Scale-Space techniques for fiducial points extraction from 3D faces

Abstract

We propose a method for extracting fiducial points from human faces that uses 3D information only and is based on two key steps: multi-scale curvature analysis, and the reliable tracking of features in a scale-space based on curvature. Our scale-space analysis, coupled to careful use of prior information based on variability boundaries of anthropometric facial proportions, does not require a training step, because it makes direct use of morphological characteristics of the analyzed surface. The proposed method precisely identifies important fiducial points and is able to extract new fiducial points that were previously unrecognized, thus paving the way to more effective recognition algorithms.