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SAMT
2007
Springer

A Region Thesaurus Approach for High-Level Concept Detection in the Natural Disaster Domain

9 years 5 months ago
A Region Thesaurus Approach for High-Level Concept Detection in the Natural Disaster Domain
Abstract. This paper presents an approach on high-level feature detection using a region thesaurus. MPEG-7 features are locally extracted from segmented regions and for a large set of images. A hierarchical clustering approach is applied and a relatively small number of region types is selected. This set of region types defines the region thesaurus. Using this thesaurus, low-level features are mapped to high-level concepts as model vectors. This representation is then used to train support vector machine-based feature detectors. As a next step, latent semantic analysis is applied on the model vectors, to further improve the analysis performance. High-level concepts detected derive from the natural disaster domain.
Evaggelos Spyrou, Yannis S. Avrithis
Added 09 Jun 2010
Updated 09 Jun 2010
Type Conference
Year 2007
Where SAMT
Authors Evaggelos Spyrou, Yannis S. Avrithis
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