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

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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)
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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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Metis ID: 237970