Learning Rules for 3D Object Recognition

Hoffman, Richard L.; Jain, Anil K.

doi:10.1109/CVPR.1988.196337

Learning Rules for 3D Object Recognition

Richard L. Hoffman, Anil K. Jain

CVPR 1988 pp. 885-892

doi:10.1109/CVPR.1988.196337 /cvpr/1988/hoffman1988cvpr-learning/

Abstract

A fully autonomous computer-vision system needs the ability to automatically learn, or discover, from training views of objects the object information (models) needed for recognition. One approach to object recognition uses an evidence rulebase composed of objects with corresponding degrees of evidence for the various objects in the databases. A technique for automatically deriving the evidence rulebase from training views of objects is presented. This generated rulebase is shown to provide successful recognition of new views of those objects.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>

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Cite

Text

Hoffman and Jain. "Learning Rules for 3D Object Recognition." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1988. doi:10.1109/CVPR.1988.196337

Markdown

[Hoffman and Jain. "Learning Rules for 3D Object Recognition." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1988.](https://mlanthology.org/cvpr/1988/hoffman1988cvpr-learning/) doi:10.1109/CVPR.1988.196337

BibTeX

@inproceedings{hoffman1988cvpr-learning,
  title     = {{Learning Rules for 3D Object Recognition}},
  author    = {Hoffman, Richard L. and Jain, Anil K.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1988},
  pages     = {885-892},
  doi       = {10.1109/CVPR.1988.196337},
  url       = {https://mlanthology.org/cvpr/1988/hoffman1988cvpr-learning/}
}