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Article: Extraction of moving objects from their background based on multiple adaptive thresholds and boundary evaluation

TitleExtraction of moving objects from their background based on multiple adaptive thresholds and boundary evaluation
Authors
KeywordsBoundary evaluation
Change detection
Curvature
Edge
Foreground extraction
Thresholds
Issue Date2010
PublisherI E E E. The Journal's web site is located at http://www.ewh.ieee.org/tc/its/trans.html
Citation
Ieee Transactions On Intelligent Transportation Systems, 2010, v. 11 n. 1, p. 40-51 How to Cite?
AbstractThe extraction of moving objects from their background is a challenging task in visual surveillance. As a single threshold often fails to resolve ambiguities and correctly segment the object, in this paper, we propose a new method that uses three thresholds to accurately classify pixels as foreground or background. These thresholds are adaptively determined by considering the distributions of differences between the input and background images and are used to generate three boundary sets. These boundary sets are then merged to produce a final boundary set that represents the boundaries of the moving objects. The merging step proceeds by first identifying boundary segment pairs that are significantly inconsistent. Then, for each inconsistent boundary segment pair, its associated curvature, edge response, and shadow index are used as criteria to evaluate the probable location of the true boundary. The resulting boundary is finally refined by estimating the width of the halo-like boundary and referring to the foreground edge map. Experimental results show that the proposed method consistently performs well under different illumination conditions, including indoor, outdoor, moderate, sunny, rainy, and dim cases. By comparing with a ground truth in each case, both the classification error rate and the displacement error indicate an accurate detection, which show substantial improvement in comparison with other existing methods. © 2010 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/73778
ISSN
2015 Impact Factor: 2.534
2015 SCImago Journal Rankings: 1.300
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorWang, Len_HK
dc.contributor.authorYung, NHCen_HK
dc.date.accessioned2010-09-06T06:54:40Z-
dc.date.available2010-09-06T06:54:40Z-
dc.date.issued2010en_HK
dc.identifier.citationIeee Transactions On Intelligent Transportation Systems, 2010, v. 11 n. 1, p. 40-51en_HK
dc.identifier.issn1524-9050en_HK
dc.identifier.urihttp://hdl.handle.net/10722/73778-
dc.description.abstractThe extraction of moving objects from their background is a challenging task in visual surveillance. As a single threshold often fails to resolve ambiguities and correctly segment the object, in this paper, we propose a new method that uses three thresholds to accurately classify pixels as foreground or background. These thresholds are adaptively determined by considering the distributions of differences between the input and background images and are used to generate three boundary sets. These boundary sets are then merged to produce a final boundary set that represents the boundaries of the moving objects. The merging step proceeds by first identifying boundary segment pairs that are significantly inconsistent. Then, for each inconsistent boundary segment pair, its associated curvature, edge response, and shadow index are used as criteria to evaluate the probable location of the true boundary. The resulting boundary is finally refined by estimating the width of the halo-like boundary and referring to the foreground edge map. Experimental results show that the proposed method consistently performs well under different illumination conditions, including indoor, outdoor, moderate, sunny, rainy, and dim cases. By comparing with a ground truth in each case, both the classification error rate and the displacement error indicate an accurate detection, which show substantial improvement in comparison with other existing methods. © 2010 IEEE.en_HK
dc.languageengen_HK
dc.publisherI E E E. The Journal's web site is located at http://www.ewh.ieee.org/tc/its/trans.htmlen_HK
dc.relation.ispartofIEEE Transactions on Intelligent Transportation Systemsen_HK
dc.rightsIEEE Transactions on Intelligent Transportation Systems. Copyright © IEEE.en_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rights©2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.-
dc.subjectBoundary evaluationen_HK
dc.subjectChange detectionen_HK
dc.subjectCurvatureen_HK
dc.subjectEdgeen_HK
dc.subjectForeground extractionen_HK
dc.subjectThresholdsen_HK
dc.titleExtraction of moving objects from their background based on multiple adaptive thresholds and boundary evaluationen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1524-9050&volume=11&issue=1&spage=40&epage=51&date=2009&atitle=Extraction+of+moving+human+objects+from+their+background+based+on+multiple+thresholds+and+boundary+evaluationen_HK
dc.identifier.emailYung, NHC:nyung@eee.hku.hken_HK
dc.identifier.authorityYung, NHC=rp00226en_HK
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/TITS.2009.2026674en_HK
dc.identifier.scopuseid_2-s2.0-77649273644en_HK
dc.identifier.hkuros164697en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-77649273644&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume11en_HK
dc.identifier.issue1en_HK
dc.identifier.spage40en_HK
dc.identifier.epage51en_HK
dc.identifier.isiWOS:000275046500005-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridWang, L=7409179415en_HK
dc.identifier.scopusauthoridYung, NHC=7003473369en_HK

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