Human action annotation, modeling and analysis based on implicit user interaction

Ntalianis, KS; Doulamis, AD; Tsapatsoulis, N; Doulamis, N

dc.contributor.author	Ntalianis, KS	en
dc.contributor.author	Doulamis, AD	en
dc.contributor.author	Tsapatsoulis, N	en
dc.contributor.author	Doulamis, N	en
dc.date.accessioned	2014-03-01T01:33:36Z
dc.date.available	2014-03-01T01:33:36Z
dc.date.issued	2010	en
dc.identifier.issn	1380-7501	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/20483
dc.subject	Action modeling	en
dc.subject	Human action analysis	en
dc.subject	Human object detection	en
dc.subject	User transparent interaction	en
dc.subject	Video annotation	en
dc.subject.classification	Computer Science, Information Systems	en
dc.subject.classification	Computer Science, Software Engineering	en
dc.subject.classification	Computer Science, Theory & Methods	en
dc.subject.classification	Engineering, Electrical & Electronic	en
dc.subject.other	Action modeling	en
dc.subject.other	Content semantics	en
dc.subject.other	File servers	en
dc.subject.other	Human actions	en
dc.subject.other	Integrated frameworks	en
dc.subject.other	Modeling and analysis	en
dc.subject.other	Object Detection	en
dc.subject.other	Spatiotemporal analysis	en
dc.subject.other	User interaction	en
dc.subject.other	Video annotations	en
dc.subject.other	Video streams	en
dc.subject.other	Object recognition	en
dc.subject.other	Semantics	en
dc.subject.other	Servers	en
dc.subject.other	Video streaming	en
dc.title	Human action annotation, modeling and analysis based on implicit user interaction	en
heal.type	journalArticle	en
heal.identifier.primary	10.1007/s11042-009-0369-6	en
heal.identifier.secondary	http://dx.doi.org/10.1007/s11042-009-0369-6	en
heal.language	English	en
heal.publicationDate	2010	en
heal.abstract	This paper proposes an integrated framework for analyzing human actions in video streams. Despite most current approaches that are just based on automatic spatiotemporal analysis of sequences, the proposed method introduces the implicit user-in-the-loop concept for dynamically mining semantics and annotating video streams. This work sets a new and ambitious goal: to recognize, model and properly use ""average user's"" selections, preferences and perception, for dynamically extracting content semantics. The proposed approach is expected to add significant value to hundreds of billions of non-annotated or inadequately annotated video streams existing in the Web, file servers, databases etc. Furthermore expert annotators can gain important knowledge relevant to user preferences, selections, styles of searching and perception. © 2009 Springer Science+Business Media, LLC.	en
heal.publisher	SPRINGER	en
heal.journalName	Multimedia Tools and Applications	en
dc.identifier.doi	10.1007/s11042-009-0369-6	en
dc.identifier.isi	ISI:000279198900010	en
dc.identifier.volume	50	en
dc.identifier.issue	1	en
dc.identifier.spage	199	en
dc.identifier.epage	225	en