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3D Face Recognition using Log-Gabor Templates

Cook, Jamie A., Chandran, Vinod, & Fookes, Clinton B. (2006) 3D Face Recognition using Log-Gabor Templates. In British Machine Vision Conference, September 2006, Edinborugh, Scotland.

Abstract

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

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ID Code: 10914
Item Type: Conference Paper
Additional Information: The contents of this paper can be freely accessed online via the conference web page (see hypertext link). For more information, please contact the authors.
Additional URLs:
Keywords: face recognition, part face, decomposition, gabor, log, gabor, FRGC
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Image Processing (080106)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Pattern Recognition and Data Mining (080109)
Divisions: Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Past > Institutes > Information Security Institute
Copyright Owner: Copyright 2006 (please consult authors)
Deposited On: 26 Nov 2007
Last Modified: 29 Feb 2012 23:22

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