scholarly journals Realistic 3D facial animation parameters from mirror-reflected multi-view video

2002 ◽  
Author(s):  
I-Chen Lin ◽  
Jeng-Sheng Yeh ◽  
Ming Ouhyoung
Keyword(s):  
Facial Animation ◽  
Facial Animation Parameters

scholarly journals A New Method of 3D Facial Expression Animation

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Shuo Sun ◽  
Chunbao Ge
Keyword(s):  
Facial Expression ◽  
Support Vector Regression ◽  
Facial Animation ◽  
Support Vector ◽  
Expression Ratio ◽  
Face Animation ◽  
Ratio Image ◽  
Facial Animation Parameters ◽  
Expression Animation ◽  
Animation System

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.

Facial Feature Tracking via Evolutionary Multiobjective Optimization

2012 ◽  
pp. 57-71
Author(s):  
Eric C. Larson ◽  
Gary G. Yen
Keyword(s):  
Feature Tracking ◽  
Computational Experiment ◽  
Signal To Noise Ratio ◽  
Facial Animation ◽  
Facial Feature ◽  
Low Bit Rate ◽  
Facial Feature Tracking ◽  
Rate Coding ◽  
Facial Animation Parameters ◽  
Efficiency And Reliability

Facial feature tracking for model–based coding has evolved over the past decades. Of particular interest is its application in very low bit rate coding in which optimization is used to analyze head and shoulder sequences. We present the results of a computational experiment in which we apply a combination of non-dominated sorting genetic algorithm and a deterministic search to find optimal facial animation parameters at many bandwidths simultaneously. As objective functions are concerned, peak signal-to-noise ratio is maximized while the total number of facial animation parameters is minimized. Particularly, the algorithm is tested for efficiency and reliability. The results show that the overall methodology works effectively, but that a better error assessment function is needed for future study.

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