Available Implementations

This part gives links to available implementions and librairies.

Note: Feel free to contact me at background.subtraction@gmail.com to add other links.

Available Implementations

Traditional Background Modeling (19 implementations)

• • Basic Background Modeling (2 implementations)

  • Statistical Background Modeling (12 implementations)

  • Background Modeling via Clustering (2 implementations)

  • Neural Network Background Modeling (3 implementations)

  • Background Estimation (0)

Recent Background Modeling (59 implementations)

• • Advanced Background Modeling (3 implementions)

  • Advanced Statistical Background Modeling (2 implementations)

  • Deep Learning Bakground Modeling (10 implementations)

  • Fuzzy Background Modeling (1 implementation)

  • Background Modeling via Subspace Tracking (1 implementation)

• Background Modeling via Robust Subspace Models (via Outliers Suppression)

  • 1. Background Modeling via RSL (1 implementation)

    2. Background Modeling via other Robust Subspace Models (0)

• Background Modeling via Robust Subspace Models (via Decomposition in Low-rank plus Additive Matrices)

  • 1. Background Modeling via RPCA (23 implementations)

    2. Background Modeling via RNMF (2 implementations)

    3. Background Modeling via RMC (2 implementations)

    4. Background Modeling via other Robust Subspace Recovery (1 implementation)

    5. Background Modeling via Subspace Tracking (5 implementations)

    6. Background Modeling via LRM (4 implementations)

• Sparse Background Modeling (2 implementations)

• Background Modeling via Robust Subspace Tensors (via Outliers Suppression)

  • 1. Background Modeling via RTSL

• Background Modeling via Robust Subspace Tensors  (via Decomposition in Low-rank plus Additive Tensors)

  • 1. Background Modeling via RPCA Tensors (1 implementation)

    2. Background Modeling via RNMF Tensors (0)

    3. Background Modeling via RTC  (0)

    4. Background Modeling via other Robust Tensor Recovery  (0)

    5. Background Modeling via LRT (0)

• Transform Domain Background Modeling (0)

• Graphs Signal Processing Background Modeling (1)

Others Background Modeling (3 implementations)

• Others Background Modeling (3 implementations)

Background Initialization (5 implementations)

Background Maintenance

Foreground Detection (3 implementations)

Available Codes

Background Modeling - Package (3 packages)

Background Modeling - Librairies (2 librairies)

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

Fair Use Policy

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.