Data-driven Facial Animation via Hypergraph Learning

Data-driven facial animation has attracted much attention in recent years. Existing facial animation methods may not preserve the topology structure, and cannot achieve a natural face. This paper proposes a new data-driven facial animation method based on hypergraph learning. It drives a neutral face to a certain expression face. This paper assumes that neutral face has similar topology with the expression face, we compute the alignment laplacian matrix using hypergraph learning. To get a natural face, we add a constraint item which is consisted of a set of motion data. Experiment results demonstrate that our method can achieve a natural expression face. And the results show the superiority over the state-of-art.