A region thesaurus approach for high-level concept detection in the natural disaster domain

Spyrou, E; Avrithis, Y

dc.contributor.author	Spyrou, E	en
dc.contributor.author	Avrithis, Y	en
dc.date.accessioned	2014-03-01T02:44:24Z
dc.date.available	2014-03-01T02:44:24Z
dc.date.issued	2007	en
dc.identifier.issn	03029743	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/31804
dc.subject	Feature Detection	en
dc.subject	Hierarchical Clustering	en
dc.subject	Latent Semantic Analysis	en
dc.subject	Natural Disaster	en
dc.subject	Support Vector Machine	en
dc.subject.other	Cluster analysis	en
dc.subject.other	Image segmentation	en
dc.subject.other	Motion Picture Experts Group standards	en
dc.subject.other	Semantics	en
dc.subject.other	Vectors	en
dc.subject.other	Natural disaster domain	en
dc.subject.other	Region thesaurus approach	en
dc.subject.other	Semantic analysis	en
dc.subject.other	Feature extraction	en
dc.title	A region thesaurus approach for high-level concept detection in the natural disaster domain	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1007/978-3-540-77051-0_7	en
heal.identifier.secondary	http://dx.doi.org/10.1007/978-3-540-77051-0_7	en
heal.publicationDate	2007	en
heal.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. © Springer-Verlag Berlin Heidelberg 2007.	en
heal.journalName	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en
dc.identifier.doi	10.1007/978-3-540-77051-0_7	en
dc.identifier.volume	4816 LNCS	en
dc.identifier.spage	74	en
dc.identifier.epage	77	en