File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Conference Paper: A novel method for handling vehicle occlusion in visual traffic surveillance

TitleA novel method for handling vehicle occlusion in visual traffic surveillance
Authors
KeywordsModel partitioning
Model-based tracking
Occlusion
Visual traffic surveillance
Issue Date2003
PublisherS P I E - International Society for Optical Engineering. The Journal's web site is located at http://spie.org/x1848.xml
Citation
Proceedings Of Spie - The International Society For Optical Engineering, 2003, v. 5014, p. 437-447 How to Cite?
AbstractThis paper presents a novel algorithm for handling occlusion in visual traffic surveillance (VTS) by geometrically splitting the model that has been fitted onto the composite binary vehicle mask of two occluded vehicles. The proposed algorithm consists of a critical points detection step, a critical points clustering step and a model partition step using the vanishing point of the road. The critical points detection step detects the major critical points on the contour of the binary vehicle mask. The critical points clustering step selects the best critical points among the detected critical points as the reference points for the model partition. The model partition step partitions the model by exploiting the information of the vanishing point of the road and the selected critical points. The proposed algorithm was tested on a number of real traffic image sequences, and has demonstrated that it can successfully partition the model that has been fitted onto two occluded vehicles. To evaluate the accuracy, the dimensions of each individual vehicle are estimated based on the partitioned model. The estimation accuracies in vehicle width, length and height are 95.5%, 93.4% and 97.7% respectively.
Persistent Identifierhttp://hdl.handle.net/10722/46360
ISSN
2023 SCImago Journal Rankings: 0.152
References

 

DC FieldValueLanguage
dc.contributor.authorPang, CCCen_HK
dc.contributor.authorLam, WWLen_HK
dc.contributor.authorYung, NHCen_HK
dc.date.accessioned2007-10-30T06:48:09Z-
dc.date.available2007-10-30T06:48:09Z-
dc.date.issued2003en_HK
dc.identifier.citationProceedings Of Spie - The International Society For Optical Engineering, 2003, v. 5014, p. 437-447en_HK
dc.identifier.issn0277-786Xen_HK
dc.identifier.urihttp://hdl.handle.net/10722/46360-
dc.description.abstractThis paper presents a novel algorithm for handling occlusion in visual traffic surveillance (VTS) by geometrically splitting the model that has been fitted onto the composite binary vehicle mask of two occluded vehicles. The proposed algorithm consists of a critical points detection step, a critical points clustering step and a model partition step using the vanishing point of the road. The critical points detection step detects the major critical points on the contour of the binary vehicle mask. The critical points clustering step selects the best critical points among the detected critical points as the reference points for the model partition. The model partition step partitions the model by exploiting the information of the vanishing point of the road and the selected critical points. The proposed algorithm was tested on a number of real traffic image sequences, and has demonstrated that it can successfully partition the model that has been fitted onto two occluded vehicles. To evaluate the accuracy, the dimensions of each individual vehicle are estimated based on the partitioned model. The estimation accuracies in vehicle width, length and height are 95.5%, 93.4% and 97.7% respectively.en_HK
dc.format.extent376376 bytes-
dc.format.extent2053 bytes-
dc.format.extent10863 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherS P I E - International Society for Optical Engineering. The Journal's web site is located at http://spie.org/x1848.xmlen_HK
dc.relation.ispartofProceedings of SPIE - The International Society for Optical Engineeringen_HK
dc.rightsCopyright 2003 Society of Photo‑Optical Instrumentation Engineers (SPIE). One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this publication for a fee or for commercial purposes, and modification of the contents of the publication are prohibited. This article is available online at https://doi.org/10.1117/12.473096-
dc.subjectModel partitioningen_HK
dc.subjectModel-based trackingen_HK
dc.subjectOcclusionen_HK
dc.subjectVisual traffic surveillanceen_HK
dc.titleA novel method for handling vehicle occlusion in visual traffic surveillanceen_HK
dc.typeConference_Paperen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0277-786X&volume=5014&spage=437&epage=447&date=2003&atitle=A+Novel+method+for+handling+vehicle+occlusion+in+visual+traffic+surveillanceen_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.doi10.1117/12.473096en_HK
dc.identifier.scopuseid_2-s2.0-0042378500en_HK
dc.identifier.hkuros81227-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0042378500&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume5014en_HK
dc.identifier.spage437en_HK
dc.identifier.epage447en_HK
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridPang, CCC=7201425202en_HK
dc.identifier.scopusauthoridLam, WWL=16836339900en_HK
dc.identifier.scopusauthoridYung, NHC=7003473369en_HK
dc.identifier.issnl0277-786X-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats