ML Anthology

Similarity Templates for Detection and Recognition

Chris Stauffer, W. Eric L. Grimson
CVPR 2001 pp. I:221-
doi:10.1109/CVPR.2001.990479 /cvpr/2001/stauffer2001cvpr-similarity/

Abstract

This paper investigates applications of a new representation for images, the similarity template. A similarity template is a probabilistic representation of the similarity of pixels in an image patch. It has application to detection of a class of objects, because it is reasonably invariant to the color of a particular object. Further, it enables the decomposition of a class of objects into component parts over which robust statistics of color can be approximated. These regions can be used to create a factored color model that is useful for recognition. Detection results are shown on a system that learns to detect a class of objects (pedestrians) in static scenes based on examples of the object provided automatically by a tracking system. Applications of the factored color model to image indexing and anomaly detection are pursued on a database of images of pedestrians.

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Text

Stauffer and Grimson. "Similarity Templates for Detection and Recognition." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2001. doi:10.1109/CVPR.2001.990479

Markdown

[Stauffer and Grimson. "Similarity Templates for Detection and Recognition." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2001.](https://mlanthology.org/cvpr/2001/stauffer2001cvpr-similarity/) doi:10.1109/CVPR.2001.990479

BibTeX

@inproceedings{stauffer2001cvpr-similarity,
  title     = {{Similarity Templates for Detection and Recognition}},
  author    = {Stauffer, Chris and Grimson, W. Eric L.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2001},
  pages     = {I:221-},
  doi       = {10.1109/CVPR.2001.990479},
  url       = {https://mlanthology.org/cvpr/2001/stauffer2001cvpr-similarity/}
}