Methodology and Performance Analysis of 3-D Facial Expression Recognition Using Statistical Shape Representation
This paper presents the methodology and performance of a statistical shape representation for automatic facial expression analysis in 3-D. The core of the method uses the statistical shape modelling technique with the deformable model-based surface matching process, which is capable of simulation and interpretation of 3-D human facial expressions. Using the proposed method, a 3-D face is represented by a low-dimensional shape space vector conveying information about face shape. Since the method relies only on the 3-D shape, it is inherently invariant to changes in the background, illumination, and viewing angle, which are the difficulties often suffered in 2-D facial expression analysis.