Background subtraction is used in different applications to detect the
moving objects in the scene when the camera is static like in video surveillance, optical motion
capture and multimedia.
1. Background subtraction presents the
2. Background subtraction presents the
- Choice of the feature size: pixel, a block or a cluster.
- Choice of the feature type: color features, edge
features, stereo features, motion features and texture features.
3. Background subtraction presents the following challenges (Challenges in Background Subtraction Website)
Author: Thierry BOUWMANS, Associate Professor, Lab. MIA, Univ. Rochelle, France.
A full overview of the background subtraction methods listed in this website are provided in:
Editors: T. Bouwmans,
F. Porikli, B. Hörferlin, A. Vacavant.
Title: Handbook “Background modeling and Foreground
Detection for video surveillance: Traditional and Recent Approaches, Benchmarking and Evaluation".
Publisher :CRC Press, Taylor and Francis Group.
Publication Date : July 1, 2014. (More information) [Purchase]
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As this website gives many information that come from my research, please cite my following survey papers:
Note: My publications are available on Academia, Research Gate, Researchr, ORCID and Publication List.
“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.
T. Bouwmans, "Recent Advanced Statistical Background
Modeling for Foreground Detection: A Systematic Survey", Recent Patents on Computer Science, Volume 4, No. 3, pages147-176,