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Authors: Thomas Reineking ; Niclas Schult and Joana Hois

Affiliation: University of Bremen, Germany

ISBN: 978-989-674-012-2

Keyword(s): Ontology, Statistics, Dempster-Shafer theory, Scene classification, Information gain, Knowledge representation, Domain analysis and modeling.

Related Ontology Subjects/Areas/Topics: AI Programming ; Artificial Intelligence ; Domain Analysis and Modeling ; Enterprise Software Technologies ; Intelligent Problem Solving ; Knowledge Engineering and Ontology Development ; Knowledge Representation ; Knowledge-Based Systems ; Software Engineering ; Symbolic Systems

Abstract: We introduce an information-driven scene classification system that combines different types of knowledge derived from a domain ontology and a statistical model in order to analyze scenes based on recognized objects. The domain ontology structures and formalizes which kind of scene classes exist and which object classes occur in them. Based on this structure, an empirical analysis of annotations from the LabelMe image database results in a statistical domain description. Both forms of knowledge are utilized for determining which object class detector to apply to the current scene according to the principle of maximum information gain. All evidence is combined in a belief-based framework that explicitly takes into account the uncertainty inherent to the statistical model and the object detection process as well as the ignorance associated with the coarse granularity of ontological constraints. Finally, we present preliminary classification performance results for scenes from the LabelM e database. (More)

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Paper citation in several formats:
Reineking T.; Schult N.; Hois J. and (2009). EVIDENTIAL COMBINATION OF ONTOLOGICAL AND STATISTICAL INFORMATION FOR ACTIVE SCENE CLASSIFICATION.In Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2009) ISBN 978-989-674-012-2, pages 72-79. DOI: 10.5220/0002304300720079

@conference{keod09,
author={Thomas Reineking and Niclas Schult and Joana Hois},
title={EVIDENTIAL COMBINATION OF ONTOLOGICAL AND STATISTICAL INFORMATION FOR ACTIVE SCENE CLASSIFICATION},
booktitle={Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2009)},
year={2009},
pages={72-79},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002304300720079},
isbn={978-989-674-012-2},
}

TY - CONF

JO - Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2009)
TI - EVIDENTIAL COMBINATION OF ONTOLOGICAL AND STATISTICAL INFORMATION FOR ACTIVE SCENE CLASSIFICATION
SN - 978-989-674-012-2
AU - Reineking, T.
AU - Schult, N.
AU - Hois, J.
PY - 2009
SP - 72
EP - 79
DO - 10.5220/0002304300720079

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