Principal Components of Expressive Speech Animation

In this paper, we describe a new technique for expressive and realistic speech animation. We use an optical tracking system that extracts the 3D positions of markers attached at the feature point locations to capture the movements of the face of a talking person. We use the feature points as defined by the MPEG-4 standard. We then form a vector space representation by using the Principal Component Analysis of this data. We call this space “expression and viseme space”. Such a representation not only offers insight into improving realism of animated faces, but also gives a new way of generating convincing speech animation and blending between several expressions. As the rigid body movements and deformation constraints on the facial movements have been considered through this analysis, the resulting facial animation is very realistic.