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Nonparametric Background Modeling Using the CONDENSATION Algorithm

9 years 16 days ago
Nonparametric Background Modeling Using the CONDENSATION Algorithm
Background modeling for dynamic scenes is an important problem in the context of real time video surveillance systems. Several nonparametric background models have been proposed to model dynamic scenes and promising results have been reported. However, a critical problem with existing nonparametric models is their high computational requirement because a large set of background samples is usually needed to model the background. In this paper, a nonparametric background model that uses an importance sampling method is proposed to overcome the problem of high computational complexity of conventional nonparametric background models. Instead of using a large number of samples to model the background probability densities, much fewer background samples are maintained and updated using the CONDENSATION algorithm. A Markov Random Field model is used to enhance the foreground detection results by imposing spatial constraints. Experimental results show that the proposed method is much faster a...
Xingzhi Luo, Suchendra M. Bhandarkar, Wei Hua, Hai
Added 10 Jun 2010
Updated 10 Jun 2010
Type Conference
Year 2006
Where AVSS
Authors Xingzhi Luo, Suchendra M. Bhandarkar, Wei Hua, Haisong Gu
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