Facial expression sequence synthesis based on shape and texture fusion model

Shape and texture are two aspects in facial expression synthesis. For the requirements of synthesized shape and texture are different, it is unsuitable to use same method to synthesize shape and texture. In this paper, we propose a Statistical Shape and Radio Texture Fusion Model for facial expression sequence synthesis. In this framework, facial shape and texture had been processed separately, then they had been fused together to synthesize final result. The main contributes of this paper are: First propose statistical shape and radio texture fusion model, process shape and texture separately. Second introduce ASM model into facial shape synthesis, and construct expression model of ASM parameters. Third put forward a shape based sample select mechanism, fusion shape and texture process together. Experiment results demonstrate that the proposed model is more expressive and realistic than traditional methods, and can process batch input well.