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Journal of Zhejiang University SCIENCE A 2006 Vol.7 No.4 P.556-563


Data-driven facial animation based on manifold Bayesian regression

Author(s):  Wang Yu-shun, Zhuang Yue-ting, Wu Fei

Affiliation(s):  School of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China; more

Corresponding email(s):   yswang@cs.zju.edu.cn, yzhuang@cs.zju.edu.cn, wufei@cs.zju.edu.cn

Key Words:  Facial animation, Manifold, Geodesic distance, Bayesian regression

Wang Yu-shun, Zhuang Yue-ting, Wu Fei. Data-driven facial animation based on manifold Bayesian regression[J]. Journal of Zhejiang University Science A, 2006, 7(4): 556-563.

@article{title="Data-driven facial animation based on manifold Bayesian regression",
author="Wang Yu-shun, Zhuang Yue-ting, Wu Fei",
journal="Journal of Zhejiang University Science A",
publisher="Zhejiang University Press & Springer",

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%T Data-driven facial animation based on manifold Bayesian regression
%A Wang Yu-shun
%A Zhuang Yue-ting
%A Wu Fei
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%D 2006
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2006.A0556

T1 - Data-driven facial animation based on manifold Bayesian regression
A1 - Wang Yu-shun
A1 - Zhuang Yue-ting
A1 - Wu Fei
J0 - Journal of Zhejiang University Science A
VL - 7
IS - 4
SP - 556
EP - 563
%@ 1673-565X
Y1 - 2006
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.2006.A0556

Driving facial animation based on tens of tracked markers is a challenging task due to the complex topology and to the non-rigid nature of human faces. We propose a solution named manifold bayesian regression. First a novel distance metric, the geodesic manifold distance, is introduced to replace the Euclidean distance. The problem of facial animation can be formulated as a sparse warping kernels regression problem, in which the geodesic manifold distance is used for modelling the topology and discontinuities of the face models. The geodesic manifold distance can be adopted in traditional regression methods, e.g. radial basis functions without much tuning. We put facial animation into the framework of bayesian regression. Bayesian approaches provide an elegant way of dealing with noise and uncertainty. After the covariance matrix is properly modulated, Hybrid Monte Carlo is used to approximate the integration of probabilities and get deformation results. The experimental results showed that our algorithm can robustly produce facial animation with large motions and complex face models.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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