A semi-supervised framework for topology preserving performance-driven facial animation

作者：Zhang, Jian^*; Li, Na; Liang, Yun

来源：Signal Processing, 2018, 143: 171-180.

DOI：10.1016/j.sigpro.2017.09.002

• Performance-driven facial animation
• Facial expression retargeting
• Face driving
• Semi-supervised framework
• Local affine transformation

In this paper, we divide performance-driven facial animation into two data transformation problems, facial expression retargeting and face driving, and report a semi-supervised framework to solve the two problems. The objective function includes two parts. In the first part, we unify the temporal and geometrical characteristics of facial expressions and face models as topology characteristics, and preserve the topology characteristics in manifold subspace during data transformation. In the second part, some given data are used as labels to guide the transformation. The proposed semi-supervised framework can be efficiently solved by a least square method. Experimental results show that the proposed framework outperforms existing methods in both facial expression retargeting and face driving.

• 出版日期2018-2
• 单位华南农业大学; 浙江外国语学院