ML Anthology

Background Modelling in Infrared and Visible Spectrum Video for People Tracking

Ciarán Ó Conaire, Eddie Cooke, Noel E. O'Connor, Noel Murphy, Alan F. Smeaton
CVPR 2005 pp. 20
doi:10.1109/CVPR.2005.419 /cvpr/2005/conaire2005cvpr-background/

Abstract

In this paper, we present our approach to robust background modelling which combines visible and thermal infrared spectrum data. Our work is based on the non-parametric background model describe in 1. We use a pedestrian detection module to prevent erroneous data from becoming part of the background model and this allows us to initialise our bacjground model, even in the presence of foreground objects. Visible and infrared features are use to remove incorrectly detected foreground regions. Allowing our model to quickly recover from ghost regions and rapid lighting changes. An object-based shadow detector also improves our algorithm's performance.

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Cite

Text

Conaire et al. "Background Modelling in Infrared and Visible Spectrum Video for People Tracking." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2005. doi:10.1109/CVPR.2005.419

Markdown

[Conaire et al. "Background Modelling in Infrared and Visible Spectrum Video for People Tracking." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2005.](https://mlanthology.org/cvpr/2005/conaire2005cvpr-background/) doi:10.1109/CVPR.2005.419

BibTeX

@inproceedings{conaire2005cvpr-background,
  title     = {{Background Modelling in Infrared and Visible Spectrum Video for People Tracking}},
  author    = {Conaire, Ciarán Ó and Cooke, Eddie and O'Connor, Noel E. and Murphy, Noel and Smeaton, Alan F.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2005},
  pages     = {20},
  doi       = {10.1109/CVPR.2005.419},
  url       = {https://mlanthology.org/cvpr/2005/conaire2005cvpr-background/}
}