FACE TRACKING ALGORITHM ROBUST TO POSE, ILLUMINATION AND FACE EXPRESSION CHANGES: A 3D PARAMETRIC MODEL APPROACH

Marco Anisetti, Valerio Bellandi, Luigi Arnone, Fabrizio Beverina

Abstract

Considering the face as an object that moves through a scene, the posture related to the camera’s point of view and the texture both may change the aspect of the object considerably. These changes are tightly coupled with the alterations in illumination conditions when the subject moves or even when some modifications happen in illumination conditions (light switched on or off etc.). This paper presents a method for tracking a face on a video sequence by recovering the full-motion and the expression deformations of the head using 3D expressive head model. Taking advantage from a 3D triangle based face model, we are able to deal with any kind of illumination changes and face expression movements. In this parametric model, any changes can be defined as a linear combination of a set of weighted basis that could easily be included in a minimization algorithm using a classical Newton optimization approach. The 3D model of the face is created using some characteristical face points given on the first frame. Using a gradient descent approach, the algorithm is able to extract simultaneously the parameters related to the face expression, the 3D posture and the virtual illumination conditions. The algorithm has been tested on Kanade-Cohn database (Kanade et al., 2000) for expression estimation and its precision has been compared with a standard multi-camera system for the 3D tracking (Elite2002 System) (Ferrigno and Pedotti, 1985). Regarding illumination tests, we use synthetic movie created using standard 3D-mesh animation tools and real experimental videos created in very extreme illumination condition. The results in all the cases are promising even with great head movements and changes in the expression and the illumination conditions. The proposed approach has a twofold application as a part of a facial expression analysis system and preprocessing for identification systems (expression, pose and illumination normalization).

References

  1. Andreoni, C., Anisetti, M., Apolloni, B., Bellandi, V., Balzarotti, S., Beverina, F., Campadelli, P., M.R.Ciceri, P.Colombo, F.Fumagalli, G.Palmas, and L.Piccini (2004). E(motional) learning. In Technology Enhanced Learning 2004 (TEL04), Milan Italy.
  2. Anisetti, M., Bellandi, V., and Beverina, F. (Sept. 2005). Accurate 3d model based face tracking for facial expression recognition. In Proc. of International Conference on Visualization, Imaging, and Image Processing (VIIPO5), pages 93 - 98.
  3. Bellandi, V., Anisetti, M., and Beverina, F. (Sept. 2005). Upper-face expression features extraction system for video sequences. In Proc. of International Conference on Visualization, Imaging, and Image Processing (VIIP05), pages 83-88.
  4. Blanz, V. and Vetter, T. (2003). Face recognition based on fitting a 3d morphable model. IEEE Transactions on Pattern Analysis and Machine Intelligence, 25(9):1063 - 1074.
  5. Bregler, C. and Malik, J. (1998). Tracking people with twists and exponential maps. In CVPR98, pages 8- 15.
  6. Cascia, M. L., Scarloff, S., and Anthitsos, V. (2000). Fast, reliable head tracking under varying illumination: An approach based on registration of texture-mapped 3d models. IEEE Transaction on Pattern Analysis and Machine Intelligence, 2000 (22)(4):322-336.
  7. Cootes, T., Edwards, G., and Taylor, C. (Jun. 2000). Active appearance mode. IEEE Transactions on Pattern Analysis and Machine Intelligence, 23(6):681 - 685.
  8. Damiani, E., Anisetti, M., Bellandi, V., and Beverina, F. (2005). Facial identification problem: A tracking based approach. In IEEE International Symposium on Signal-Image Technology and InternetBased Systems (IEEE SITIS'05).
  9. Dornaika, F. and Ahlberg, J. (2003). Face and facial feature tracking using deformable models. International Journal of Image and Graphics.
  10. Dornaika, F. and Ahlberg, J. (Aug. 2004). Fast and reliable active appearance model search for 3-d face tracking. IEEE Transactions on Systems, Man and Cybernetics, 34(4):1838 - 1853.
  11. Eisert, P. and Girod, B. ('July 1997). Model-based 3dmotion estimation with illumination compensation. In Conference Publication.
  12. Ekman, P. and Friesen., W. (1978). Facial action coding system: A technique for the measurement of facial movement. Consulting Psychologists Press.
  13. Ferrigno, G. and Pedotti, A. (1985). Elite: a digital dedicated hardware system for movement analysis via real-time tv signal processing. IEEE Trans Biomed Eng., pages 943-950.
  14. Hager, G. D. and Belhumeur, P. N. (1998). Efficient region tracking with parametric models of geometry and illumination. IEEE Transaction on Pattern Analysis and Machine Intelligence, 1998 (20)(10):322-336.
  15. Ishiyama, R. and Sakamoto, S. (2004). Fast and accurate facial pose estimation by aligning a 3d appearance model. In Proc. of 17th international conference on pattern recognition (ICPR'04).
  16. Kanade, T., Cohn, J., and Tian, Y. (2000). Comprehensive database for facial expression analysis. Proc. 4th IEEE International Conference on Automatic Face and Gesture Recognition (FG'00), pages 46-53.
  17. Lucas, B. and Kanade, T. (1981). An iterative image registration technique with an application to stereo vision. Proc. Int. Joint Conf. Artificial Intelligence, pages 674-679.
  18. Matthews, I., Ishikawa, T., and Baker, S. (2003). The template update problem. In Proc. of the British Machine Vision Conference.
  19. Murray, R., Li, Z., and Sastray (1992). A mathematical introduction to robotic manipulation. CRC press.
  20. Tao, H. and Huang, T. (1999). Explanation-based facial motion tracking using a piecewise bier volume deformation model. In CVPR99.
  21. Xiao, J., Kanade, T., and Cohn, J. (2002). Robust fullmotion recovery of head by dynamic templates and re-registration techniques. Proc. of Conference on automatic face and gesture recognition.
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Paper Citation


in Harvard Style

Anisetti M., Bellandi V., Arnone L. and Beverina F. (2006). FACE TRACKING ALGORITHM ROBUST TO POSE, ILLUMINATION AND FACE EXPRESSION CHANGES: A 3D PARAMETRIC MODEL APPROACH . In Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, ISBN 972-8865-40-6, pages 318-325. DOI: 10.5220/0001365103180325


in Bibtex Style

@conference{visapp06,
author={Marco Anisetti and Valerio Bellandi and Luigi Arnone and Fabrizio Beverina},
title={FACE TRACKING ALGORITHM ROBUST TO POSE, ILLUMINATION AND FACE EXPRESSION CHANGES: A 3D PARAMETRIC MODEL APPROACH},
booktitle={Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP,},
year={2006},
pages={318-325},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001365103180325},
isbn={972-8865-40-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP,
TI - FACE TRACKING ALGORITHM ROBUST TO POSE, ILLUMINATION AND FACE EXPRESSION CHANGES: A 3D PARAMETRIC MODEL APPROACH
SN - 972-8865-40-6
AU - Anisetti M.
AU - Bellandi V.
AU - Arnone L.
AU - Beverina F.
PY - 2006
SP - 318
EP - 325
DO - 10.5220/0001365103180325