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Wallflower: Principles and Practice of Background Maintenance (1999)
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BibTeX
@MISC{Toyama99wallflower:principles,
author = {Kentaro Toyama and John Krumm and et al.},
title = {Wallflower: Principles and Practice of Background Maintenance},
year = {1999}
}
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Abstract
Background maintenance is a frequent element of video surveillance systems. We develop Wallflower, a three-component system for background maintenance: the pixel-level component performs Wiener filtering to make probabilistic predictions of the expected background; the region-level component fills in homogeneous regions of foreground objects; and the frame-level component detects sudden, global changes in the image and swaps in better approximations of the background. We compare our system with 8 other background subtraction algorithms. Wallflower is shown to outperform previous algorithms by handling a greater set of the difficult situations that can occur. Finally, we analyze the experimental results and propose
Keyphrases
background maintenance three-component system video surveillance system foreground object frequent element homogeneous region global change region-level component fill background subtraction algorithm previous algorithm probabilistic prediction difficult situation experimental result expected background frame-level component detects pixel-level component performs wiener
