Improved Adaptive Gaussian Mixture Model for Background Subtraction

Cambridge UK August 23-August 26

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http://doi.ieeecomputersociety.org/10.1109/ICPR.2004.1333992

17th International Conference on Patt ...

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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	x
	@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}, }

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	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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