Publisher:
International Society of Information Fusion (ISIF)
Issued date:
2009
Citation:
Proceedings of the 12th International Conference on Information Fusion, 2009 (FUSION '09), p. 2136-2143
ISBN:
978-0-9824-4380-4
Sponsor:
This work was supported in part by Projects CICYT TIN2008-06742-C02-02/TSI, CICYT TEC2008-06732-C02-02/TEC, SINPROB, CAM MADRINET S-0505/TIC/0255 and DPS2008-07029-C02-02.
Context knowledge is essential to achieve successful information fusion, especially at high JDL levels. Context can be used to interpret the perceived situation, which is required for accurate assessment. Both types of knowledge, contextual and perceptual, canContext knowledge is essential to achieve successful information fusion, especially at high JDL levels. Context can be used to interpret the perceived situation, which is required for accurate assessment. Both types of knowledge, contextual and perceptual, can be represented with formal languages such as ontologies, which support the creation of readable representations and reasoning with them. In this paper, we present an ontology-based model compliant with JDL to represent knowledge in cognitive visual data fusion systems. We depict the use of the model with an example on surveillance. We show that such a model promotes system extensibility and facilitates the incorporation of humans in the fusion loop.[+][-]
Description:
8 pages, 4 figures.-- Contributed to: 12th International Conference on Information Fusion, 2009 (FUSION '09, Seattle, Washington, US, Jul 6-9, 2009).