Pose-Invariant 2.5D Face Recognition using Geodesic Texture Warping

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Title Pose-Invariant 2.5D Face Recognition using Geodesic Texture Warping
Author Hajati, Farshid; Raie, Abolghasem; Gao, Yongsheng
Publication Title 11th International Conference on Control, Automation, Robotics and Vision (ICARCV), 2010 Proceedings
Editor IEEE
Year Published 2010
Place of publication Singapore
Publisher IEEE
Abstract In recent years, 3D face recognition has become a popular solution to deal with the problem of pose-invariant face recognition. The majority of 3D face data are, however, actually 2.5D which are sensitive to pose variations. This paper presents a novel Geodesic Texture Warping (GTW) solution for 2.5D poseinvariant face recognition. In this method, we use the geodesic distance computed on a 2.5D face scan to warp the texture of a rotated face to that of a frontal one to perform matching. A feasibility and effectiveness investigation for the proposed method is conducted using a wide range of experiments including samples with different face rotations. The encouraging experimental results demonstrate that the proposed method achieves much higher accuracy than the state-of-the-art method with a low computational cost.
Peer Reviewed Yes
Published Yes
Alternative URI http://dx.doi.org/10.1109/ICARCV.2010.5707848
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.
Conference name The 11th International Conference on Control, Automation, Robotics and Vision (ICARCV 2010)
Location Singapore
Date From 2010-12-07
Date To 2010-12-10
URI http://hdl.handle.net/10072/38052
Date Accessioned 2011-01-31
Date Available 2011-04-19T07:03:28Z
Language en_AU
Research Centre Institute for Integrated and Intelligent Systems
Faculty Faculty of Science, Environment, Engineering and Technology
Subject Computer Vision
Publication Type Conference Publications (Full Written Paper - Refereed)
Publication Type Code e1

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