Using Local Region Semantics for Concept Detection in Video

Spyrou, E; Koumoulos, G; Avrithis, Y; Kollias, S

dc.contributor.author	Spyrou, E	en
dc.contributor.author	Koumoulos, G	en
dc.contributor.author	Avrithis, Y	en
dc.contributor.author	Kollias, S	en
dc.date.accessioned	2014-03-01T02:50:17Z
dc.date.available	2014-03-01T02:50:17Z
dc.date.issued	2006	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/35026
dc.relation.uri	http://ceur-ws.org/Vol-233/p31.pdf	en
dc.relation.uri	http://sunsite.informatik.rwth-aachen.de/Publications/CEUR-WS/Vol-233/p31.pdf	en
dc.relation.uri	http://www.informatik.uni-trier.de/~ley/db/conf/samt/samt2006p.html#SpyrouKAK06	en
dc.relation.uri	http://www.image.ece.ntua.gr/papers/453.pdf	en
dc.relation.uri	http://ftp.informatik.rwth-aachen.de/Publications/CEUR-WS/Vol-233/p31.pdf	en
dc.subject	Clustering Method	en
dc.subject	Feature Vector	en
dc.subject	Indexing Terms	en
dc.subject	Semantic Analysis	en
dc.subject	Texture Features	en
dc.title	Using Local Region Semantics for Concept Detection in Video	en
heal.type	conferenceItem	en
heal.publicationDate	2006	en
heal.abstract	This paper presents a framework for the detection of semantic features in video sequences. Low-level feature extrac- tion is performed on the keyframes of the shots 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 method.Then, a "model vector" that contains the distances	en
heal.journalName	Semantics and Digital Media Technologies	en