3D face recognition with geometrically localized surface shape indexes

This paper describes a pose invariant three-dimensional (3D) face recognition method using distinctive facial features. A face has its structural components like the eyes, nose and mouth. The positions and the shapes of the facial components are very important characteristics of a face. We extract invariant facial feature points on those components using the facial geometry from a normalized face data and calculate relative features using these feature points. We also calculate a shape index on each area of facial feature point to represent curvature characteristics of facial components. We perform recognition by using weighted distance matching, Support Vector Machine (SVM) and Independent Component Analysis (ICA).