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FACS-coding of facial expressions

Published: 18 June 2009 Publication History

Abstract

Facial expressions can be coded manually using FACS, which is based on local visual movements of the face, called Action Units, caused by contraction/dilatation of facial muscles. Automatic coding tools based on AU's are still under development. In this paper, we present a tool to generate facial expressions. The GUI of that tool has moving sliders corresponding to the activation of AU's. All generated facial expressions can be coded by the position of the sliders and as a consequence the percentage of activation of AU's. We coded 21 well-known emotional facial expressions. The contribution of this paper consists of investigating whether the Euclidean distance measure in the AU-coded space can be used as a semantic distance measure.

References

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Essa, I. A., A. P. Pentland, Coding, analysis, interpretation, and recognition of facial expressions. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 19, no. 9, pp. 757--763, 1997.
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Lien, J. J., T. Kanade, J. F. Cohn, C. C. Li, Detection, tracking, and classification of action units in facial expression. Robotics and Autonomous Systems, vol. 31, pp. 131--146, 2000.
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Pantic, M., L. J. M. Rothkrantz, Expert System for Automatic Analysis of Facial Expressions. Image and Vision Computing, vol. 18, no. 11, pp. 881--905, 2000.
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Whissell, C. M., M. J. Dewson, The Dictionary of Affect in Language. in Emotion: Theory, Research, and Experience. New York, USA: Academic Press, 1989, vol. 18, pp. 113--131.
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Wojdel, A., Knowledge Driven Facial Modelling. PhD Thesis, Delft University of Technology, Delft, 2005.
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The Machine Perception Toolbox, http://mplab.ucsd.edu/grants/project1/free-software/mptwebsite/API/.
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Sun, X., L. J. M. Rothkrantz, D. Datcu, P. Wiggers, A Bayesian Approach to Recognise facial Expressions using Vector Flow. CompSysTech'09, Rousse, Bulgaria, 2009.
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Cited By

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  • (2023)Expression Recognition Using a Flow-Based Latent-Space RepresentationPattern Recognition, Computer Vision, and Image Processing. ICPR 2022 International Workshops and Challenges10.1007/978-3-031-37745-7_11(151-165)Online publication date: 29-Jul-2023

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CompSysTech '09: Proceedings of the International Conference on Computer Systems and Technologies and Workshop for PhD Students in Computing
June 2009
653 pages
ISBN:9781605589862
DOI:10.1145/1731740
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

Publication History

Published: 18 June 2009

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Author Tags

  1. Whissell score
  2. action units
  3. facial animation
  4. facial expression coding scheme (FACS)
  5. recognition facial expressions

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CompSysTech '09

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Overall Acceptance Rate 241 of 492 submissions, 49%

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View all
  • (2023)Expression Recognition Using a Flow-Based Latent-Space RepresentationPattern Recognition, Computer Vision, and Image Processing. ICPR 2022 International Workshops and Challenges10.1007/978-3-031-37745-7_11(151-165)Online publication date: 29-Jul-2023

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