OSTD
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)
Zitieren als
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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STOC-RPCA
Version | Veröffentlicht | Versionshinweise | |
---|---|---|---|
0.1 |