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Journal of Applied MathematicsVolume 2014 2014, Article ID 706159, 6 pages

Research Article

Department of Mathematics, Tianjin Polytechnic University, Tianjin 300387, China

Shengshi Interactive Game, Beijing 10010, China

Received 4 March 2014; Accepted 6 April 2014; Published 20 May 2014

Academic Editor: Li Wei

Copyright © 2014 Shuo Sun and Chunbao Ge. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Animating expressive facial animation is a very challenging topic within the graphics community. In this paper, we introduce a novel ERI expression ratio image driving framework based on SVR and MPEG-4 for automatic 3D facial expression animation. Through using the method of support vector regression SVR, the framework can learn and forecast the regression relationship between the facial animation parameters FAPs and the parameters of expression ratio image. Firstly, we build a 3D face animation system driven by FAP. Secondly, through using the method of principle component analysis PCA, we generate the parameter sets of eigen-ERI space, which will rebuild reasonable expression ratio image. Then we learn a model with the support vector regression mapping, and facial animation parameters can be synthesized quickly with the parameters of eigen-ERI. Finally, we implement our 3D face animation system driving by the result of FAP and it works effectively.

Author: Shuo Sun and Chunbao Ge

Source: https://www.hindawi.com/


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