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Type: Conference paper
Title: A re-evaluation of mixture-of-Gaussian background modeling
Author: Wang, H.
Suter, D.
Citation: IEEE International Conference on Acoustics, Speech, and Signal Processing : proceedings March 18-23, 2005, Pennsylvania Convention Center / Marriott Hotel, Philadelphia, Pennsylvania, USA / sponsored by the Institute of Electrical and Electronics Engineers, Signal Processing Society; volume 2: pp.1017-1020
Publisher: IEEE
Publisher Place: Online
Issue Date: 2005
Series/Report no.: International Conference on Acoustics Speech and Signal Processing ICASSP
ISBN: 0780388747
ISSN: 1520-6149
Conference Name: IEEE International Conference on Acoustics, Speech and Signal Processing (30th : 2005 : Philadelphia, Pa.)
Statement of
Hanzi Wang and David Suter
Abstract: The mixture of Gaussians (MOG) has been widely used for robustly modeling complicated backgrounds, especially those with small repetitive movements (such as leaves, bushes, rotating fan, ocean waves, rain). The performance of MOG can be greatly improved by tackling several practical issues. In this paper, we quantitatively evaluate (using the Wallflower benchmarks) the performance of the MOG with and without our modifications. The experimental results show that the MOG, with our modifications, can achieve much better results - even outperforming other state-of-the-art methods.
Description: © Copyright 2005 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. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
RMID: 0020094043
DOI: 10.1109/ICASSP.2005.1415580
Appears in Collections:Computer Science publications

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