Expressive Face Animation Synthesis Based on Dynamic Mapping Method

Panrong Yin, Liyue Zhao, Lixing Huang, Jianhua Tao

Abstract: In the paper, we present a framework of speech driven face animation system with expressions. It systematically addresses audio-visual data acquisition, expressive trajectory analysis and audio-visual mapping. Based on this framework, we learn the correlation between neutral facial deformation and expressive facial deformation with Gaussian Mixture Model (GMM). A hierarchical structure is proposed to map the acoustic parameters to lip FAPs. Then the synthesized neutral FAP streams will be extended with expressive variations according to the prosody of the input speech. The quantitative evaluation of the experimental result is encouraging and the synthesized face shows a realistic quality.