Complex Background Modeling and Motion Detection based on Texture Pattern Flow

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Title Complex Background Modeling and Motion Detection based on Texture Pattern Flow
Author Zhang, Baochang; Gao, Yongsheng; Zhong, Bineng
Publication Title Proceedings of the 19th International Conference on Pattern Recognition (ICPR)
Editor IAPR
Year Published 2008
Place of publication Los Alamitos, California, USA
Publisher IEEE Computer Society
Abstract This paper proposes a novel Texture Pattern Flow (TPF) for complex background modeling and motion detection. The Pattern Flow is proposed to encode the binary pattern changes among the neighborhoods in the space-time domain. To model the distribution of the TPF, the TPF integral histograms are used to extract the discriminative features to represent the input video. Experimental results on the public videos testify the effectiveness of the proposed method in comparison to LBP and GMM based background modeling methods.
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 978-1-4244-2175-6
Conference name The 19th International Conference on Pattern Recognition (ICPR)
Location Tampa, Florida, USA
Date From 2008-12-08
Date To 2008-12-11
Date Accessioned 2009-02-04
Language en_AU
Research Centre Institute for Integrated and Intelligent Systems
Faculty Faculty of Science, Environment, Engineering and Technology
Subject PRE2009-Computer Vision
Publication Type Conference Publications (Full Written Paper - Refereed)
Publication Type Code e1

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