by Zang, Q and Klette, R
Abstract:
Background subtraction is one of the main techniques to extract moving objects from background scenes. A mixture of Gaussions is a common model for background subtraction that has been used in many applications. However modelling background pixels using this model results into a low-level process at pixel level. Some of its main drawbacks are: a subtracted (moving object) region may contain holes; it can not solve partial occlusion problems, and it requires updates in cases of shadows or sudden changes in the scene. We present a multi-layered mixture of Gaussions model named PixelMap. We combine the mixture of Gaussions model with concepts defined by region level and frame level considerations. Our experimental results show that our method improved the accuracy of extracting moving objects from background. A single stationary camera has been used.
Reference:
Robust background subtraction and maintenance (Zang, Q and Klette, R), In Proceedings – International Conference on Pattern Recognition, volume 2, 2004.
Bibtex Entry:
@inproceedings{zang2004robustmaintenance,
author = "Zang, Q and Klette, R",
booktitle = "Proceedings - International Conference on Pattern Recognition",
pages = "90--93",
title = "Robust background subtraction and maintenance",
volume = "2",
year = "2004",
abstract = "Background subtraction is one of the main techniques to extract moving objects from background scenes. A mixture of Gaussions is a common model for background subtraction that has been used in many applications. However modelling background pixels using this model results into a low-level process at pixel level. Some of its main drawbacks are: a subtracted (moving object) region may contain holes; it can not solve partial occlusion problems, and it requires updates in cases of shadows or sudden changes in the scene. We present a multi-layered mixture of Gaussions model named PixelMap. We combine the mixture of Gaussions model with concepts defined by region level and frame level considerations. Our experimental results show that our method improved the accuracy of extracting moving objects from background. A single stationary camera has been used.",
doi = "10.1109/ICPR.2004.1334047",
isbn = "0769521282",
issn = "1051-4651",
language = "eng",
}