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Orthogonal-Blendshape-Based Editing System for Facial Motion Capture Data

Published: 01 November 2008 Publication History

Abstract

The authors present a novel data-driven 3D facial motion capture data editing system using automated construction of an orthogonal blendshape face model and constrained weight propagation, aiming to bridge the popular facial motion capture technique and blendshape approach. In this work, a 3D facial-motion-capture-editing problem is transformed to a blendshape-animation-editing problem. Given a collected facial motion capture data set, we construct a truncated PCA space spanned by the greatest retained eigenvectors and a corresponding blendshape face model for each anatomical region of the human face. As such, modifying blendshape weights (PCA coefficients) is equivalent to editing their corresponding motion capture sequence. In addition, a constrained weight propagation technique allows animators to balance automation and flexible controls.

Cited By

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  • (2022)Customizing blendshapes to capture facial detailsThe Journal of Supercomputing10.1007/s11227-022-04885-779:6(6347-6372)Online publication date: 3-Nov-2022
  • (2020)Intuitive facial animation editing based on a generative RNN frameworkProceedings of the ACM SIGGRAPH/Eurographics Symposium on Computer Animation10.1111/cgf.14117(1-11)Online publication date: 6-Oct-2020
  • (2019)A Robust Interactive Facial Animation Editing SystemProceedings of the 12th ACM SIGGRAPH Conference on Motion, Interaction and Games10.1145/3359566.3360076(1-10)Online publication date: 28-Oct-2019
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Published In

cover image IEEE Computer Graphics and Applications
IEEE Computer Graphics and Applications  Volume 28, Issue 6
November 2008
82 pages

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IEEE Computer Society Press

Washington, DC, United States

Publication History

Published: 01 November 2008

Author Tags

  1. Motion editing
  2. blendshape animation
  3. data-driven
  4. facial animation
  5. motion capture
  6. motion propagation

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Cited By

View all
  • (2022)Customizing blendshapes to capture facial detailsThe Journal of Supercomputing10.1007/s11227-022-04885-779:6(6347-6372)Online publication date: 3-Nov-2022
  • (2020)Intuitive facial animation editing based on a generative RNN frameworkProceedings of the ACM SIGGRAPH/Eurographics Symposium on Computer Animation10.1111/cgf.14117(1-11)Online publication date: 6-Oct-2020
  • (2019)A Robust Interactive Facial Animation Editing SystemProceedings of the 12th ACM SIGGRAPH Conference on Motion, Interaction and Games10.1145/3359566.3360076(1-10)Online publication date: 28-Oct-2019
  • (2017)Interactive facial expression editing based on spatio-temporal coherencyThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-017-1387-433:6-8(981-991)Online publication date: 1-Jun-2017
  • (2014)Controllable high-fidelity facial performance transferACM Transactions on Graphics10.1145/2601097.260121033:4(1-11)Online publication date: 27-Jul-2014
  • (2012)Spacetime expression cloning for blendshapesACM Transactions on Graphics10.1145/2159516.215951931:2(1-12)Online publication date: 30-Apr-2012
  • (2009)Interactive modeling of 3D facial expressions with hierarchical Gaussian process latent variable modelsProceedings of the 16th IEEE international conference on Image processing10.5555/1819298.1819419(2449-2452)Online publication date: 7-Nov-2009
  • (2009)Style learning and transferring for facial animation editingProceedings of the 2009 ACM SIGGRAPH/Eurographics Symposium on Computer Animation10.1145/1599470.1599486(123-132)Online publication date: 1-Aug-2009

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