Significant Jet Point for Facial Image Representation and Recognition

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Title Significant Jet Point for Facial Image Representation and Recognition
Author Zhao, Sanqiang; Gao, Yongsheng
Publication Title The IEEE International Conference on Image Processing (ICIP)
Editor Gang Qian (ed)
Year Published 2008
Place of publication USA
Publisher IEEE
Abstract Gabor wavelet related feature extraction and classification is an important topic in image analysis and pattern recognition. Gabor features can be used either holistically or analytically. While holistic approaches involve significant computational complexity, existing analytic approaches require explicit correspondence of predefined feature points for classification. Different from these approaches, this paper presents a new analytic Gabor method for face recognition. The proposed method attaches Gabor features on a set of shape-driven sparse points to describe both geometric and textural information. Neither the number nor the correspondence of these points is needed. A variant of Hausdorff distance is employed to recognize faces. The experiments performed on AR database demonstrated that the proposed algorithm is effective to identify individuals in various circumstances, such as under expression and illumination changes.
Peer Reviewed Yes
Published Yes
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Copyright Statement Copyright 2008 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 1-4244-1764-3
Conference name The IEEE International Conference on Image Processing (ICIP) 2008
Location San Diego, California, U.S.A
Date From 2008-10-12
Date To 2008-10-15
Date Accessioned 2008-06-18
Language en_AU
Research Centre Institute for Integrated and Intelligent Systems
Faculty Faculty of Science, Environment, Engineering and Technology
Subject PRE2009-Computer Vision; PRE2009-Pattern Recognition
Publication Type Conference Publications (Full Written Paper - Refereed)
Publication Type Code e1

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