ML Anthology

Spatio-Temporal Consistency and Distributivity as Qualities of Features

Michael Eckmann, Terrance E. Boult
CVPRW 2008 pp. 1-8
doi:10.1109/CVPRW.2008.4563137 /cvprw/2008/eckmann2008cvprw-spatiotemporal/

Abstract

In this work, we define two new and important qualities of features which expand upon the usual local feature information. Spatio-temporal consistency is a quality of a feature that quantifies how consistently a feature has been tracked in prior frames and how smooth its motion was over prior frames. Distributivity is a quality of a feature that quantifies physical distance (in number of pixels) from other features in the same frame.

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Cite

Text

Eckmann and Boult. "Spatio-Temporal Consistency and Distributivity as Qualities of Features." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2008. doi:10.1109/CVPRW.2008.4563137

Markdown

[Eckmann and Boult. "Spatio-Temporal Consistency and Distributivity as Qualities of Features." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2008.](https://mlanthology.org/cvprw/2008/eckmann2008cvprw-spatiotemporal/) doi:10.1109/CVPRW.2008.4563137

BibTeX

@inproceedings{eckmann2008cvprw-spatiotemporal,
  title     = {{Spatio-Temporal Consistency and Distributivity as Qualities of Features}},
  author    = {Eckmann, Michael and Boult, Terrance E.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2008},
  pages     = {1-8},
  doi       = {10.1109/CVPRW.2008.4563137},
  url       = {https://mlanthology.org/cvprw/2008/eckmann2008cvprw-spatiotemporal/}
}