Automatic facial expression recognition on a single 3d face by exploring shape deformation

Facial expression recognition has many applications in multime-dia processing and the development of 3D data acquisition tech-niques makes it possible to identify expressions using 3D shape information. In this paper, we propose an automatic facial expres-sion recognition approach based on a single 3D face. The shape of an expressional 3D face is approximated as the sum of two parts, a basic facial shape component (BFSC) and an expressional shape component (ESC). The BFSC represents the basic face structure and neutral-style shape and the ESC contains shape changes caused by facial expressions. To separate the BFSC and ESC, our method firstly builds a reference face for each input 3D non-neutral face by a learning method, which well represents the basic facial shape. Then, based on the BFSC and the original expressional face, a fa-cial expression descriptor is designed. The surface depth changes are considered in the descriptor. Finally, the descriptor is input into an SVM to recognize the expression. Unlike previous meth-ods which recognize a facial expression with the help of manually labeled key points and/or a neutral face, our method works on a sin-gle 3D face without any manual assistance. Extensive experiments are carried out on the BU-3DFE database and comparisons with existing methods are conducted. The experimental results show the effectiveness of our method