Facial expression synthesis based on motion patterns learned from face database

Facial expression is the core function in face-to-face human-computer communication. In order to improve the accuracy and variety of the synthesized facial expressions, we propose a facial expression synthesis approach based on motion patterns learned from face database. We first define a set of partial facial regions: eyebrow, eye-lid, eyeball, upper lip, bottom lip and corner lip. For each region, we use a hierarchical clustering algorithm to learn the motion patterns from the face database. Then the patterns are used for parameterized synthesis of facial expression on the target face models. The experimental results show the effectiveness of the proposed approach.