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Conference Paper: Estimation of the camera pose from image point correspondences through the essential matrix and convex optimization

TitleEstimation of the camera pose from image point correspondences through the essential matrix and convex optimization
Authors
KeywordsCamera pose
Convex optimization
Essential matrix
Point correspondences
Issue Date2009
Citation
IEEE International Conference on Robotics and Automation (ICRA), Kobe, Japan, 12 -17 May 2009. In I E E E International Conference on Robotics and Automation Proceedings, 2009, p. 35-40 How to Cite?
AbstractEstimating the camera pose in stereo vision systems is an important issue in computer vision and robotics. One popular way to handle this problem consists of determining the essential matrix which minimizes the algebraic error obtained from image point correspondences. Unfortunately, this search amounts to solving a nonconvex optimization, and the existing methods either rely on some approximations in order to get rid of the non-convexity or provide a solution that may be affected by the presence of local minima. This paper proposes a new approach to address this search without presenting such problems. In particular, we show that the sought essential matrix can be obtained by solving a convex optimization built through a suitable reformulation of the considered minimization via appropriate techniques for representing polynomials. Numerical results show the proposed approach compares favorably with some standard methods in both cases of synthetic data and real data. © 2009 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/62039
ISSN
References

 

DC FieldValueLanguage
dc.contributor.authorChesi, Gen_HK
dc.date.accessioned2010-07-13T03:52:38Z-
dc.date.available2010-07-13T03:52:38Z-
dc.date.issued2009en_HK
dc.identifier.citationIEEE International Conference on Robotics and Automation (ICRA), Kobe, Japan, 12 -17 May 2009. In I E E E International Conference on Robotics and Automation Proceedings, 2009, p. 35-40en_HK
dc.identifier.issn1050-4729en_HK
dc.identifier.urihttp://hdl.handle.net/10722/62039-
dc.description.abstractEstimating the camera pose in stereo vision systems is an important issue in computer vision and robotics. One popular way to handle this problem consists of determining the essential matrix which minimizes the algebraic error obtained from image point correspondences. Unfortunately, this search amounts to solving a nonconvex optimization, and the existing methods either rely on some approximations in order to get rid of the non-convexity or provide a solution that may be affected by the presence of local minima. This paper proposes a new approach to address this search without presenting such problems. In particular, we show that the sought essential matrix can be obtained by solving a convex optimization built through a suitable reformulation of the considered minimization via appropriate techniques for representing polynomials. Numerical results show the proposed approach compares favorably with some standard methods in both cases of synthetic data and real data. © 2009 IEEE.en_HK
dc.languageengen_HK
dc.relation.ispartofI E E E International Conference on Robotics and Automation Proceedingsen_HK
dc.rightsI E E E International Conference on Robotics and Automation Proceedings. Copyright © I E E E, Computer Society.-
dc.rights©2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectCamera poseen_HK
dc.subjectConvex optimizationen_HK
dc.subjectEssential matrixen_HK
dc.subjectPoint correspondencesen_HK
dc.titleEstimation of the camera pose from image point correspondences through the essential matrix and convex optimizationen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailChesi, G:chesi@eee.hku.hken_HK
dc.identifier.authorityChesi, G=rp00100en_HK
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/ROBOT.2009.5152224en_HK
dc.identifier.scopuseid_2-s2.0-70350418624en_HK
dc.identifier.hkuros156201en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-70350418624&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.spage35en_HK
dc.identifier.epage40en_HK
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridChesi, G=7006328614en_HK

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