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Authors: Michael Ying Yang 1 ; Wolfgang Förstner 1 and Martin Drauschke 2

Affiliations: 1 Bonn University, Germany ; 2 Bundeswehr University Munich, Germany

Keyword(s): Multi-class image classification, Hierarchical conditional random field, Image segmentation, Region adjacency graph, Region hierarchy graph.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Image and Video Analysis ; Segmentation and Grouping

Abstract: Multi-class image classification has made significant advances in recent years through the combination of local and global features. This paper proposes a novel approach called hierarchical conditional random field (HCRF) that explicitly models region adjacency graph and region hierarchy graph structure of an image. This allows to set up a joint and hierarchical model of local and global discriminative methods that augments conditional random field to a multi-layer model. Region hierarchy graph is based on a multi-scale watershed segmentation.

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Paper citation in several formats:
Ying Yang, M.; Förstner, W. and Drauschke, M. (2010). HIERARCHICAL CONDITIONAL RANDOM FIELD FOR MULTI-CLASS IMAGE CLASSIFICATION. In Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2010) - Volume 2: VISAPP; ISBN 978-989-674-029-0; ISSN 2184-4321, SciTePress, pages 464-469. DOI: 10.5220/0002877404640469

@conference{visapp10,
author={Michael {Ying Yang}. and Wolfgang Förstner. and Martin Drauschke.},
title={HIERARCHICAL CONDITIONAL RANDOM FIELD FOR MULTI-CLASS IMAGE CLASSIFICATION},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2010) - Volume 2: VISAPP},
year={2010},
pages={464-469},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002877404640469},
isbn={978-989-674-029-0},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2010) - Volume 2: VISAPP
TI - HIERARCHICAL CONDITIONAL RANDOM FIELD FOR MULTI-CLASS IMAGE CLASSIFICATION
SN - 978-989-674-029-0
IS - 2184-4321
AU - Ying Yang, M.
AU - Förstner, W.
AU - Drauschke, M.
PY - 2010
SP - 464
EP - 469
DO - 10.5220/0002877404640469
PB - SciTePress