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short-paper

Optimal marker set for motion capture of dynamical facial expressions

Authors:

Clément Reverdy,

Caroline LarbouletteAuthors Info & Claims

MIG '15: Proceedings of the 8th ACM SIGGRAPH Conference on Motion in Games

Pages 31 - 36

https://doi.org/10.1145/2822013.2822042

Published: 16 November 2015 Publication History

Abstract

We seek to determine an optimal set of markers for marker-based facial motion capture and animation control. The problem is addressed in two different ways: on the one hand, different sets of empirical markers classically used in computer animation are evaluated; on the other hand, a clustering method that automatically determines optimal marker sets is proposed and compared with the empirical marker sets. To evaluate the quality of a set of markers, we use a blendshape-based synthesis technique that learns the mapping between marker positions and blendshape weights, and we calculate the reconstruction error of various animated sequences created from the considered set of markers in comparison to ground truth data. Our results show that the clustering method outperforms the heuristic approach.

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References

[1]

Beeler, T., Hahn, F., Bradley, D., Bickel, B., Beardsley, P., Gotsman, C., Sumner, R. W., and Gross, M. 2011. High-quality passive facial performance capture using anchor frames. ACM Trans. Graph..

Digital Library

[2]

Botsch, M., and Sorkine, O. 2008. On linear variational surface deformation methods. Visualization and Computer Graphics, IEEE Transactions on.

Digital Library

[3]

Bradley, D., Heidrich, W., Popa, T., and Sheffer, A. 2010. High resolution passive facial performance capture. ACM Trans. Graph..

Digital Library

[4]

Cao, Y., Tien, W. C., Faloutsos, P., and Pighin, F. 2005. Expressive speech-driven facial animation. ACM Transactions on Graphics.

Digital Library

[5]

Csató, L., and Opper, M. 2002. Sparse on-line gaussian processes. Neural Computation.

Digital Library

[6]

Deng, Z., Chiang, P.-Y., Fox, P., and Newmann, U. 2006. Animating blendshape faces by cross-mapping motion capture data. In Proceedings of the 2006 symposium on Interactive 3D graphics and games.

Digital Library

[7]

Ekman, P., and Friesen, W. 1978. Facial Action Coding System: A Technique for the Measurement of Facial Movement. Consulting Psychologists Press.

[8]

2012. faceshift. http://www.faceshift.com/product/.

[9]

Gibet, S., Courty, N., Duarte, K., and Le Naour, T. 2011. The SignCom System for Data-Driven Animation of Interactive Virtual Signers: Methodology and Evaluation. ACM Transaction on Interactive Intelligent Systems.

Digital Library

[10]

Le, B., Zhu, M., and Deng, Z. 2013. Marker optimization for facial motion acquisition and deformation. Visualization and Computer Graphics, IEEE Transactions on.

Digital Library

[11]

Lefebvre-Albaret, F., Gibet, S., Turki, A., Hamon, L., and Brun, R. 2013. Overview of the Sign3D Project High-fidelity 3D recording, indexing and editing of French Sign Language content. In Third International Symposium on Sign Language Translation and Avatar Technology (SLTAT) 2013.

[12]

Li, H., Adams, B., Guibas, L. J., and Pauly, M. 2009. Robust single-view geometry and motion reconstruction. ACM Trans. Graph..

Digital Library

[13]

Li, H., Weise, T., and Pauly, M. 2010. Example-based facial rigging. ACM Trans. Graph..

Digital Library

[14]

Liu, X., Mao, T., Xia, S., Yu, Y., and Wang, Z. 2008. Facial animation by optimized blendshapes from motion capture data. Computer Animation and Virtual Worlds.

Digital Library

[15]

Meyer, M., and Anderson, J. 2007. Key point subspace acceleration and soft caching. ACM Trans. Graph..

Digital Library

[16]

Rasmussen, C. E., and Williams, C. K. I. 2005. Gaussian Processes for Machine Learning. The MIT Press.

Digital Library

[17]

Sattler, M., Sarlette, R., and Klein, R. 2005. Simple and efficient compression of animation sequences. In Proceedings of the 2005 ACM SIGGRAPH/Eurographics Symposium on Computer Animation.

Digital Library

[18]

Sorkine, O., and Cohen-Or, D. 2004. Least-squares meshes. In Shape Modeling Applications, 2004. Proceedings.

Digital Library

[19]

Southern, R., and Zhang, J. 2011. Motion-sensitive anchor identification of least-squares meshes from examples. Visualization and Computer Graphics, IEEE Transactions on.

Digital Library

[20]

Weise, T., Leibe, B., and Van Gool, L. 2008. Accurate and robust registration for in-hand modeling. In Computer Vision and Pattern Recognition.

[21]

Weise, T., Bouaziz, S., Li, H., and Pauly, M. 2011. Realtime performance-based facial animation. ACM Trans. Graph..

Digital Library

[22]

Zhang, L., Snavely, N., Curless, B., and Seitz, S. 2008. Spacetime faces: High-resolution capture for modeling and animation. In Data-Driven 3D Facial Animation.

Cited By

Racković SJakovetić DSoares C(2024)Refined Inverse Rigging: A Balanced Approach to High-fidelity Blendshape AnimationSIGGRAPH Asia 2024 Conference Papers10.1145/3680528.3687670(1-9)Online publication date: 3-Dec-2024
https://dl.acm.org/doi/10.1145/3680528.3687670
Vilchis CPerez-Guerrero CMendez-Ruiz MGonzalez-Mendoza M(2023)A survey on the pipeline evolution of facial capture and tracking for digital humansMultimedia Systems10.1007/s00530-023-01081-229:4(1917-1940)Online publication date: 1-Apr-2023
https://doi.org/10.1007/s00530-023-01081-2
Zell EMcDonnell R(2022)Compact Facial Landmark Layouts for Performance CaptureComputer Graphics Forum10.1111/cgf.1446341:2(121-133)Online publication date: 24-May-2022
https://doi.org/10.1111/cgf.14463
Show More Cited By

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MIG '15: Proceedings of the 8th ACM SIGGRAPH Conference on Motion in Games

November 2015

247 pages

ISBN:9781450339919

DOI:10.1145/2822013

Copyright © 2015 ACM.

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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SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 November 2015

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Short-paper

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MIG '15

MIG '15: Motion in Games

November 16 - 18, 2015

Paris, France

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Overall Acceptance Rate -9 of -9 submissions, 100%

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Cited By

Racković SJakovetić DSoares C(2024)Refined Inverse Rigging: A Balanced Approach to High-fidelity Blendshape AnimationSIGGRAPH Asia 2024 Conference Papers10.1145/3680528.3687670(1-9)Online publication date: 3-Dec-2024
https://dl.acm.org/doi/10.1145/3680528.3687670
Vilchis CPerez-Guerrero CMendez-Ruiz MGonzalez-Mendoza M(2023)A survey on the pipeline evolution of facial capture and tracking for digital humansMultimedia Systems10.1007/s00530-023-01081-229:4(1917-1940)Online publication date: 1-Apr-2023
https://doi.org/10.1007/s00530-023-01081-2
Zell EMcDonnell R(2022)Compact Facial Landmark Layouts for Performance CaptureComputer Graphics Forum10.1111/cgf.1446341:2(121-133)Online publication date: 24-May-2022
https://doi.org/10.1111/cgf.14463
Romeo MSchvartzman S(2020)Data‐Driven Facial SimulationComputer Graphics Forum10.1111/cgf.1408939:6(513-526)Online publication date: 8-Aug-2020
https://doi.org/10.1111/cgf.14089
Kawaler MCzyżewski A(2019)Database of speech and facial expressions recorded with optimized face motion capture settingsJournal of Intelligent Information Systems10.1007/s10844-019-00547-yOnline publication date: 21-Feb-2019
https://doi.org/10.1007/s10844-019-00547-y

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