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Article: Simultaneous motion detection and background reconstruction with a mixed-state conditional Markov random field

TitleSimultaneous motion detection and background reconstruction with a mixed-state conditional Markov random field
Authors
KeywordsComputer Vision
Hidden Markov Models
Image Processing
Image Segmentation
Nematic Liquid Crystals
Object Recognition
Photography
Restoration
Video Recording
Issue Date2008
PublisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/
Citation
Lecture Notes In Computer Science (Including Subseries Lecture Notes In Artificial Intelligence And Lecture Notes In Bioinformatics), 2008, v. 5302 LNCS PART 1, p. 113-126 How to Cite?
AbstractWe consider the problem of motion detection by background subtraction. An accurate estimation of the background is only possible if we locate the moving objects; meanwhile, a correct motion detection is achieved if we have a good available background model. This work proposes a new direction in the way such problems are considered. The main idea is to formulate this class of problem as a joint decision-estimation unique step. The goal is to exploit the way two processes interact, even if they are of a dissimilar nature (symbolic- continuous), by means of a recently introduced framework called mixed-state Markov random fields. In this paper, we will describe the theory behind such a novel statistical framework, that subsequently will allows us to formulate the specific joint problem of motion detection and background reconstruction. Experiments on real sequences and comparisons with existing methods will give a significant support to our approach. Further implications for video sequence inpainting will be also discussed. © 2008 Springer Berlin Heidelberg.
Persistent Identifierhttp://hdl.handle.net/10722/132608
ISSN
2005 Impact Factor: 0.402
2015 SCImago Journal Rankings: 0.252
References

 

DC FieldValueLanguage
dc.contributor.authorCrivelli, Ten_HK
dc.contributor.authorPiriou, Gen_HK
dc.contributor.authorBouthemy, Pen_HK
dc.contributor.authorCernuschiFrías, Ben_HK
dc.contributor.authorYao, JFen_HK
dc.date.accessioned2011-03-28T09:26:59Z-
dc.date.available2011-03-28T09:26:59Z-
dc.date.issued2008en_HK
dc.identifier.citationLecture Notes In Computer Science (Including Subseries Lecture Notes In Artificial Intelligence And Lecture Notes In Bioinformatics), 2008, v. 5302 LNCS PART 1, p. 113-126en_HK
dc.identifier.issn0302-9743en_HK
dc.identifier.urihttp://hdl.handle.net/10722/132608-
dc.description.abstractWe consider the problem of motion detection by background subtraction. An accurate estimation of the background is only possible if we locate the moving objects; meanwhile, a correct motion detection is achieved if we have a good available background model. This work proposes a new direction in the way such problems are considered. The main idea is to formulate this class of problem as a joint decision-estimation unique step. The goal is to exploit the way two processes interact, even if they are of a dissimilar nature (symbolic- continuous), by means of a recently introduced framework called mixed-state Markov random fields. In this paper, we will describe the theory behind such a novel statistical framework, that subsequently will allows us to formulate the specific joint problem of motion detection and background reconstruction. Experiments on real sequences and comparisons with existing methods will give a significant support to our approach. Further implications for video sequence inpainting will be also discussed. © 2008 Springer Berlin Heidelberg.en_HK
dc.languageengen_US
dc.publisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/en_HK
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)en_HK
dc.subjectComputer Visionen_US
dc.subjectHidden Markov Modelsen_US
dc.subjectImage Processingen_US
dc.subjectImage Segmentationen_US
dc.subjectNematic Liquid Crystalsen_US
dc.subjectObject Recognitionen_US
dc.subjectPhotographyen_US
dc.subjectRestorationen_US
dc.subjectVideo Recordingen_US
dc.titleSimultaneous motion detection and background reconstruction with a mixed-state conditional Markov random fielden_HK
dc.typeArticleen_HK
dc.identifier.emailYao, JF: jeffyao@hku.hken_HK
dc.identifier.authorityYao, JF=rp01473en_HK
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1007/978-3-540-88682-2-10en_HK
dc.identifier.scopuseid_2-s2.0-56749180635en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-56749180635&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume5302 LNCSen_HK
dc.identifier.issuePART 1en_HK
dc.identifier.spage113en_HK
dc.identifier.epage126en_HK
dc.identifier.eissn1611-3349-
dc.publisher.placeGermanyen_HK
dc.identifier.scopusauthoridCrivelli, T=25824832900en_HK
dc.identifier.scopusauthoridPiriou, G=22433503700en_HK
dc.identifier.scopusauthoridBouthemy, P=7005146506en_HK
dc.identifier.scopusauthoridCernuschiFrías, B=7003558300en_HK
dc.identifier.scopusauthoridYao, JF=7403503451en_HK

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