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ABSTRACT
Animating 3D faces to achieve compelling realism is a challenging task in the entertainment industry. Previously proposed face transfer approaches generally require a high-quality animated source face in order to transfer its motion to new 3D faces. In this work, we present a semi-automatic technique to directly animate popularized 3D blendshape face models by mapping facial motion capture data spaces to 3D blendshape face spaces. After sparse markers on the face of a human subject are captured by motion capture systems while a video camera is simultaneously used to record his/her front face, then we carefully select a few motion capture frames and accompanying video frames as reference mocap-video pairs. Users manually tune blendshape weights to perceptually match the animated blendshape face models with reference facial images (the reference mocap-video pairs) in order to create reference mocap-weight pairs. Finally, the Radial Basis Function (RBF) regression technique is used to map any new facial motion capture frame to blendshape weights based on the reference mocap-weight pairs. Our results demonstrate that this technique is efficient to animate blendshape face models, while offering its generality and flexiblity.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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CITED BY 7
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Tanasai Sucontphunt , Zhenyao Mo , Ulrich Neumann , Zhigang Deng, Interactive 3D facial expression posing through 2D portrait manipulation, Proceedings of graphics interface 2008, May 28-30, 2008, Windsor, Ontario, Canada
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Zhigang Deng , Ulrich Neumann , J. P. Lewis , Tae-Yong Kim , Murtaza Bulut , Shrikanth Narayanan, Expressive Facial Animation Synthesis by Learning Speech Coarticulation and Expression Spaces, IEEE Transactions on Visualization and Computer Graphics, v.12 n.6, p.1523-1534, November 2006
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