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3D facial expression analysis and deformation

Published: 25 July 2007 Publication History

Abstract

Facial expressions are an important channel of non-verbal communication. An expression is a dynamic change of visual appearance involving the shape and position of facial features (the eyes, eyebrows, nose, and mouth), the coloration and condition of the skin and wrinkles. The main source that contributes to expression variation is facial muscular movements. We have used a registration framework, based on selected facial landmarks, to create expressions on surface models of the face. Deformation is applied to 3D face models with neutral expression to synthesize a corresponding model with some expression. Likewise when applied to 3D faces with expression the neutral expression can be synthesized. In addition to this work, we also analyse the optimal placement of landmarks to control facial expressions through deformation.

References

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Cohn, J., Zlochower, Lien, J., and Kanade, T. 1998. Feature-point tracking by optical flow discriminates subtle differences in facial expression. 3rd IEEE ICAFGR, pg 396--401.
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Ekman, P. and Friesen, W. 1978. Facial action coding system: A technique for the measurement of facial movement. Consulting Psychologists Press, Palo Alto.
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Essa, I. and Pentland, A. 1997. Coding analysis interpretation and recognition of facial expressions. IEEE Transactions of Pattern Analysis and Machine Intelligence, 19(7):757--763.
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Kolar, J. and Salter, E. (1997). Craniofacial Anthropometry: Practical Measurement, Charles C Thomas Publisher, Illinois.
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Pantic, M. and Rothkrantz, J. 2004. Facial action recognition for facial expression analysis from static face images. IEEE Transactions on Systems, Man and Cybernetics Part B: Cybernetics, 34(3):1149

Cited By

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  • (2014)Dynamic 3D facial expression modeling using Laplacian smooth and multi-scale mesh matchingThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-014-0960-330:6-8(649-659)Online publication date: 1-Jun-2014
  • (2008)Chapter 18Proceedings of the 2008 3rd International Conference on Geometric Modeling and Imaging10.1109/GMAI.2008.25(108-113)Online publication date: 9-Jul-2008

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cover image ACM Conferences
APGV '07: Proceedings of the 4th symposium on Applied perception in graphics and visualization
July 2007
152 pages
ISBN:9781595936707
DOI:10.1145/1272582
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 25 July 2007

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Overall Acceptance Rate 19 of 33 submissions, 58%

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Cited By

View all
  • (2014)Dynamic 3D facial expression modeling using Laplacian smooth and multi-scale mesh matchingThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-014-0960-330:6-8(649-659)Online publication date: 1-Jun-2014
  • (2008)Chapter 18Proceedings of the 2008 3rd International Conference on Geometric Modeling and Imaging10.1109/GMAI.2008.25(108-113)Online publication date: 9-Jul-2008

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