Geometric Modeling of 3D-Face Features and Its Applications

This paper proposes a method of geometric modeling of features extracted from 3D face and presents some of its applications. It describes a new automatic pose and expression invariant feature extraction algorithms to extract features (control points) from eyebrows, nose and lips of 3D facial data. The proposed algorithms are tested on BU-3DFE (Binghamton University 3D Facial Expression) Database where each subject has at least six expressions. Three dimensional curves are fitted on these extracted features. Through Chi-Square test it reveals that the curve fitted against each extracted feature is found to be good with 98.5% confidence level. In this paper, the proposed geometric model has been used in 3D face recognition and in regeneration of all features. It has been found that the model helps to reduce the storage space considerably and can be used as a soft biometric tool to classify the biometric images in the database so that search space in the database for identification can be reduced substantially.