Background Maintenance

Background Maintenance relies to the mechanism used for adapting the model to the changes occurred in the scene over time. There are three main issues:

Maintenance rules which are used to adapt the background image.
Learning rates which determine the speed of the adaptation to the scene changes.
Adaptation rates which detemine the frequency of the maintenance.

Author: Thierry BOUWMANS, Associate Professor, Lab. MIA, Univ. Rochelle, France.

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As this website gives many information that come from my research, please cite my following survey papers:

T. Bouwmans, “Traditional and Recent Approaches in Background Modeling for Foreground Detection: An Overview”, Computer Science Review, 2014. [pdf]

T. Bouwmans, E. Zahzah, “Robust PCA via Principal Component Pursuit: A Review for a Comparative Evaluation in Video Surveillance”, Special Issue on Background Models Challenge, Computer Vision and Image Understanding, CVIU 2014, Volume 122, pages 22–34, May 2014. [pdf]

T. Bouwmans, "Recent Advanced Statistical Background Modeling for Foreground Detection: A Systematic Survey", Recent Patents on Computer Science, Volume 4, No. 3, pages147-176, September 2011. [pdf]

Note: My publications are available on Academia, Research Gate, Researchr, ORCID and Publication List.