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Article: Fast multiple-view L2 triangulation with occlusion handling

TitleFast multiple-view L2 triangulation with occlusion handling
Authors
KeywordsComputer vision
LMI
Multiple-view triangulation
Occlusion
Issue Date2011
PublisherAcademic Press. The Journal's web site is located at http://www.elsevier.com/locate/cviu
Citation
Computer Vision And Image Understanding, 2011, v. 115 n. 2, p. 211-223 How to Cite?
AbstractMultiple-view L2 triangulation is a key problem in computer vision. This paper addresses the standard case where all image points are available, and the case where some image points are not available. In the latter case, it is supposed that the unknown image point belongs to a known region such as a line segment or an ellipse, as it happens for instance due to occlusions. For this problem we propose two methods based on linear matrix inequalities (LMIs). The first method, named TFML, exploits the fundamental matrix and is fast (the average computational time with two and three-views is 0.01 and 0.05 s on Matlab) at the expense of possible conservatism, which however it is shown to occur rarely in practice, and which can be immediately detected. The second method, named TPML, exploits the projection matrix, is slower, but allows one to reduce the conservatism by using techniques for optimization over polynomials. Various examples with synthetic and real data illustrate the proposed strategy. © 2010 Elsevier Inc. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/135116
ISSN
2023 Impact Factor: 4.3
2023 SCImago Journal Rankings: 1.420
ISI Accession Number ID
Funding AgencyGrant Number
HKU200907176048
RGCHKU711208E
HKU712808E
Funding Information:

The authors would like to thank the Editors and the Reviewers for their valuable comments. The work presented in this paper was supported in part by HKU Grant 200907176048 and RGC Grants HKU711208E and HKU712808E.

References
Grants

 

DC FieldValueLanguage
dc.contributor.authorChesi, Gen_HK
dc.contributor.authorHung, YSen_HK
dc.date.accessioned2011-07-27T01:28:29Z-
dc.date.available2011-07-27T01:28:29Z-
dc.date.issued2011en_HK
dc.identifier.citationComputer Vision And Image Understanding, 2011, v. 115 n. 2, p. 211-223en_HK
dc.identifier.issn1077-3142en_HK
dc.identifier.urihttp://hdl.handle.net/10722/135116-
dc.description.abstractMultiple-view L2 triangulation is a key problem in computer vision. This paper addresses the standard case where all image points are available, and the case where some image points are not available. In the latter case, it is supposed that the unknown image point belongs to a known region such as a line segment or an ellipse, as it happens for instance due to occlusions. For this problem we propose two methods based on linear matrix inequalities (LMIs). The first method, named TFML, exploits the fundamental matrix and is fast (the average computational time with two and three-views is 0.01 and 0.05 s on Matlab) at the expense of possible conservatism, which however it is shown to occur rarely in practice, and which can be immediately detected. The second method, named TPML, exploits the projection matrix, is slower, but allows one to reduce the conservatism by using techniques for optimization over polynomials. Various examples with synthetic and real data illustrate the proposed strategy. © 2010 Elsevier Inc. All rights reserved.en_HK
dc.languageengen_US
dc.publisherAcademic Press. The Journal's web site is located at http://www.elsevier.com/locate/cviuen_HK
dc.relation.ispartofComputer Vision and Image Understandingen_HK
dc.rightsNOTICE: this is the author’s version of a work that was accepted for publication in Computer Vision and Image Understanding. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computer Vision and Image Understanding, 2011, v. 115 n. 2, p. 211-223. DOI: 10.1016/j.cviu.2010.10.005-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectComputer visionen_HK
dc.subjectLMIen_HK
dc.subjectMultiple-view triangulationen_HK
dc.subjectOcclusionen_HK
dc.titleFast multiple-view L2 triangulation with occlusion handlingen_HK
dc.typeArticleen_HK
dc.identifier.emailChesi, G:chesi@eee.hku.hken_HK
dc.identifier.emailHung, YS:yshung@eee.hku.hken_HK
dc.identifier.authorityChesi, G=rp00100en_HK
dc.identifier.authorityHung, YS=rp00220en_HK
dc.description.naturepostprint-
dc.identifier.doi10.1016/j.cviu.2010.10.005en_HK
dc.identifier.scopuseid_2-s2.0-78751649642en_HK
dc.identifier.hkuros187529en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-78751649642&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume115en_HK
dc.identifier.issue2en_HK
dc.identifier.spage211en_HK
dc.identifier.epage223en_HK
dc.identifier.isiWOS:000286715900007-
dc.publisher.placeUnited Statesen_HK
dc.relation.projectTriangulation of Points in Multiple-View Vision Systems with Uncertain Data-
dc.identifier.scopusauthoridChesi, G=7006328614en_HK
dc.identifier.scopusauthoridHung, YS=8091656200en_HK
dc.identifier.citeulike8134095-
dc.identifier.issnl1077-3142-

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