Task-Specific Utility in a General Bayes Net Vision System

Rimey, Raymond D.; Brown, Christopher M.

doi:10.1109/CVPR.1992.223214

Task-Specific Utility in a General Bayes Net Vision System

Raymond D. Rimey, Christopher M. Brown

CVPR 1992 pp. 142-147

doi:10.1109/CVPR.1992.223214 /cvpr/1992/rimey1992cvpr-task/

Abstract

TEA is a task-oriented computer vision system that uses Bayes nets and a maximum expected-utility decision rule to choose a sequence of task-dependent and opportunistic visual operations on the basis of their cost and (present and future) benefit. The authors discuss technical problems regarding utilities, present TEA-1's utility function (which approximates a two-step lookahead), and compare it to various simpler utility functions in experiments with real and simulated scenes.< <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

Rimey and Brown. "Task-Specific Utility in a General Bayes Net Vision System." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1992. doi:10.1109/CVPR.1992.223214

Markdown

[Rimey and Brown. "Task-Specific Utility in a General Bayes Net Vision System." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1992.](https://mlanthology.org/cvpr/1992/rimey1992cvpr-task/) doi:10.1109/CVPR.1992.223214

BibTeX

@inproceedings{rimey1992cvpr-task,
  title     = {{Task-Specific Utility in a General Bayes Net Vision System}},
  author    = {Rimey, Raymond D. and Brown, Christopher M.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1992},
  pages     = {142-147},
  doi       = {10.1109/CVPR.1992.223214},
  url       = {https://mlanthology.org/cvpr/1992/rimey1992cvpr-task/}
}