Knowledge - Assisted Video Analysis and Object Detection

Tsechpenakis, G; Akrivas, G; Andreou, G; Stamou, G; Kollias, S

dc.contributor.author	Tsechpenakis, G	en
dc.contributor.author	Akrivas, G	en
dc.contributor.author	Andreou, G	en
dc.contributor.author	Stamou, G	en
dc.contributor.author	Kollias, S	en
dc.date.accessioned	2014-03-01T01:51:33Z
dc.date.available	2014-03-01T01:51:33Z
dc.date.issued	2002	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/26363
dc.relation.uri	http://cbim.rutgers.edu/dmdocuments/eunite_2002.pdf	en
dc.relation.uri	http://www.image.ece.ntua.gr/papers/208.pdf	en
dc.subject	Active Contour	en
dc.subject	Automatic Annotation	en
dc.subject	Knowledge Base	en
dc.subject	Object Detection	en
dc.subject	Object Localization	en
dc.subject	Object Recognition	en
dc.subject	Semantic Relations	en
dc.subject	Video Analysis	en
dc.title	Knowledge - Assisted Video Analysis and Object Detection	en
heal.type	journalArticle	en
heal.publicationDate	2002	en
heal.abstract	Intelligent video analysis is a problem of great importance for applications such as surveillance and automatic annotation. We present, in this paper, a hybrid, knowledge - based approach for object recognition in video sequences. Objects are modelled, in the signal level, through the visual descriptors defined by MPEG-7, the ISO stan- dard for description of audiovisual content and in the	en