Video-surveillance and context aware system for activity recognition

dc.creator	Kolovou, X.	en
dc.creator	Maglogiannis, I.	en
dc.date.accessioned	2015-11-23T10:35:24Z
dc.date.available	2015-11-23T10:35:24Z
dc.date.issued	2010
dc.identifier	10.1145/1839294.1839371
dc.identifier.isbn	9781450300711
dc.identifier.uri	http://hdl.handle.net/11615/29578
dc.description.abstract	Fall detection is the main issue in design an AAL system for elderly. This paper describes an algorithm for vision and audio fall detection. The main problem with video surveillance is the distinction of a fall from similar daily activities such as lying down, kneeling, standing up, walking or falling. The goal of this research is to design a reliable fall detection system which not only relies on video analysis, but also uses the information from environment of the patient to create context information. Copyright © 2010 ACM.	en
dc.source.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-77956295285&partnerID=40&md5=7646e4bc81e983480f8af61200e4c13d
dc.subject	Fall detection	en
dc.subject	Sound analysis	en
dc.subject	Video processing	en
dc.subject	Activity recognition	en
dc.subject	Context information	en
dc.subject	Context-aware systems	en
dc.subject	Daily activity	en
dc.subject	Standing-up	en
dc.subject	Video analysis	en
dc.subject	Video surveillance	en
dc.subject	Video signal processing	en
dc.subject	Security systems	en
dc.title	Video-surveillance and context aware system for activity recognition	en
dc.type	conferenceItem	en

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