Decomposition into low-rank plus additive matrices for background/foreground separation: A review for a comparative evaluation with a large-scale dataset
- DOI
- 10.1016/j.cosrev.2016.11.001
- Published
- 2017-02
- Container
- Computer Science Review
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.cosrev.2016.11.001,
title = {Decomposition into low-rank plus additive matrices for background/foreground separation: A review for a comparative evaluation with a large-scale dataset},
author = {Thierry Bouwmans and Andrews Sobral and Sajid Javed and Soon Ki Jung and El-Hadi Zahzah},
year = {2017},
journal = {Computer Science Review},
doi = {10.1016/j.cosrev.2016.11.001},
url = {https://doi.org/10.1016/j.cosrev.2016.11.001}
}RIS
TY - JOUR TI - Decomposition into low-rank plus additive matrices for background/foreground separation: A review for a comparative evaluation with a large-scale dataset AU - Thierry Bouwmans AU - Andrews Sobral AU - Sajid Javed AU - Soon Ki Jung AU - El-Hadi Zahzah PY - 2017 JO - Computer Science Review DO - 10.1016/j.cosrev.2016.11.001 UR - https://doi.org/10.1016/j.cosrev.2016.11.001 ER -
APA
Bouwmans, T., Sobral, A., Javed, S., Jung, S. K., & Zahzah, E. (2017). Decomposition into low-rank plus additive matrices for background/foreground separation: A review for a comparative evaluation with a large-scale dataset. Computer Science Review. https://doi.org/10.1016/j.cosrev.2016.11.001
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- crossref · retrieved 2026-09-25T08:36:09.898Z