A framework for automatic and perceptually valid facial animation generation

Facial expressions are facial movements reflecting the internal emotional states of a character or in response to social communications. Realistic facial animation should consider at least two factors: believable facial expression visual effect and valid facial movements. However, most research tends to separate these two issues. In this paper, we present a framework for generating facial animations considering both visual effect of facial expression and the dynamic factor. A facial expression mapping approach based on local geometry encoding is proposed, which encodes deformation in the 1-ring vector. This method is capable of mapping subtle facial movements without considering those shape and topological constraints. Facial expression mapping is achieved through three steps correspondence establishment, deviation transfer and movement mapping. Deviation is transferred to the conformal face space through minimizing the error function formed by the source neutral and the deformed face model related by those transformation matrices in 1-ring neighborhood. The transformation matrix in 1-ring neighborhood is independent of the face shape and mesh topology. Facial dynamics is then integrated with facial expressions for generating valid facial expressions. The dynamic factor was solved based on psychophysical methods. An application of the framework using various faces with different shapes and topological representations has been tested.