Statistical Background Modeling for Foreground Detection: A Survey

NOTE: This page presents the results of the first generation models on the Wallflower datasets. If you use it for publication, you have to cite the following paper

T. Bouwmans, F. El Baf, B. Vachon, “Statistical Background Modeling for Foreground Detection: A Survey”, Handbook of Pattern Recognition and Computer Vision, World Scientific Publishing, Volume 4, Part 2, Chapter 3, pages 181-199, January 2010.

References

[1] C. Wren, A. Azarbayejani, T. Darrell, A. Pentland, “Pfinder : Real-Time Tracking of the Human Body”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 19, No. 7, pages 780-785, July 1997.

[2] C. Stauffer, W. Grimson, “Adaptive background mixture models for real-time tracking”, Proceedings IEEE Conference on Computer Vision and Pattern Recognition, CVPR 1999, pages 246-252, 1999.

[3] A. Elgammal, D. Harwood, L. Davis, “Non-parametric Model for Background Subtraction”, 6th European Conference on Computer Vision, ECCV 2000, pages 751-767, Dublin, Ireland, June 2000.

[4] N. Oliver, B. Rosario, A. Pentland, “A Bayesian Computer Vision System for Modeling Human Interactions”, International Conference on Vision Systems, ICVS 1999, Gran Canaria, Spain, January 1999.