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Conference Paper: Vehicle feature extraction by patch-based sampling

TitleVehicle feature extraction by patch-based sampling
Authors
KeywordsObject segmentation
Shadow detection
Texture analysis
Vehicle extraction
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. 5022 II, p. 921-932 How to Cite?
AbstractIn modern traffic surveillance, computer vision methods are often employed to detect vehicles of interest because of the rich information content contained in an image. In this paper, we propose an efficient method for extracting the boundary of vehicles free from their moving cast shadows and reflective regions. The extraction method is based on the hypothesis that regions of similar texture are less discriminative, disregarding intensity differences between the vehicle body and the cast shadow or reflection on the vehicle. In this novel algorithm, a united likelihood map that based on the relationship of texture, luminance and chrominance of each pixel is initially constructed. Subsequently, a foreground mask is constructed by applying morphological operations. Vehicles can be successfully extracted and different vehicle components can be efficiently distinguished by the related autocorrelation index within the vehicle mask.
Persistent Identifierhttp://hdl.handle.net/10722/46361
ISSN
References

 

DC FieldValueLanguage
dc.contributor.authorLam, WWLen_HK
dc.contributor.authorPang, CCCen_HK
dc.contributor.authorYung, NHCen_HK
dc.date.accessioned2007-10-30T06:48:10Z-
dc.date.available2007-10-30T06:48:10Z-
dc.date.issued2003en_HK
dc.identifier.citationProceedings Of Spie - The International Society For Optical Engineering, 2003, v. 5022 II, p. 921-932en_HK
dc.identifier.issn0277-786Xen_HK
dc.identifier.urihttp://hdl.handle.net/10722/46361-
dc.description.abstractIn modern traffic surveillance, computer vision methods are often employed to detect vehicles of interest because of the rich information content contained in an image. In this paper, we propose an efficient method for extracting the boundary of vehicles free from their moving cast shadows and reflective regions. The extraction method is based on the hypothesis that regions of similar texture are less discriminative, disregarding intensity differences between the vehicle body and the cast shadow or reflection on the vehicle. In this novel algorithm, a united likelihood map that based on the relationship of texture, luminance and chrominance of each pixel is initially constructed. Subsequently, a foreground mask is constructed by applying morphological operations. Vehicles can be successfully extracted and different vehicle components can be efficiently distinguished by the related autocorrelation index within the vehicle mask.en_HK
dc.format.extent929291 bytes-
dc.format.extent10863 bytes-
dc.format.mimetypeapplication/pdf-
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.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rightsS P I E - the International Society for Optical Proceedings. Copyright © S P I E - International Society for Optical Engineering.en_HK
dc.rightsCopyright 2003 Society of Photo-Optical Instrumentation Engineers. This paper was published in Image and Video Communications and Processing, Electronic Imaging: Science and Technology Proceedings, Santa Clara, California, USA, 21-24 January 2003, v. 5022, p. 921-932 and is made available as an electronic reprint with permission of SPIE. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.en_HK
dc.subjectObject segmentationen_HK
dc.subjectShadow detectionen_HK
dc.subjectTexture analysisen_HK
dc.subjectVehicle extractionen_HK
dc.subjectVisual traffic surveillanceen_HK
dc.titleVehicle feature extraction by patch-based samplingen_HK
dc.typeConference_Paperen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0277-786X&volume=5022&spage=921&epage=932&date=2003&atitle=Vehicle+feature+extraction+by+patch-based+samplingen_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.doi10.1117/12.476650en_HK
dc.identifier.scopuseid_2-s2.0-0042062314en_HK
dc.identifier.hkuros81230-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0042062314&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume5022 IIen_HK
dc.identifier.spage921en_HK
dc.identifier.epage932en_HK
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridLam, WWL=16836339900en_HK
dc.identifier.scopusauthoridPang, CCC=7201425202en_HK
dc.identifier.scopusauthoridYung, NHC=7003473369en_HK

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