The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
ViBE: A powerful random technique to estimate the background in video sequences
Open accessAbstract
Background subtraction is a crucial step in many automatic video content analysis applications. While numerous acceptable techniques have been proposed so far for background extraction, there is still a need to produce more efficient algorithms in terms of adaptability to multiple environments, noise resilience, and computation efficiency. In this paper, we present a powerful method for background extraction that improves in accuracy and reduces the computational load. The main innovation concerns the use of a random policy to select values to build a samples-based estimation of the background. To our knowledge, it is the first time that a random aggregation is used in the field of background extraction. In addition we propose a novel policy that propagates information between neighboring pixels of an image. Experiment detailed in this paper show how our method improves on other widely used techniques, and how it outperforms these techniques for noisy images.
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Citations
Cites
Learning patterns of activity using real-time tracking
Stauffer, C., & Grimson, W. E. L. (2000) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.868677 · Cited by 3,248
Non-parametric Model for Background Subtraction
Elgammal, A., Harwood, D., & Davis, L. (2000) · Lecture Notes in Computer Science · doi:10.1007/3-540-45053-x_48 · Cited by 2,118
Background subtraction techniques: a review
Piccardi, M. (2005) · 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583) · doi:10.1109/icsmc.2004.1400815 · Cited by 2,083
Improved adaptive Gaussian mixture model for background subtraction
Zivkovic, Z. (2004) · Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004. · doi:10.1109/icpr.2004.1333992 · Cited by 1,951
Image change detection algorithms: a systematic survey
Radke, R. J., Andra, S., Al-Kofahi, O., & Roysam, B. (2005) · IEEE Transactions on Image Processing · doi:10.1109/tip.2004.838698 · Cited by 1,869
Improved Adaptive Gaussian Mixture Model for Background Subtraction
Živković, Z. (2004) · Cited by 1,671
Efficient adaptive density estimation per image pixel for the task of background subtraction
Zivkovic, Z., & van der Heijden, F. (2006) · Pattern Recognition Letters · doi:10.1016/j.patrec.2005.11.005 · Cited by 1,557
A consensus-based method for tracking: Modelling background scenario and foreground appearance
Wang, H., & Suter, D. (2007) · Pattern Recognition · doi:10.1016/j.patcog.2006.05.024 · Cited by 163
Cited by
Traditional and recent approaches in background modeling for foreground detection: An overview
Bouwmans, T. (2014) · Computer Science Review · doi:10.1016/j.cosrev.2014.04.001 · Cited by 676
Evaluation of background subtraction techniques for video surveillance
Brutzer, S., Hoferlin, B., & Heidemann, G. (2011) · CVPR 2011 · doi:10.1109/cvpr.2011.5995508 · Cited by 622
Background subtraction in real applications: Challenges, current models and future directions
Garcia-Garcia, B., Bouwmans, T., & Rosales Silva, A. J. (2020) · Computer Science Review · doi:10.1016/j.cosrev.2019.100204 · Cited by 337
NIC: A Robust Background Extraction Algorithm for Foreground Detection in Dynamic Scenes
Huynh-The, T., Banos, O., Lee, S., Kang, B. H., Kim, E.-S., & Le-Tien, T. (2017) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2016.2543118 · Cited by 51
Metadata
- Authors
- Barnich, O., & Van Droogenbroeck, M.
- Venue
- 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
- Publisher
- IEEE
- Published
- 2009-04
- Pages
- 945-948
- ISSN
- 1520-6149 (ISSN-L)
- OpenAlex
- W2115352131
- Cited by
- 417
- References
- 8
- FWCI
- 8.72
- Type
- conference paper
- Language
- en
- Open access
- green
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- Barnich, O., & Van Droogenbroeck, M. (2009). ViBE: A powerful random technique to estimate the background in video sequences. 2009 IEEE International Conference on Acoustics, Speech and Signal Processing. https://doi.org/10.1109/icassp.2009.4959741
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