Estimation of occlusion and dense motion fields in a bidirectional Bayesian framework

Estimation of occlusion and dense motion fields in a bidirectional Bayesian framework

This paper presents new MRF (Markov random field) models in a bidirectional Bayesian framework for accurate motion and occlusion field estimation. With careful selection of the five free parameters required by the models, good experimental results have been obtained. The resultant computational spee...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on pattern analysis and machine intelligence 2002-05, Vol.24 (5), p.712-718
Hauptverfasser: Keng Pang Lim, Das, A., Man Nang Chong
Format: Artikel
Sprache:eng
Schlagworte:
Bayesian analysis
Bayesian methods
Bidirectional
Intelligence
Magnetorheological fluids
Mathematical models
Motion estimation
Occlusion
Pattern analysis
Resultants
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 718
container_issue 5
container_start_page 712
container_title IEEE transactions on pattern analysis and machine intelligence
container_volume 24
creator Keng Pang Lim
Das, A.
Man Nang Chong
description This paper presents new MRF (Markov random field) models in a bidirectional Bayesian framework for accurate motion and occlusion field estimation. With careful selection of the five free parameters required by the models, good experimental results have been obtained. The resultant computational speed is also 5.5 times faster compared with the conventional "iterated conditional mode" relaxation using the proposed fast bidirectional relaxation.
doi_str_mv 10.1109/34.1000246
format Article
fullrecord <record><control><sourceid>proquest_RIE</sourceid><recordid>TN_cdi_crossref_primary_10_1109_34_1000246</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>1000246</ieee_id><sourcerecordid>907961814</sourcerecordid><originalsourceid>FETCH-LOGICAL-c370t-7f3592b1b7c7d3c0e16f0b9f46eba4d19b240c4753629f9bda124e281147ef183</originalsourceid><addsrcrecordid>eNqF0U1LAzEQBuAgCtaPi1cviwcFYWsmyW6So5b6AQUv9rxksxNI3TY1aZH-e1Pbg3hQCAyZ92EOM4RcAB0CUH3HxRAopUzUB2QAmuuSV1wfkgGFmpVKMXVMTlKaUQqionxApuO08nOz8mFRBFcEa_t12n7Mois6XCQs5uE7dR77LhU-R0XrOx_RbvumLx7MBpM3mUQzx88Q38_IkTN9wvN9PSXTx_Hb6LmcvD69jO4npeWSrkrpeKVZC620suOWItSOttqJGlsjOtAtE9QKWfGaaafbzgATyBSAkOhA8VNys5u7jOFjjWnVzH2y2PdmgWGdGk2lrkGByPL6T8lUnR_I_6GUAqRiGV79grOwjnkfqVFKCC1pVWV0u0M2hpQiumYZ87rjpgHabC_WcNHsL5bx5Q57RPwBd-kXLQqPgQ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>884497055</pqid></control><display><type>article</type><title>Estimation of occlusion and dense motion fields in a bidirectional Bayesian framework</title><source>IEEE Electronic Library (IEL)</source><creator>Keng Pang Lim ; Das, A. ; Man Nang Chong</creator><creatorcontrib>Keng Pang Lim ; Das, A. ; Man Nang Chong</creatorcontrib><description>This paper presents new MRF (Markov random field) models in a bidirectional Bayesian framework for accurate motion and occlusion field estimation. With careful selection of the five free parameters required by the models, good experimental results have been obtained. The resultant computational speed is also 5.5 times faster compared with the conventional "iterated conditional mode" relaxation using the proposed fast bidirectional relaxation.</description><identifier>ISSN: 0162-8828</identifier><identifier>EISSN: 1939-3539</identifier><identifier>DOI: 10.1109/34.1000246</identifier><identifier>CODEN: ITPIDJ</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Bayesian analysis ; Bayesian methods ; Bidirectional ; Intelligence ; Magnetorheological fluids ; Mathematical models ; Motion estimation ; Occlusion ; Pattern analysis ; Resultants</subject><ispartof>IEEE transactions on pattern analysis and machine intelligence, 2002-05, Vol.24 (5), p.712-718</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2002</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c370t-7f3592b1b7c7d3c0e16f0b9f46eba4d19b240c4753629f9bda124e281147ef183</citedby><cites>FETCH-LOGICAL-c370t-7f3592b1b7c7d3c0e16f0b9f46eba4d19b240c4753629f9bda124e281147ef183</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/1000246$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/1000246$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Keng Pang Lim</creatorcontrib><creatorcontrib>Das, A.</creatorcontrib><creatorcontrib>Man Nang Chong</creatorcontrib><title>Estimation of occlusion and dense motion fields in a bidirectional Bayesian framework</title><title>IEEE transactions on pattern analysis and machine intelligence</title><addtitle>TPAMI</addtitle><description>This paper presents new MRF (Markov random field) models in a bidirectional Bayesian framework for accurate motion and occlusion field estimation. With careful selection of the five free parameters required by the models, good experimental results have been obtained. The resultant computational speed is also 5.5 times faster compared with the conventional "iterated conditional mode" relaxation using the proposed fast bidirectional relaxation.</description><subject>Bayesian analysis</subject><subject>Bayesian methods</subject><subject>Bidirectional</subject><subject>Intelligence</subject><subject>Magnetorheological fluids</subject><subject>Mathematical models</subject><subject>Motion estimation</subject><subject>Occlusion</subject><subject>Pattern analysis</subject><subject>Resultants</subject><issn>0162-8828</issn><issn>1939-3539</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2002</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNqF0U1LAzEQBuAgCtaPi1cviwcFYWsmyW6So5b6AQUv9rxksxNI3TY1aZH-e1Pbg3hQCAyZ92EOM4RcAB0CUH3HxRAopUzUB2QAmuuSV1wfkgGFmpVKMXVMTlKaUQqionxApuO08nOz8mFRBFcEa_t12n7Mois6XCQs5uE7dR77LhU-R0XrOx_RbvumLx7MBpM3mUQzx88Q38_IkTN9wvN9PSXTx_Hb6LmcvD69jO4npeWSrkrpeKVZC620suOWItSOttqJGlsjOtAtE9QKWfGaaafbzgATyBSAkOhA8VNys5u7jOFjjWnVzH2y2PdmgWGdGk2lrkGByPL6T8lUnR_I_6GUAqRiGV79grOwjnkfqVFKCC1pVWV0u0M2hpQiumYZ87rjpgHabC_WcNHsL5bx5Q57RPwBd-kXLQqPgQ</recordid><startdate>20020501</startdate><enddate>20020501</enddate><creator>Keng Pang Lim</creator><creator>Das, A.</creator><creator>Man Nang Chong</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>F28</scope><scope>FR3</scope></search><sort><creationdate>20020501</creationdate><title>Estimation of occlusion and dense motion fields in a bidirectional Bayesian framework</title><author>Keng Pang Lim ; Das, A. ; Man Nang Chong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c370t-7f3592b1b7c7d3c0e16f0b9f46eba4d19b240c4753629f9bda124e281147ef183</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2002</creationdate><topic>Bayesian analysis</topic><topic>Bayesian methods</topic><topic>Bidirectional</topic><topic>Intelligence</topic><topic>Magnetorheological fluids</topic><topic>Mathematical models</topic><topic>Motion estimation</topic><topic>Occlusion</topic><topic>Pattern analysis</topic><topic>Resultants</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Keng Pang Lim</creatorcontrib><creatorcontrib>Das, A.</creatorcontrib><creatorcontrib>Man Nang Chong</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>ANTE: Abstracts in New Technology &amp; Engineering</collection><collection>Engineering Research Database</collection><jtitle>IEEE transactions on pattern analysis and machine intelligence</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Keng Pang Lim</au><au>Das, A.</au><au>Man Nang Chong</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Estimation of occlusion and dense motion fields in a bidirectional Bayesian framework</atitle><jtitle>IEEE transactions on pattern analysis and machine intelligence</jtitle><stitle>TPAMI</stitle><date>2002-05-01</date><risdate>2002</risdate><volume>24</volume><issue>5</issue><spage>712</spage><epage>718</epage><pages>712-718</pages><issn>0162-8828</issn><eissn>1939-3539</eissn><coden>ITPIDJ</coden><abstract>This paper presents new MRF (Markov random field) models in a bidirectional Bayesian framework for accurate motion and occlusion field estimation. With careful selection of the five free parameters required by the models, good experimental results have been obtained. The resultant computational speed is also 5.5 times faster compared with the conventional "iterated conditional mode" relaxation using the proposed fast bidirectional relaxation.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/34.1000246</doi><tpages>7</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISSN: 0162-8828
ispartof IEEE transactions on pattern analysis and machine intelligence, 2002-05, Vol.24 (5), p.712-718
issn 0162-8828
1939-3539
language eng
recordid cdi_crossref_primary_10_1109_34_1000246
source IEEE Electronic Library (IEL)
subjects Bayesian analysis
Bayesian methods
Bidirectional
Intelligence
Magnetorheological fluids
Mathematical models
Motion estimation
Occlusion
Pattern analysis
Resultants
title Estimation of occlusion and dense motion fields in a bidirectional Bayesian framework
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-05T18%3A26%3A38IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Estimation%20of%20occlusion%20and%20dense%20motion%20fields%20in%20a%20bidirectional%20Bayesian%20framework&rft.jtitle=IEEE%20transactions%20on%20pattern%20analysis%20and%20machine%20intelligence&rft.au=Keng%20Pang%20Lim&rft.date=2002-05-01&rft.volume=24&rft.issue=5&rft.spage=712&rft.epage=718&rft.pages=712-718&rft.issn=0162-8828&rft.eissn=1939-3539&rft.coden=ITPIDJ&rft_id=info:doi/10.1109/34.1000246&rft_dat=%3Cproquest_RIE%3E907961814%3C/proquest_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=884497055&rft_id=info:pmid/&rft_ieee_id=1000246&rfr_iscdi=true