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Conference Paper: A Factorization-Based Method for Projective Reconstruction with Minimization of 2-D Reprojection Errors

TitleA Factorization-Based Method for Projective Reconstruction with Minimization of 2-D Reprojection Errors
Authors
Issue Date2002
Citation
Symposium for Pattern Recognition DAGM02, Zurich, Switzerland, 2002. In Van Gool, L (Ed.). Pattern Recognition. DAGM 2002. Lecture Notes in Computer Science, v. 2449, p. 387-394. Berlin, Heidelberg: Springer, 2002 How to Cite?
AbstractIn this paper, we consider the problem of projective reconstruction based on the factorization method. Unlike existing factorization based methods which minimize the SVD reprojection error, we propose to estimate the projective depths by minimizing the 2-D reprojection errors. An iterative algorithm is developed to minimize 2-D reprojection errors. This algorithm reconstructs the projective depths robustly and does not rely on any geometric knowledge, such as epipolar geometry. Simulation results using synthetic data are given to illustrate the performance of the algorithm.
Persistent Identifierhttp://hdl.handle.net/10722/99607
ISBN
Series/Report no.Lecture Notes in Computer Science book series

 

DC FieldValueLanguage
dc.contributor.authorTang, AWKen_HK
dc.contributor.authorHung, YSen_HK
dc.date.accessioned2010-09-25T18:37:12Z-
dc.date.available2010-09-25T18:37:12Z-
dc.date.issued2002en_HK
dc.identifier.citationSymposium for Pattern Recognition DAGM02, Zurich, Switzerland, 2002. In Van Gool, L (Ed.). Pattern Recognition. DAGM 2002. Lecture Notes in Computer Science, v. 2449, p. 387-394. Berlin, Heidelberg: Springer, 2002-
dc.identifier.isbn978-3-540-44209-7-
dc.identifier.urihttp://hdl.handle.net/10722/99607-
dc.description.abstractIn this paper, we consider the problem of projective reconstruction based on the factorization method. Unlike existing factorization based methods which minimize the SVD reprojection error, we propose to estimate the projective depths by minimizing the 2-D reprojection errors. An iterative algorithm is developed to minimize 2-D reprojection errors. This algorithm reconstructs the projective depths robustly and does not rely on any geometric knowledge, such as epipolar geometry. Simulation results using synthetic data are given to illustrate the performance of the algorithm.-
dc.languageengen_HK
dc.relation.ispartofPattern Recognition. DAGM 2002. Lecture Notes in Computer Scienceen_HK
dc.relation.ispartofseriesLecture Notes in Computer Science book series-
dc.titleA Factorization-Based Method for Projective Reconstruction with Minimization of 2-D Reprojection Errorsen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailTang, AWK: wktang@hku.hken_HK
dc.identifier.emailHung, YS: yshung@eee.hku.hken_HK
dc.identifier.authorityHung, YS=rp00220en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1007/3-540-45783-6_47-
dc.identifier.hkuros82485en_HK

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