ML Anthology

Segmentation by Minimal Description

Trevor Darrell, Stan Sclaroff, Alex Pentland
ICCV 1990 pp. 112-116
doi:10.1109/ICCV.1990.139506 /iccv/1990/darrell1990iccv-segmentation/

Abstract

The authors formulate the segmentation task as a search for a set of descriptions which minimally encodes a scene. A novel framework for cooperative robust estimation is used to estimate descriptions that locally provide the most savings in encoding an image. A modified Hopfield-Tank networks finds the subset of these descriptions which best describes an entire scene, accounting for occlusion and transparent overlap among individual descriptions. Using a part-based 3-D shape model the authors have implemented a system that is able to successfully segment images into their constituent structure.< <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

Darrell et al. "Segmentation by Minimal Description." IEEE/CVF International Conference on Computer Vision, 1990. doi:10.1109/ICCV.1990.139506

Markdown

[Darrell et al. "Segmentation by Minimal Description." IEEE/CVF International Conference on Computer Vision, 1990.](https://mlanthology.org/iccv/1990/darrell1990iccv-segmentation/) doi:10.1109/ICCV.1990.139506

BibTeX

@inproceedings{darrell1990iccv-segmentation,
  title     = {{Segmentation by Minimal Description}},
  author    = {Darrell, Trevor and Sclaroff, Stan and Pentland, Alex},
  booktitle = {IEEE/CVF International Conference on Computer Vision},
  year      = {1990},
  pages     = {112-116},
  doi       = {10.1109/ICCV.1990.139506},
  url       = {https://mlanthology.org/iccv/1990/darrell1990iccv-segmentation/}
}