High-Level Concept Detection in Video Using a Region Thesaurus

Spyrou, E; Avrithis, Y

dc.contributor.author	Spyrou, E	en
dc.contributor.author	Avrithis, Y	en
dc.date.accessioned	2014-03-01T01:56:00Z
dc.date.available	2014-03-01T01:56:00Z
dc.date.issued	2007	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/27913
dc.relation.uri	http://www.informatik.uni-trier.de/~ley/db/series/faia/faia160.html#SpyrouA07	en
dc.relation.uri	http://www.image.ece.ntua.gr/papers/498.pdf	en
dc.subject	Clustering Method	en
dc.subject	Feature Detection	en
dc.subject	Feature Extraction	en
dc.subject	Feature Vector	en
dc.subject	Latent Semantic Analysis	en
dc.subject	Texture Features	en
dc.title	High-Level Concept Detection in Video Using a Region Thesaurus	en
heal.type	journalArticle	en
heal.publicationDate	2007	en
heal.abstract	This work presents an approach on high-level semantic feature detec- tion in video sequences. Keyframes are selected to represent the visual content of the shots. Then, low-level feature extraction is performed on the keyframes and a feature vector including color and texture features is formed. A region thesaurus that contains all the high-level features is constructed using a subtractive clustering	en