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Error Analysis of Background Adaption

10 years 2 months ago
Error Analysis of Background Adaption
Background modeling is a common component in video surveillance systems and is used to quickly identify regions of interest. To increase the robustness of background subtraction techniques, researchers have developed techniques to update the background model and also developed probabilistic/statistical approaches for thresholding the difference. This paper presents an error analysis of this type of background modeling and pixel labeling, providing both theoretical analysis and experimental validation. Evaluation is centered around the tradeoff of probability of false alarm and probability of miss detection, and this paper shows how to efficiently compute these probabilities from simpler values that are more easily measured. It includes an analysis for both static and dynamic background modeling. The paper also examines the assumptions of Gaussian and mixture of Gaussian models for a pixel.
Xiang Gao, Terrance E. Boult, Frans Coetzee, Visva
Added 30 Jul 2010
Updated 30 Jul 2010
Type Conference
Year 2000
Where CVPR
Authors Xiang Gao, Terrance E. Boult, Frans Coetzee, Visvanathan Ramesh
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