File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Article: A novel method for resolving vehicle occlusion in a monocular traffic-image sequence

TitleA novel method for resolving vehicle occlusion in a monocular traffic-image sequence
Authors
KeywordsComposite signature
Curvature
Monocular traffic image sequence
Occlusion
Signature decomposition
Vanishing point
Issue Date2004
PublisherIEEE. The Journal's web site is located at http://www.ewh.ieee.org/tc/its/trans.html
Citation
IEEE Transactions on Intelligent Transportation Systems, 2004, v. 5 n. 3, p. 129-141 How to Cite?
AbstractThis paper presents a novel method for resolving the occlusion of vehicles seen in a sequence of traffic images taken from a single roadside mounted camera. Its concept is built upon a previously proposed vehicle-segmentation method, which is able to extract the vehicle shape out of the background accurately without the effect of shadows and other visual artifacts. Based on the segmented shape and that the shape can be represented by a simple cubical model, we propose a two-step method: first, detect the curvature of the shape contour to generate a data set of the vehicles occluded and, second, decompose it into individual vehicle models using a vanishing point in three dimensions and the set of curvature points of the composite model. The proposed method has been tested on a number of monocular traffic-image sequences and found that it detects the presence of occlusion correctly and resolves most of the occlusion cases involving two vehicles. It only fails when the occlusion was very severe. Further analysis of vehicle dimension also shows that the average estimation accuracy for vehicle width, length, and height are 94.78%, 94.09%, and 95.44%, respectively.
Persistent Identifierhttp://hdl.handle.net/10722/44778
ISSN
2015 Impact Factor: 2.534
2015 SCImago Journal Rankings: 1.300
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorPang, CCCen_HK
dc.contributor.authorLam, WWLen_HK
dc.contributor.authorYung, NHCen_HK
dc.date.accessioned2007-10-30T06:10:01Z-
dc.date.available2007-10-30T06:10:01Z-
dc.date.issued2004en_HK
dc.identifier.citationIEEE Transactions on Intelligent Transportation Systems, 2004, v. 5 n. 3, p. 129-141en_HK
dc.identifier.issn1524-9050en_HK
dc.identifier.urihttp://hdl.handle.net/10722/44778-
dc.description.abstractThis paper presents a novel method for resolving the occlusion of vehicles seen in a sequence of traffic images taken from a single roadside mounted camera. Its concept is built upon a previously proposed vehicle-segmentation method, which is able to extract the vehicle shape out of the background accurately without the effect of shadows and other visual artifacts. Based on the segmented shape and that the shape can be represented by a simple cubical model, we propose a two-step method: first, detect the curvature of the shape contour to generate a data set of the vehicles occluded and, second, decompose it into individual vehicle models using a vanishing point in three dimensions and the set of curvature points of the composite model. The proposed method has been tested on a number of monocular traffic-image sequences and found that it detects the presence of occlusion correctly and resolves most of the occlusion cases involving two vehicles. It only fails when the occlusion was very severe. Further analysis of vehicle dimension also shows that the average estimation accuracy for vehicle width, length, and height are 94.78%, 94.09%, and 95.44%, respectively.en_HK
dc.format.extent923756 bytes-
dc.format.extent2053 bytes-
dc.format.extent3030 bytes-
dc.format.extent10863 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.format.mimetypetext/plain-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherIEEE. 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.rights©2004 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.en_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectComposite signatureen_HK
dc.subjectCurvatureen_HK
dc.subjectMonocular traffic image sequenceen_HK
dc.subjectOcclusionen_HK
dc.subjectSignature decompositionen_HK
dc.subjectVanishing pointen_HK
dc.titleA novel method for resolving vehicle occlusion in a monocular traffic-image sequenceen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1524-9050&volume=5&issue=3&spage=129&epage=141&date=2004&atitle=A+novel+method+for+resolving+vehicle+occlusion+in+a+monocular+traffic-image+sequenceen_HK
dc.identifier.emailYung, NHC:nyung@eee.hku.hken_HK
dc.identifier.authorityYung, NHC=rp00226en_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/TITS.2004.833769en_HK
dc.identifier.scopuseid_2-s2.0-4544342966en_HK
dc.identifier.hkuros102234-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-4544342966&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume5en_HK
dc.identifier.issue3en_HK
dc.identifier.spage129en_HK
dc.identifier.epage141en_HK
dc.identifier.isiWOS:000223749700001-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridPang, CCC=7201425202en_HK
dc.identifier.scopusauthoridLam, WWL=16836339900en_HK
dc.identifier.scopusauthoridYung, NHC=7003473369en_HK

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats