Synthesizing neutral facial expression on 3D faces using Active Shape Models

Facial expression synthesizing is a process of generating new face shapes from a given face. The earlier work on synthesizing facial expressions used 2D images. Only recently, the work has moved to using 3D face shapes due to the availability and improvement of 3D scanner acquisition technology. This paper presents a work on synthesizing neutral facial expression or neutralizing facial expression on realistic 3D face models that holds distinct facial characteristics of the subjects. We apply Active Shape Model (ASM) to these dense face shapes. This approach could be used to improve the performance of existing biometric face identification systems, or to enhance human recognition.