One-sided Radial-Fundamental Matrix Estimation

Detalhes bibliográficos
Autor(a) principal: Brito, José Henrique
Data de Publicação: 2012
Outros Autores: Zach, Christopher, Köser, Kevin, Ferreira, Manuel, Pollefeys, Marc
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/11110/359
Resumo: For modern consumer cameras often approximate calibration data is available, making applications such as 3D reconstruction or photo registration easier as compared to the pure uncalibrated setting. In this paper we address the setting with calibrateduncalibrated image pairs: for one image intrinsic parameters are assumed to be known, whereas the second view has unknown distortion and calibration parameters. This situation arises e.g. when one would like to register archive imagery to recently taken photos. A commonly adopted strategy for determining epipolar geometry is based on feature matching and minimal solvers inside a RANSAC framework. However, only very few existing solutions apply to the calibrated-uncalibrated setting. We propose a simple and numerically stable two-step scheme to first estimate radial distortion parameters and subsequently the focal length using novel solvers. We demonstrate the performance on synthetic and real datasets.
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spelling One-sided Radial-Fundamental Matrix Estimationradial distortioncalibrationFor modern consumer cameras often approximate calibration data is available, making applications such as 3D reconstruction or photo registration easier as compared to the pure uncalibrated setting. In this paper we address the setting with calibrateduncalibrated image pairs: for one image intrinsic parameters are assumed to be known, whereas the second view has unknown distortion and calibration parameters. This situation arises e.g. when one would like to register archive imagery to recently taken photos. A commonly adopted strategy for determining epipolar geometry is based on feature matching and minimal solvers inside a RANSAC framework. However, only very few existing solutions apply to the calibrated-uncalibrated setting. We propose a simple and numerically stable two-step scheme to first estimate radial distortion parameters and subsequently the focal length using novel solvers. We demonstrate the performance on synthetic and real datasets.BMVA Press2013-12-05T10:17:57Z2013-12-05T10:17:57Z2012-09-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/11110/359oai:ciencipca.ipca.pt:11110/359eng1-901725-46-4http://hdl.handle.net/11110/359Brito, José HenriqueZach, ChristopherKöser, KevinFerreira, ManuelPollefeys, Marcinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2022-09-05T12:51:56Zoai:ciencipca.ipca.pt:11110/359Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T15:00:46.718415Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv One-sided Radial-Fundamental Matrix Estimation
title One-sided Radial-Fundamental Matrix Estimation
spellingShingle One-sided Radial-Fundamental Matrix Estimation
Brito, José Henrique
radial distortion
calibration
title_short One-sided Radial-Fundamental Matrix Estimation
title_full One-sided Radial-Fundamental Matrix Estimation
title_fullStr One-sided Radial-Fundamental Matrix Estimation
title_full_unstemmed One-sided Radial-Fundamental Matrix Estimation
title_sort One-sided Radial-Fundamental Matrix Estimation
author Brito, José Henrique
author_facet Brito, José Henrique
Zach, Christopher
Köser, Kevin
Ferreira, Manuel
Pollefeys, Marc
author_role author
author2 Zach, Christopher
Köser, Kevin
Ferreira, Manuel
Pollefeys, Marc
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Brito, José Henrique
Zach, Christopher
Köser, Kevin
Ferreira, Manuel
Pollefeys, Marc
dc.subject.por.fl_str_mv radial distortion
calibration
topic radial distortion
calibration
description For modern consumer cameras often approximate calibration data is available, making applications such as 3D reconstruction or photo registration easier as compared to the pure uncalibrated setting. In this paper we address the setting with calibrateduncalibrated image pairs: for one image intrinsic parameters are assumed to be known, whereas the second view has unknown distortion and calibration parameters. This situation arises e.g. when one would like to register archive imagery to recently taken photos. A commonly adopted strategy for determining epipolar geometry is based on feature matching and minimal solvers inside a RANSAC framework. However, only very few existing solutions apply to the calibrated-uncalibrated setting. We propose a simple and numerically stable two-step scheme to first estimate radial distortion parameters and subsequently the focal length using novel solvers. We demonstrate the performance on synthetic and real datasets.
publishDate 2012
dc.date.none.fl_str_mv 2012-09-01T00:00:00Z
2013-12-05T10:17:57Z
2013-12-05T10:17:57Z
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/11110/359
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