3D facial expression editing based on the dynamic graph model

To model a detailed 3D expressive face based on the limited user constraints is a challenge work. In this paper, we present the facial expression editing technique based on a dynamic graph model. The probabilistic relations between facial expressions and the complex combination of local facial features, as well as the temporal behaviors of facial expressions are represented by the hierarchical dynamic Bayesian network. Given limited user-constraints on the sparse feature mesh, the system can infer the basis expression probabilities, which are used to locate the corresponding expressive mesh in the shape space spanned by the basis models. The experiments demonstrate the 3D dense facial meshes corresponding to the user-constraints can be synthesized effectively.