Adaptive rule-based recognition of events in video sequences

Tzouvaras, V; Tsechpenakis, G; Stamou, G; Kollias, S

dc.contributor.author	Tzouvaras, V	en
dc.contributor.author	Tsechpenakis, G	en
dc.contributor.author	Stamou, G	en
dc.contributor.author	Kollias, S	en
dc.date.accessioned	2014-03-01T02:42:11Z
dc.date.available	2014-03-01T02:42:11Z
dc.date.issued	2003	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/30848
dc.subject	Event Recognition	en
dc.subject	Fuzzy Inference	en
dc.subject	Knowledge Base	en
dc.subject	Video Analysis	en
dc.subject	Rule Based	en
dc.subject.other	Adaptive control systems	en
dc.subject.other	Computer simulation	en
dc.subject.other	Error statistics	en
dc.subject.other	Fuzzy control	en
dc.subject.other	Inference engines	en
dc.subject.other	Mathematical operators	en
dc.subject.other	Nonlinear equations	en
dc.subject.other	Semantics	en
dc.subject.other	Compositional neuron	en
dc.subject.other	Neurofuzzy networks	en
dc.subject.other	Image analysis	en
dc.title	Adaptive rule-based recognition of events in video sequences	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/ICIP.2003.1246753	en
heal.identifier.secondary	http://dx.doi.org/10.1109/ICIP.2003.1246753	en
heal.publicationDate	2003	en
heal.abstract	Knowledge-based fuzzy inference and neural learning are used in this paper in order to model the event recognition task in semantic video analysis. The advantage of their use is the symbolic nature of the representation of the knowledge concerning the events to be recognized. Moreover, this knowledge can be adapted with the aid of data taken from video sequences. The proposed system has been tested in soccer video sequences for detecting some complex predetermined (and represented in the, form of rules) events.	en
heal.journalName	IEEE International Conference on Image Processing	en
dc.identifier.doi	10.1109/ICIP.2003.1246753	en
dc.identifier.volume	2	en
dc.identifier.spage	607	en
dc.identifier.epage	610	en