A background subtraction algorithm for detecting and tracking vehicles

Mandellos, NA; Keramitsoglou, I; Kiranoudis, CT

dc.contributor.author	Mandellos, NA	en
dc.contributor.author	Keramitsoglou, I	en
dc.contributor.author	Kiranoudis, CT	en
dc.date.accessioned	2014-03-01T01:34:51Z
dc.date.available	2014-03-01T01:34:51Z
dc.date.issued	2011	en
dc.identifier.issn	0957-4174	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/20899
dc.subject	Background maintenance	en
dc.subject	Background reconstruction	en
dc.subject	Background subtraction	en
dc.subject	Background update	en
dc.subject	Computer vision	en
dc.subject	Tracking	en
dc.subject	Traffic surveillance	en
dc.subject	Vehicle detection	en
dc.subject.classification	Computer Science, Artificial Intelligence	en
dc.subject.classification	Engineering, Electrical & Electronic	en
dc.subject.classification	Operations Research & Management Science	en
dc.subject.other	Background maintenance	en
dc.subject.other	Background reconstruction	en
dc.subject.other	Background subtraction	en
dc.subject.other	Background update	en
dc.subject.other	Tracking	en
dc.subject.other	Traffic surveillance	en
dc.subject.other	Vehicle detection	en
dc.subject.other	Algorithms	en
dc.subject.other	Image segmentation	en
dc.subject.other	Maintenance	en
dc.subject.other	Monitoring	en
dc.subject.other	Motor transportation	en
dc.subject.other	Traffic congestion	en
dc.subject.other	Vehicles	en
dc.subject.other	Computer vision	en
dc.title	A background subtraction algorithm for detecting and tracking vehicles	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.eswa.2010.07.083	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.eswa.2010.07.083	en
heal.language	English	en
heal.publicationDate	2011	en
heal.abstract	An innovative system for detecting and extracting vehicles in traffic surveillance scenes is presented. This system involves locating moving objects present in complex road scenes by implementing an advanced background subtraction methodology. The innovation concerns a histogram-based filtering procedure, which collects scatter background information carried in a series of frames, at pixel level, generating reliable instances of the actual background. The proposed algorithm reconstructs a background instance on demand under any traffic conditions. The background reconstruction algorithm demonstrated a rather robust performance in various operating conditions including unstable lighting, different view-angles and congestion. (C) 2010 Elsevier Ltd. All rights reserved.	en
heal.publisher	PERGAMON-ELSEVIER SCIENCE LTD	en
heal.journalName	Expert Systems with Applications	en
dc.identifier.doi	10.1016/j.eswa.2010.07.083	en
dc.identifier.isi	ISI:000284863200039	en
dc.identifier.volume	38	en
dc.identifier.issue	3	en
dc.identifier.spage	1619	en
dc.identifier.epage	1631	en