Efficient adaptive density estimation per image pixel for the task of background subtraction

Zivkovic, Zoran and Heijden van der, Ferdinand (2006) Efficient adaptive density estimation per image pixel for the task of background subtraction. Pattern Recognition Letters, 27 (7). pp. 773-780. ISSN 0167-8655

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Abstract:	We analyze the computer vision task of pixel-level background subtraction. We present recursive equations that are used to constantly update the parameters of a Gaussian mixture model and to simultaneously select the appropriate number of components for each pixel. We also present a simple non-parametric adaptive density estimation method. The two methods are compared with each other and with some previously proposed algorithms.
Item Type:	Article
Copyright:	© 2006 Elsevier
Faculty:	Electrical Engineering, Mathematics and Computer Science (EEMCS)
Research Group:	Signals and Systems (SAS)
Link to this item:	http://purl.utwente.nl/publications/57717
Official URL:	http://dx.doi.org/10.1016/j.patrec.2005.11.005
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