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Article: Reconstruction of 3-D symmetric curves from perspective images without discrete features

TitleReconstruction of 3-D symmetric curves from perspective images without discrete features
Authors
Issue Date2004
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), 2004, v. 3023, p. 533-545 How to Cite?
AbstractThe shapes of many natural and man-made objects have curved contours. The images of such contours usually do not have sufficient distinctive features to apply conventional feature-based reconstruction algorithms. This paper shows that both the shape of curves in 3-D space and the camera poses can be accurately reconstructed from their perspective images with unknown point correspondences given that the curves have certain invariant properties such as symmetry. We show that in such cases the minimum number of views needed for a solution is remarkably small: one for planar curves and two for nonplanar curves (of arbitrary shapes), which is significantly less than what is required by most existing algorithms for general curves. Our solutions rely on minimizing the L2-distance between the shapes of the curves reconstructed via the "epipolar geometry" of symmetric curves. Both simulations and experiments on real images are presented to demonstrate the effectiveness of our approach. © Springer-Verlag 2004.
Persistent Identifierhttp://hdl.handle.net/10722/152362
ISSN
2005 Impact Factor: 0.402
2015 SCImago Journal Rankings: 0.252
References

 

DC FieldValueLanguage
dc.contributor.authorHong, Wen_US
dc.contributor.authorMa, Yen_US
dc.contributor.authorYu, Yen_US
dc.date.accessioned2012-06-26T06:37:37Z-
dc.date.available2012-06-26T06:37:37Z-
dc.date.issued2004en_US
dc.identifier.citationLecture Notes In Computer Science (Including Subseries Lecture Notes In Artificial Intelligence And Lecture Notes In Bioinformatics), 2004, v. 3023, p. 533-545en_US
dc.identifier.issn0302-9743en_US
dc.identifier.urihttp://hdl.handle.net/10722/152362-
dc.description.abstractThe shapes of many natural and man-made objects have curved contours. The images of such contours usually do not have sufficient distinctive features to apply conventional feature-based reconstruction algorithms. This paper shows that both the shape of curves in 3-D space and the camera poses can be accurately reconstructed from their perspective images with unknown point correspondences given that the curves have certain invariant properties such as symmetry. We show that in such cases the minimum number of views needed for a solution is remarkably small: one for planar curves and two for nonplanar curves (of arbitrary shapes), which is significantly less than what is required by most existing algorithms for general curves. Our solutions rely on minimizing the L2-distance between the shapes of the curves reconstructed via the "epipolar geometry" of symmetric curves. Both simulations and experiments on real images are presented to demonstrate the effectiveness of our approach. © Springer-Verlag 2004.en_US
dc.languageengen_US
dc.publisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/en_US
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)en_US
dc.titleReconstruction of 3-D symmetric curves from perspective images without discrete featuresen_US
dc.typeArticleen_US
dc.identifier.emailYu, Y:yzyu@cs.hku.hken_US
dc.identifier.authorityYu, Y=rp01415en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.scopuseid_2-s2.0-34948826445en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-34948826445&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume3023en_US
dc.identifier.spage533en_US
dc.identifier.epage545en_US
dc.publisher.placeGermanyen_US
dc.identifier.scopusauthoridHong, W=36077687100en_US
dc.identifier.scopusauthoridMa, Y=35196583100en_US
dc.identifier.scopusauthoridYu, Y=8554163500en_US

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