Study of parameterizations for the rigid body transformations of the scan registration problem
The iterative closest point (ICP) algorithm is the de facto standard for geometric alignment of three-dimensional models when an initial relative pose estimate is available. The basis of the algorithm is the minimization of an error function that takes point correspondences into account. Four closed...
Gespeichert in:
Veröffentlicht in: | Computer vision and image understanding 2010-08, Vol.114 (8), p.963-980 |
---|---|
Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 980 |
---|---|
container_issue | 8 |
container_start_page | 963 |
container_title | Computer vision and image understanding |
container_volume | 114 |
creator | Nüchter, Andreas Elseberg, Jan Schneider, Peter Paulus, Dietrich |
description | The iterative closest point (ICP) algorithm is the de facto standard for geometric alignment of three-dimensional models when an initial relative pose estimate is available. The basis of the algorithm is the minimization of an error function that takes point correspondences into account. Four closed-form solution methods are known for minimizing this function. This paper presents novel linear solutions to the scan registration problem, i.e., to the problem of putting and aligning 3D scans in a common coordinate system. We extend the methods for registering
n-scans in a global and simultaneous fashion, such that the registration of the
nth scan influences all previous registrations in
one step. |
doi_str_mv | 10.1016/j.cviu.2010.03.007 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_753684565</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S107731421000072X</els_id><sourcerecordid>753684565</sourcerecordid><originalsourceid>FETCH-LOGICAL-c362t-3b51ef92acc58c7a53817febb4948c7f9f28bd0ffaebc66d71674c1828dfaca73</originalsourceid><addsrcrecordid>eNp9kE1LxDAQhoMouK7-AU-5iKfWfLRNC15k8QsWPKjgyZCmkzVL26xJu7D-elN28egpyeR5Z5gHoUtKUkpocbNO9daOKSOxQHhKiDhCM0oqkjCefxxPdyESTjN2is5CWBNCaVbRGfp8HcZmh53BG-VVBwN4-6MG6_qAjfN4-ALs7co2uHaRG7zqQ6x3ByTmJiJo1WMPKxsiMP3gjXd1C905OjGqDXBxOOfo_eH-bfGULF8enxd3y0Tzgg0Jr3MKpmJK67zUQuW8pMJAXWdVFt-mMqysG2KMgloXRSNoITJNS1Y2Rmkl-Bxd7_vGud8jhEF2NmhoW9WDG4MUOS_KLC_ySLI9qb0LwYORG2875XeSEjm5lGs5uZSTS0m4jC5j6OrQXsVVWxMtaBv-koxTXpKyiNztnoO469aCl0Fb6DU01oMeZOPsf2N-AQqVjTk</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>753684565</pqid></control><display><type>article</type><title>Study of parameterizations for the rigid body transformations of the scan registration problem</title><source>Elsevier ScienceDirect Journals</source><creator>Nüchter, Andreas ; Elseberg, Jan ; Schneider, Peter ; Paulus, Dietrich</creator><creatorcontrib>Nüchter, Andreas ; Elseberg, Jan ; Schneider, Peter ; Paulus, Dietrich</creatorcontrib><description>The iterative closest point (ICP) algorithm is the de facto standard for geometric alignment of three-dimensional models when an initial relative pose estimate is available. The basis of the algorithm is the minimization of an error function that takes point correspondences into account. Four closed-form solution methods are known for minimizing this function. This paper presents novel linear solutions to the scan registration problem, i.e., to the problem of putting and aligning 3D scans in a common coordinate system. We extend the methods for registering
n-scans in a global and simultaneous fashion, such that the registration of the
nth scan influences all previous registrations in
one step.</description><identifier>ISSN: 1077-3142</identifier><identifier>EISSN: 1090-235X</identifier><identifier>DOI: 10.1016/j.cviu.2010.03.007</identifier><identifier>CODEN: CVIUF4</identifier><language>eng</language><publisher>Amsterdam: Elsevier Inc</publisher><subject>3D point cloud registration ; 3D scan matching ; Algorithms ; Alignment ; Applied sciences ; Artificial intelligence ; Computer science; control theory; systems ; Exact sciences and technology ; ICP algorithm ; Mathematical analysis ; Mathematical models ; Parametrization ; Pattern recognition. Digital image processing. Computational geometry ; Rigid-body dynamics ; Three dimensional</subject><ispartof>Computer vision and image understanding, 2010-08, Vol.114 (8), p.963-980</ispartof><rights>2010 Elsevier Inc.</rights><rights>2015 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c362t-3b51ef92acc58c7a53817febb4948c7f9f28bd0ffaebc66d71674c1828dfaca73</citedby><cites>FETCH-LOGICAL-c362t-3b51ef92acc58c7a53817febb4948c7f9f28bd0ffaebc66d71674c1828dfaca73</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S107731421000072X$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=23138086$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Nüchter, Andreas</creatorcontrib><creatorcontrib>Elseberg, Jan</creatorcontrib><creatorcontrib>Schneider, Peter</creatorcontrib><creatorcontrib>Paulus, Dietrich</creatorcontrib><title>Study of parameterizations for the rigid body transformations of the scan registration problem</title><title>Computer vision and image understanding</title><description>The iterative closest point (ICP) algorithm is the de facto standard for geometric alignment of three-dimensional models when an initial relative pose estimate is available. The basis of the algorithm is the minimization of an error function that takes point correspondences into account. Four closed-form solution methods are known for minimizing this function. This paper presents novel linear solutions to the scan registration problem, i.e., to the problem of putting and aligning 3D scans in a common coordinate system. We extend the methods for registering
n-scans in a global and simultaneous fashion, such that the registration of the
nth scan influences all previous registrations in
one step.</description><subject>3D point cloud registration</subject><subject>3D scan matching</subject><subject>Algorithms</subject><subject>Alignment</subject><subject>Applied sciences</subject><subject>Artificial intelligence</subject><subject>Computer science; control theory; systems</subject><subject>Exact sciences and technology</subject><subject>ICP algorithm</subject><subject>Mathematical analysis</subject><subject>Mathematical models</subject><subject>Parametrization</subject><subject>Pattern recognition. Digital image processing. Computational geometry</subject><subject>Rigid-body dynamics</subject><subject>Three dimensional</subject><issn>1077-3142</issn><issn>1090-235X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><recordid>eNp9kE1LxDAQhoMouK7-AU-5iKfWfLRNC15k8QsWPKjgyZCmkzVL26xJu7D-elN28egpyeR5Z5gHoUtKUkpocbNO9daOKSOxQHhKiDhCM0oqkjCefxxPdyESTjN2is5CWBNCaVbRGfp8HcZmh53BG-VVBwN4-6MG6_qAjfN4-ALs7co2uHaRG7zqQ6x3ByTmJiJo1WMPKxsiMP3gjXd1C905OjGqDXBxOOfo_eH-bfGULF8enxd3y0Tzgg0Jr3MKpmJK67zUQuW8pMJAXWdVFt-mMqysG2KMgloXRSNoITJNS1Y2Rmkl-Bxd7_vGud8jhEF2NmhoW9WDG4MUOS_KLC_ySLI9qb0LwYORG2875XeSEjm5lGs5uZSTS0m4jC5j6OrQXsVVWxMtaBv-koxTXpKyiNztnoO469aCl0Fb6DU01oMeZOPsf2N-AQqVjTk</recordid><startdate>20100801</startdate><enddate>20100801</enddate><creator>Nüchter, Andreas</creator><creator>Elseberg, Jan</creator><creator>Schneider, Peter</creator><creator>Paulus, Dietrich</creator><general>Elsevier Inc</general><general>Elsevier</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20100801</creationdate><title>Study of parameterizations for the rigid body transformations of the scan registration problem</title><author>Nüchter, Andreas ; Elseberg, Jan ; Schneider, Peter ; Paulus, Dietrich</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c362t-3b51ef92acc58c7a53817febb4948c7f9f28bd0ffaebc66d71674c1828dfaca73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>3D point cloud registration</topic><topic>3D scan matching</topic><topic>Algorithms</topic><topic>Alignment</topic><topic>Applied sciences</topic><topic>Artificial intelligence</topic><topic>Computer science; control theory; systems</topic><topic>Exact sciences and technology</topic><topic>ICP algorithm</topic><topic>Mathematical analysis</topic><topic>Mathematical models</topic><topic>Parametrization</topic><topic>Pattern recognition. Digital image processing. Computational geometry</topic><topic>Rigid-body dynamics</topic><topic>Three dimensional</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Nüchter, Andreas</creatorcontrib><creatorcontrib>Elseberg, Jan</creatorcontrib><creatorcontrib>Schneider, Peter</creatorcontrib><creatorcontrib>Paulus, Dietrich</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Computer and Information Systems 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><jtitle>Computer vision and image understanding</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Nüchter, Andreas</au><au>Elseberg, Jan</au><au>Schneider, Peter</au><au>Paulus, Dietrich</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Study of parameterizations for the rigid body transformations of the scan registration problem</atitle><jtitle>Computer vision and image understanding</jtitle><date>2010-08-01</date><risdate>2010</risdate><volume>114</volume><issue>8</issue><spage>963</spage><epage>980</epage><pages>963-980</pages><issn>1077-3142</issn><eissn>1090-235X</eissn><coden>CVIUF4</coden><abstract>The iterative closest point (ICP) algorithm is the de facto standard for geometric alignment of three-dimensional models when an initial relative pose estimate is available. The basis of the algorithm is the minimization of an error function that takes point correspondences into account. Four closed-form solution methods are known for minimizing this function. This paper presents novel linear solutions to the scan registration problem, i.e., to the problem of putting and aligning 3D scans in a common coordinate system. We extend the methods for registering
n-scans in a global and simultaneous fashion, such that the registration of the
nth scan influences all previous registrations in
one step.</abstract><cop>Amsterdam</cop><pub>Elsevier Inc</pub><doi>10.1016/j.cviu.2010.03.007</doi><tpages>18</tpages></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1077-3142 |
ispartof | Computer vision and image understanding, 2010-08, Vol.114 (8), p.963-980 |
issn | 1077-3142 1090-235X |
language | eng |
recordid | cdi_proquest_miscellaneous_753684565 |
source | Elsevier ScienceDirect Journals |
subjects | 3D point cloud registration 3D scan matching Algorithms Alignment Applied sciences Artificial intelligence Computer science control theory systems Exact sciences and technology ICP algorithm Mathematical analysis Mathematical models Parametrization Pattern recognition. Digital image processing. Computational geometry Rigid-body dynamics Three dimensional |
title | Study of parameterizations for the rigid body transformations of the scan registration problem |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-02T01%3A44%3A41IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Study%20of%20parameterizations%20for%20the%20rigid%20body%20transformations%20of%20the%20scan%20registration%20problem&rft.jtitle=Computer%20vision%20and%20image%20understanding&rft.au=N%C3%BCchter,%20Andreas&rft.date=2010-08-01&rft.volume=114&rft.issue=8&rft.spage=963&rft.epage=980&rft.pages=963-980&rft.issn=1077-3142&rft.eissn=1090-235X&rft.coden=CVIUF4&rft_id=info:doi/10.1016/j.cviu.2010.03.007&rft_dat=%3Cproquest_cross%3E753684565%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=753684565&rft_id=info:pmid/&rft_els_id=S107731421000072X&rfr_iscdi=true |