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17th International Conference on Pattern Recognition (ICPR'04) - Volume 2
Improved Adaptive Gaussian Mixture Model for Background Subtraction
Cambridge UK
August 23-August 26
ISBN: 0-7695-2128-2
ASCII Text
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Zoran Zivkovic, "Improved Adaptive Gaussian Mixture Model for Background Subtraction," Pattern Recognition, International Conference on, vol. 2, pp. 28-31, 17th International Conference on Pattern Recognition (ICPR'04) - Volume 2, 2004.
 
 
BibTex
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@article{ 10.1109/ICPR.2004.1333992,
author = {Zoran Zivkovic},
title = {Improved Adaptive Gaussian Mixture Model for Background Subtraction},
journal ={Pattern Recognition, International Conference on},
volume = {2},
year = {2004},
issn = {1051-4651},
pages = {28-31},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICPR.2004.1333992},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Pattern Recognition, International Conference on
TI - Improved Adaptive Gaussian Mixture Model for Background Subtraction
SN - 1051-4651
SP28
EP31
A1 - Zoran Zivkovic,
PY - 2004
KW - null
VL - 2
JA - Pattern Recognition, International Conference on
ER -
 
Zoran Zivkovic, University of Amsterdam, The Netherlands
Background subtraction is a common computer vision task. We analyze the usual pixel-level approach. We develop an efficient adaptive algorithm using Gaussian mixture probability density. Recursive equations are used to constantly update the parameters and but also to simultaneously select the appropriate number of components for each pixel.
Citation:
Zoran Zivkovic, "Improved Adaptive Gaussian Mixture Model for Background Subtraction," icpr, vol. 2, pp.28-31, 17th International Conference on Pattern Recognition (ICPR'04) - Volume 2, 2004
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