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Conference Paper: Crowd counting and segmentation in visual surveillance

TitleCrowd counting and segmentation in visual surveillance
Authors
KeywordsBayesian method
Crowd counting
Crowd segmentation
Model based segmentation
Issue Date2009
PublisherI E E E. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000349
Citation
The 16th IEEE International Conference on Image Processing (ICIP 2009), Cairo, Egypt, 7-10 November 2009. In International Conference on Image Processing Proceedings, 2009, p. 2573-2576 How to Cite?
AbstractIn this paper, the crowd counting and segmentation problem is formulated as a maximum a posterior problem, in which 3D human shape models are designed and matched with image evidence provided by foreground/background separation and probability of boundary. The solution is obtained by considering only the human candidates that are possible to be un-occluded in each iteration, and then applying on them a validation and rejection strategy based on minimum description length. The merit of the proposed optimization procedure is that its computational cost is much smaller than that of the global optimization methods while its performance is comparable to them. The approach is shown to be robust with respect to severe partial occlusions. ©2009 IEEE.
DescriptionReference no. MP-PD.8
Persistent Identifierhttp://hdl.handle.net/10722/126209
ISSN
References

 

DC FieldValueLanguage
dc.contributor.authorWang, Len_HK
dc.contributor.authorYung, NHCen_HK
dc.date.accessioned2010-10-31T12:15:42Z-
dc.date.available2010-10-31T12:15:42Z-
dc.date.issued2009en_HK
dc.identifier.citationThe 16th IEEE International Conference on Image Processing (ICIP 2009), Cairo, Egypt, 7-10 November 2009. In International Conference on Image Processing Proceedings, 2009, p. 2573-2576en_HK
dc.identifier.issn1522-4880en_HK
dc.identifier.urihttp://hdl.handle.net/10722/126209-
dc.descriptionReference no. MP-PD.8-
dc.description.abstractIn this paper, the crowd counting and segmentation problem is formulated as a maximum a posterior problem, in which 3D human shape models are designed and matched with image evidence provided by foreground/background separation and probability of boundary. The solution is obtained by considering only the human candidates that are possible to be un-occluded in each iteration, and then applying on them a validation and rejection strategy based on minimum description length. The merit of the proposed optimization procedure is that its computational cost is much smaller than that of the global optimization methods while its performance is comparable to them. The approach is shown to be robust with respect to severe partial occlusions. ©2009 IEEE.en_HK
dc.languageengen_HK
dc.publisherI E E E. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000349en_HK
dc.relation.ispartofProceedings - International Conference on Image Processing, ICIPen_HK
dc.rightsInternational Conference on Image Processing Proceedings. Copyright © IEEE.-
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.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectBayesian methoden_HK
dc.subjectCrowd countingen_HK
dc.subjectCrowd segmentationen_HK
dc.subjectModel based segmentationen_HK
dc.titleCrowd counting and segmentation in visual surveillanceen_HK
dc.typeConference_Paperen_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/ICIP.2009.5413919en_HK
dc.identifier.scopuseid_2-s2.0-77951967656en_HK
dc.identifier.hkuros176246en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-77951967656&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.spage2573en_HK
dc.identifier.epage2576en_HK
dc.publisher.placeUnited Statesen_HK
dc.description.otherThe 16th IEEE International Conference on Image Processing (ICIP 2009), Cairo, Egypt, 7-10 November 2009. In International Conference on Image Processing Proceedings, 2009, p. 2573-2576-
dc.identifier.scopusauthoridWang, L=7409179415en_HK
dc.identifier.scopusauthoridYung, NHC=7003473369en_HK

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