A Novel Pose Invariant Face Recognition Approach Using A 2D-3D Searching Strategy

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Title A Novel Pose Invariant Face Recognition Approach Using A 2D-3D Searching Strategy
Author Dahm, Nicholas; Gao, Yongsheng
Publication Title Proceedings of the 20th International Conference on Pattern Recognition (ICPR 2010)
Editor IAPR
Year Published 2010
Place of publication United States
Publisher IEEE Computer Society
Abstract Many Face Recognition techniques focus on 2D- 2D comparison or 3D-3D comparison, however few techniques explore the idea of cross-dimensional comparison. This paper presents a novel face recognition approach that implements cross-dimensional comparison to solve the issue of pose invariance. Our approach implements a Gabor representation during comparison to allow for variations in texture, illumination, expression and pose. Kernel scaling is used to reduce comparison time during the branching search, which determines the facial pose of input images. The conducted experiments prove the viability of this approach, with our larger kernel experiments returning 91.6% - 100% accuracy on a database comprised of both local data, and data from the USF HumanID 3D database.
Peer Reviewed Yes
Published Yes
Alternative URI http://dx.doi.org/10.1109/ICPR.2010.965
Copyright Statement Copyright 2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
ISBN 1051-4651
Conference name The 20th International Conference on Pattern Recognition (ICPR 2010)
Location Istanbul, Turkey
Date From 2010-08-23
Date To 2010-08-26
URI http://hdl.handle.net/10072/37187
Date Accessioned 2010-12-07
Language en_AU
Research Centre Institute for Integrated and Intelligent Systems
Faculty Faculty of Science, Environment, Engineering and Technology
Subject Computer Vision; Pattern Recognition and Data Mining
Publication Type Conference Publications (Full Written Paper - Refereed)
Publication Type Code e1

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