OSTD

Online Stochastic Tensor Decomposition for Background Subtraction in Multispectral Video Sequences
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Actualizado 12 mar 2021

Online Stochastic Tensor Decomposition for Background Subtraction in Multispectral Video Sequences

Highlights
* An online stochastic framework for tensor decomposition to deal with multi-dimensional and streaming data.
* And, the use of multispectral video sequences instead of standard mono/trichromatic images, enabling a better background subtraction.

Citation
If you use this code for your publications, please cite it as (Online Reference):

@inproceedings{ostd,
author = {Sobral, Andrews and Javed, Sajid and Ki Jung, Soon and Bouwmans, Thierry and Zahzah, El-hadi},
title = {Online Tensor Decomposition for Background Subtraction in Multispectral Video Sequences},
booktitle = {IEEE International Conference on Computer Vision Workshops (ICCVW)},
address = {Santiago, Chile},
year = {2015},
month = {December},
url = {https://github.com/andrewssobral/ostd}
}

Source code
hyperspectral/ - hyperspectral image sequences
hyperspectral/fet.py - foreground evaluation tool in python
STOC-RPCA/ - stochastic RPCA
OSTD.m - proposed algorithm
demo.m - demo file

License
The source code is available only for academic/research purposes (non-commercial).

Problems or Questions
If you have any problems or questions, please contact the author: Andrews Sobral (andrewssobral at gmail dot com)

Citar como

Sobral, Andrews, et al. “Online Stochastic Tensor Decomposition for Background Subtraction in Multispectral Video Sequences.” 2015 IEEE International Conference on Computer Vision Workshop (ICCVW), IEEE, 2015, doi:10.1109/iccvw.2015.125.

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Compatibilidad con la versión de MATLAB
Se creó con R2013b
Compatible con cualquier versión
Compatibilidad con las plataformas
Windows macOS Linux

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Versión Publicado Notas de la versión
0.1

Para consultar o notificar algún problema sobre este complemento de GitHub, visite el repositorio de GitHub.
Para consultar o notificar algún problema sobre este complemento de GitHub, visite el repositorio de GitHub.