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

Ntalianis, K; Doulamis, A; Tsapatsoulis, N; Doulamis, N

dc.contributor.author	Ntalianis, K	en
dc.contributor.author	Doulamis, A	en
dc.contributor.author	Tsapatsoulis, N	en
dc.contributor.author	Doulamis, N	en
dc.date.accessioned	2014-03-01T02:45:28Z
dc.date.available	2014-03-01T02:45:28Z
dc.date.issued	2008	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/32273
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.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	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	Management	en
dc.subject.other	Semantics	en
dc.subject.other	Servers	en
dc.subject.other	Technical presentations	en
dc.subject.other	Video streaming	en
dc.title	Human action analysis, annotation and modeling in video streams based on implicit user interaction	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1145/1463542.1463554	en
heal.identifier.secondary	http://dx.doi.org/10.1145/1463542.1463554	en
heal.publicationDate	2008	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. Copyright 2008 ACM.	en
heal.journalName	MM'08 - Proceedings of the 2008 ACM International Conference on Multimedia, with co-located Symposium and Workshops	en
dc.identifier.doi	10.1145/1463542.1463554	en
dc.identifier.spage	65	en
dc.identifier.epage	72	en