Bayesian foreground and shadow detection in uncertain frame rate surveillance videos

Benedek, Csaba and Szirányi, Tamás (2008) Bayesian foreground and shadow detection in uncertain frame rate surveillance videos. IEEE Transactions on Image Processing, 17 (4). pp. 608-621.

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In in this paper we propose a new model regarding foreground and shadow detection in video sequences. The model works without detailed a-priori object-shape information, and it is also appropriate for low and unstable frame rate video sources. Contribution is presented in three key issues: (1) we propose a novel adaptive shadow model, and show the improvements versus previous approaches in scenes with difficult lighting and coloring effects. (2)We give a novel description for the foreground based on spatial statistics of the neighboring pixel values, which enhances the detection of background or shadow-colored object parts. (3) We show how microstructure analysis can be used in the proposed framework as additional feature components improving the results. Finally, a Markov Random Field model is used to enhance the accuracy of the separation. We validate our method on outdoor and indoor sequences including real surveillance videos and well-known benchmark test sets.

Item Type: ISI Article
Subjects: Q Science > QA Mathematics and Computer Science > QA75 Electronic computers. Computer science / számítástechnika, számítógéptudomány
Divisions: Distributed Events Analysis Research Laboratory
Depositing User: Eszter Nagy
Date Deposited: 11 Dec 2012 15:29
Last Modified: 17 Feb 2014 12:12

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