Automatic threshold selection for automated visual surveillance

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dc.contributor.authorÇelik, T
dc.contributor.authorKabakli, T
dc.contributor.authorUyguroglu, M
dc.contributor.authorÖzkaramanli, H
dc.contributor.authorDemirel, H
dc.date.accessioned2026-02-06T18:28:45Z
dc.date.issued2004
dc.departmentDoğu Akdeniz Üniversitesi
dc.descriptionIEEE 12th Signal Processing and Communications Applications Conference -- APR 28-30, 2004 -- Kusadasi, TURKEY
dc.description.abstractAutomated Visual surveillance systems mostly depend upon effective background subtraction technique. Most of the background subtraction techniques mainly suffer from parameter updates for threshold selection. Here a new threshold selection technique which is found while system trains to learn background, is proposed.
dc.description.sponsorshipIEEE,Tubitak,Istanbul Teknik Univ,Aselsan,Profile Telre,TURCom,Sgi,Datacore,Divit
dc.identifier.doi10.1109/SIU.2004.1338568
dc.identifier.endpage480
dc.identifier.isbn0-7803-8318-4
dc.identifier.orcid0000-0001-6925-6010
dc.identifier.scopus2-s2.0-18844412447
dc.identifier.scopusqualityN/A
dc.identifier.startpage478
dc.identifier.urihttps://doi.org/10.1109/SIU.2004.1338568
dc.identifier.urihttps://hdl.handle.net/11129/11089
dc.identifier.wosWOS:000225861200123
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherIEEE
dc.relation.ispartofProceedings of the Ieee 12Th Signal Processing and Communications Applications Conference
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WoS_20260204
dc.titleAutomatic threshold selection for automated visual surveillance
dc.typeConference Object

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