3D Face Recognition using Log-Gabor Templates
J. A. Cook, Vinod Chandran, Clinton Fookes · 2006
The use of Three Dimensional (3D) data allows new facial recognition algorithms to overcome factors such as pose and illumination variations which have plagued traditional 2D Face Recognition. In this paper a new method for providing insensitivity to expression variation in range images based on Log-Gabor Templates is presented. By decomposing a single image of a subject into 147 observations the reliance of the algorithm upon any particular part of the face is relaxed allowing high accuracy even in the presence of occulusions, distortions and facial expressions. Using the 3D database collected by University of Notre Dame for the Face Recognition Grand Challenge (FRGC), benchmarking results are presented showing superior performance of the proposed method. Comparisons showing the relative strength of the algorithm against two commercial and two academic 3D face recognition algorithms are also presented. algoritms are also presented. 1 Introduction