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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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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

Index Terms

Optimal marker set for motion capture of dynamical facial expressions
1. Computing methodologies
  1. Computer graphics
    1. Animation

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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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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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