ICIP 2006, Atlanta, GA

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Atlanta Conv. & Vis. Bureau


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Paper Detail

Session:Image/Video Processing Applications: Models and Methods
Time:Wednesday, October 11, 14:20 - 17:00
Presentation: Poster
Authors: Kristof Op De Beeck; Katholieke Universiteit Leuven 
 Irene Y.H. Gu; Chalmers University of Technology 
 Liyuan Li; Institute for Infocomm Research 
 Mats Viberg; Chalmers University of Technology 
 Bart De Moor; Katholieke Universiteit Leuven 
Abstract: This paper proposes a novel region-based scheme for dynamically modeling time-evolving statistics of video background, leading to an effective segmentation of foreground moving objects for a video surveillance system. In [1] statistical-based video surveillance systems employ a Bayes decision rule for classifying foreground and background changes in individual pixels. Although principal feature representations significantly reduce the size of tables of statistics, pixel-wise maintenance remains a challenge due to the computations and memory requirement. The proposed region-based scheme, which is extension of the above method, replaces pixel-based statistics by region-based statistics through introducing dynamic background region (or pixel) merging and splitting. Simulations have been conducted to several outdoor and indoor image sequences, and results have shown a significant reduction of memory requirements for tables of statistics while maintaining relatively good quality in foreground segmented video objects.