Style Learning and Transferring for Facial Animation Editing

This demo shows a novel facial editing style learning framework that is able to learn a constraint-based Gaussian Process model from a small number of facial-editing pairs, and then it can be effectively applied to automate the editing of the remaining facial animation frames or transfer editing styles between different animation sequences. This work was done at the Computer Graphics and Interacitve Media Lab at the University of Houston (http://graphics.cs.uh.edu). For more details of this specific work, please refer to http://graphics.cs.uh.edu/publication/pub/StyleLearning_SCA_2009_preprint.pdf

Category:

Science & Technology

Tags:

• Facial Animation
• Facial Expression
• Animation Transferring
• Style Learning
• Animation Editing
• Gaussian Process
• Facial Constraints