ML Anthology

Wallflower: Principles and Practice of Background Maintenance

Kentaro Toyama, John Krumm, Barry Brumitt, Brian Meyers
ICCV 1999 pp. 255-261
doi:10.1109/ICCV.1999.791228 /iccv/1999/toyama1999iccv-wallflower/

Abstract

Background maintenance is a frequent element of video surveillance systems. We develop Wallflower, a three-component system for background maintenance: the pixel-level component performs Wiener filtering to make probabilistic predictions of the expected background; the region-level component fills in homogeneous regions of foreground objects; and the frame-level component detects sudden, global changes in the image and swaps in better approximations of the background. We compare our system with 8 other background subtraction algorithms. Wallflower is shown to outperform previous algorithms by handling a greater set of the difficult situations that can occur. Finally, we analyze the experimental results and propose normative principles for background maintenance.

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Cite

Text

Toyama et al. "Wallflower: Principles and Practice of Background Maintenance." IEEE/CVF International Conference on Computer Vision, 1999. doi:10.1109/ICCV.1999.791228

Markdown

[Toyama et al. "Wallflower: Principles and Practice of Background Maintenance." IEEE/CVF International Conference on Computer Vision, 1999.](https://mlanthology.org/iccv/1999/toyama1999iccv-wallflower/) doi:10.1109/ICCV.1999.791228

BibTeX

@inproceedings{toyama1999iccv-wallflower,
  title     = {{Wallflower: Principles and Practice of Background Maintenance}},
  author    = {Toyama, Kentaro and Krumm, John and Brumitt, Barry and Meyers, Brian},
  booktitle = {IEEE/CVF International Conference on Computer Vision},
  year      = {1999},
  pages     = {255-261},
  doi       = {10.1109/ICCV.1999.791228},
  url       = {https://mlanthology.org/iccv/1999/toyama1999iccv-wallflower/}
}