ML Anthology

Parallel Structure Recognition with Uncertainty: Coupled Segmentation and Matching

Paul R. Cooper
ICCV 1990 pp. 287-290
doi:10.1109/ICCV.1990.139532 /iccv/1990/cooper1990iccv-parallel/

Abstract

A network is described that recognizes objects from uncertain image-derivable descriptions. The network handles uncertainty by making the recognition and segmentation decisions simultaneously, in a cooperative way. Both problems are posed as labeling problems, and a coupled Markov random field (MRF) is used to provide a single formal framework for both. Prior domain knowledge is represented as weights within the MRF network and interacts with the evidence to yield a labeling decision. The domain problem is the recognition of structured objects composed of simple junction and link primitives. Implementation experiments demonstrate the parallel segmentation and recognition of multiple objects in noisy ambiguous scenes with occlusion.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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Cite

Text

Cooper. "Parallel Structure Recognition with Uncertainty: Coupled Segmentation and Matching." IEEE/CVF International Conference on Computer Vision, 1990. doi:10.1109/ICCV.1990.139532

Markdown

[Cooper. "Parallel Structure Recognition with Uncertainty: Coupled Segmentation and Matching." IEEE/CVF International Conference on Computer Vision, 1990.](https://mlanthology.org/iccv/1990/cooper1990iccv-parallel/) doi:10.1109/ICCV.1990.139532

BibTeX

@inproceedings{cooper1990iccv-parallel,
  title     = {{Parallel Structure Recognition with Uncertainty: Coupled Segmentation and Matching}},
  author    = {Cooper, Paul R.},
  booktitle = {IEEE/CVF International Conference on Computer Vision},
  year      = {1990},
  pages     = {287-290},
  doi       = {10.1109/ICCV.1990.139532},
  url       = {https://mlanthology.org/iccv/1990/cooper1990iccv-parallel/}
}