FACIAL ACTIONS TRACKING FOR EXPRESSION CLONING BASED ON MIXTURE EDGE APPEARANCE MODELS
Zhenghong Liu · Journal of Beijing Normal University · 2011
Facial feature tracking plays an important role in interactive entertainment,such as expression cloning.Online-learning methods such as online appearance models have achieved good results in tracking,as they have strong abilities to adapt to variations.However,most previous works use only raw intensity to build observation models,which is very sensitive to illumination and expression changes.In this paper,a real time,fully automatic facial feature tracking approach using local structure based mixture observation model is presented.A 3D parameterized model is used to model face and facial actions,a weak perspective projection method is used to model head pose.WSF Mixture Appearance Models are built from shape-free patches based on non-linear normalized edge strength.Experimental results demonstrate that edge strength measures in observation modeling and adaptive mixture learning can improve accuracy and robustness of tracking.