Using Adaptive Tracking to Classify and Monitor Activities in a Site

W. Eric L. Grimson, Chris Stauffer, R. Romano, L. Lee

CVPR 1998 pp. 22-29

doi:10.1109/CVPR.1998.698583 /cvpr/1998/grimson1998cvpr-using/

Abstract

We describe a vision system that monitors activity in a site over extended periods of time. The system uses a distributed set of sensors to cover the site, and an adaptive tracker detects multiple moving objects in the sensors. Our hypothesis is that motion tracking is sufficient to support a range of computations about site activities. We demonstrate using the tracked motion data to calibrate the distributed sensors, to construct rough site models, to classify detected objects, to learn common patterns of activity for different object classes, and to detect unusual activities.

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Cite

Text

Grimson et al. "Using Adaptive Tracking to Classify and Monitor Activities in a Site." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1998. doi:10.1109/CVPR.1998.698583

Markdown

[Grimson et al. "Using Adaptive Tracking to Classify and Monitor Activities in a Site." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1998.](https://mlanthology.org/cvpr/1998/grimson1998cvpr-using/) doi:10.1109/CVPR.1998.698583

BibTeX

@inproceedings{grimson1998cvpr-using,
  title     = {{Using Adaptive Tracking to Classify and Monitor Activities in a Site}},
  author    = {Grimson, W. Eric L. and Stauffer, Chris and Romano, R. and Lee, L.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1998},
  pages     = {22-29},
  doi       = {10.1109/CVPR.1998.698583},
  url       = {https://mlanthology.org/cvpr/1998/grimson1998cvpr-using/}
}