A New Method of 3D Facial Expression Animation

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.

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Realistic Facial Animation Synthesis and Transfer Based on Flexible Expression Ratio Image

Multimedia and Expo, 2007 IEEE International Conference on ◽

10.1109/icme.2007.4284873 ◽

2007 ◽

Author(s):

Pith Xie ◽

Yiqiang Chen ◽

Junfa Liu

Keyword(s):

Facial Animation ◽

Expression Ratio ◽

Ratio Image

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Automatic Facial Expression Recognition Using Facial Animation Parameters and Multistream HMMs

IEEE Transactions on Information Forensics and Security ◽

10.1109/tifs.2005.863510 ◽

2006 ◽

Vol 1 (1) ◽

pp. 3-11 ◽

Cited By ~ 131

Author(s):

P.S. Aleksic ◽

A.K. Katsaggelos

Keyword(s):

Facial Expression ◽

Facial Expression Recognition ◽

Facial Animation ◽

Expression Recognition ◽

Facial Animation Parameters

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Performance comparison of Support Vector Regression and Relevance Vector Regression for facial expression recognition

2015 International Conference on Soft Computing Techniques and Implementations (ICSCTI) ◽

10.1109/icscti.2015.7489548 ◽

2015 ◽

Cited By ~ 2

Author(s):

Gaurav Gupta ◽

Neeru Rathee

Keyword(s):

Facial Expression ◽

Support Vector Regression ◽

Facial Expression Recognition ◽

Performance Comparison ◽

Support Vector ◽

Expression Recognition ◽

Relevance Vector Regression

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Design and Implementation of 3D Facial Animation Based on MPEG-4

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.433-440.5045 ◽

2012 ◽

Vol 433-440 ◽

pp. 5045-5049

Author(s):

Jian Hua Yong ◽

Ping Guang Cheng

Keyword(s):

Implementation Process ◽

Facial Animation ◽

Face Model ◽

Design And Implementation ◽

Design Program ◽

Depth Study ◽

Implementation Method ◽

Expression Animation ◽

Generation Technology ◽

Animation System

Through the in-depth study of the MPEG-4 face model definition standard and animation-driven principles, learning from the existing generation technology of facial animation, this paper presents a 3D facial animation system design program. This program can accept driver information to generate a realistic facial expression animation and simulate the real face actions. At the same time, in the implementation process it also uses FAP frame with a mask and implementation method of FAP intermediate frame calculation, insert to reduce the amount of animation-driven data, and then improve the continuous effect of facial animation.

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Dynamic Facial Expression Analysis and Synthesis With MPEG-4 Facial Animation Parameters

IEEE Transactions on Circuits and Systems for Video Technology ◽

10.1109/tcsvt.2008.928887 ◽

2008 ◽

Vol 18 (10) ◽

pp. 1383-1396 ◽

Cited By ~ 40

Author(s):

Yongmian Zhang ◽

Qiang Ji ◽

Zhiwei Zhu ◽

Beifang Yi

Keyword(s):

Facial Expression ◽

Expression Analysis ◽

Facial Animation ◽

Facial Expression Analysis ◽

Analysis And Synthesis ◽

Facial Animation Parameters ◽

Dynamic Facial Expression

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An Improved Surface Simplification Method for Facial Expression Animation Based on Homogeneous Coordinate Transformation Matrix and Maximum Shape Operator

Mathematical Problems in Engineering ◽

10.1155/2016/2370919 ◽

2016 ◽

Vol 2016 ◽

pp. 1-14 ◽

Cited By ~ 3

Author(s):

Juin-Ling Tseng

Keyword(s):

Facial Expression ◽

Coordinate System ◽

Coordinate Transformation ◽

Local Coordinate System ◽

Facial Animation ◽

Shape Operator ◽

Transformation Matrix ◽

3D Animation ◽

Surface Simplification ◽

Expression Animation

Facial animation is one of the most popular 3D animation topics researched in recent years. However, when using facial animation, a 3D facial animation model has to be stored. This 3D facial animation model requires many triangles to accurately describe and demonstrate facial expression animation because the face often presents a number of different expressions. Consequently, the costs associated with facial animation have increased rapidly. In an effort to reduce storage costs, researchers have sought to simplify 3D animation models using techniques such as Deformation Sensitive Decimation and Feature Edge Quadric. The studies conducted have examined the problems in the homogeneity of the local coordinate system between different expression models and in the retainment of simplified model characteristics. This paper proposes a method that applies Homogeneous Coordinate Transformation Matrix to solve the problem of homogeneity of the local coordinate system and Maximum Shape Operator to detect shape changes in facial animation so as to properly preserve the features of facial expressions. Further, root mean square error and perceived quality error are used to compare the errors generated by different simplification methods in experiments. Experimental results show that, compared with Deformation Sensitive Decimation and Feature Edge Quadric, our method can not only reduce the errors caused by simplification of facial animation, but also retain more facial features.

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