems, pages 1-12, Oct. 2004.
8. F. Lu, Y. Sugano, T. Okabe, and Y. Sato. Inferring human gaze from appearance via adaptive linear regression. In Int. Conf. on Computer Vision, Barcelona, Nov. 2011.
9. F. Lu, Y. Sugano, T. Okabe, and Y. Sato. Head pose-free appearance-based gaze sensing via eye image synthesis. In Int. Conf. on Pattern Recognition, Nov. 2012.
10. F. Lu, O. Takahiro, Y. Sugano, and Y. Sato. A Head Pose-free Approach for Appearance-based Gaze Estimation. In Proc. of the British Machine Vision Conference, 2011.
11. T. Moriyama and J. Cohn. Meticulously detailed eye model and its application to analysis of facial image. Int. Conf. on Systems, Man and Cybernetics, 1:629-634, 2004.
12. M. Opper and C. Archambeau. The variational gaussian approximation revisited. Neural Comput., Mar. 2009.
13. P. Paysan, R. Knothe, B. Amberg, S. Romdhani, and T. Vetter. A 3D Face Model for Pose and Illumination Invariant Face Recognition. In Proceedings of Advanced Video and Signal based Surveillance, Genova, Italy, 2009. IEEE.
14. Y. Sugano, Y. Matsushita, Y. Sato, and H. Koike. An incremental learning method for unconstrained gaze estimation. In ECCV, pages 656-667. Springer, 2008.
15. O. Williams, A. Blake, and R. Cipolla. Sparse and semi-supervised visual mapping with the S3GP. In Computer Vision and Pattern Recognition, pages 230-237, 2006.
16. D. Winfield and D. Parkhurst. Starburst: A hybrid algorithm for video-based eye tracking combining feature-based and model-based approaches. Proc. of Computer Vision and Pattern Recognition Workshops, 3:79-79.
17. H. Yamazoe, A. Utsumi, T. Yonezawa, and S. Abe. Remote gaze estimation with a single camera based on facial-feature tracking without special calibration actions. In Symp. on Eye Tracking Research & Applications, New York, 2008.
18. A. L. Yuille, P. W. Hallinan, and D. S. Cohen. Feature extraction from faces using deformable templates. International Journal of Computer Vision, 8(2):99-111, Aug. 1992.