Background Subtraction

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 following steps:

2. Background subtraction presents the following issues:

  • 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.
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:
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.

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