ML Anthology

Image Interpretation Using Multi-Relational Grammars

Staffan Truvé
ICCV 1990 pp. 146-155
doi:10.1109/ICCV.1990.139513 /iccv/1990/truve1990iccv-image/

Abstract

An approach to computational vision that is based on multiple levels of interpretation is presented. The step between each level is seen as taking place in three stages-parsing (in which features and groups of features in an image are given labels), interpreting (in which several interpretations are built, assuring that each feature is given at most one explanation in terms of a higher-level label), and pruning (in which some interpretations are discarded because of global constraints). The parsing and pruning steps are guided by multirelational grammars, a generalization of ordinary attribute grammars and of graph grammars. A bottom-up parsing algorithm for this class of grammars is presented, and their usefulness in image interpretation is illustrated by examples using both synthetic and real-world data.< <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

Truvé. "Image Interpretation Using Multi-Relational Grammars." IEEE/CVF International Conference on Computer Vision, 1990. doi:10.1109/ICCV.1990.139513

Markdown

[Truvé. "Image Interpretation Using Multi-Relational Grammars." IEEE/CVF International Conference on Computer Vision, 1990.](https://mlanthology.org/iccv/1990/truve1990iccv-image/) doi:10.1109/ICCV.1990.139513

BibTeX

@inproceedings{truve1990iccv-image,
  title     = {{Image Interpretation Using Multi-Relational Grammars}},
  author    = {Truvé, Staffan},
  booktitle = {IEEE/CVF International Conference on Computer Vision},
  year      = {1990},
  pages     = {146-155},
  doi       = {10.1109/ICCV.1990.139513},
  url       = {https://mlanthology.org/iccv/1990/truve1990iccv-image/}
}