Autocalibration for Structure from Motion

Detalhes bibliográficos
Autor(a) principal: Brito, José Henrique
Data de Publicação: 2017
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/11110/1742
Resumo: This paper is about the estimation of calibration parameters of images to be used in Structure from Mo- tion (SfM) pipelines and 3D reconstruction from image feature correspondences. It addresses the estima- tion of calibration parameters when they are not available, so that additional images may be included in the 3D reconstruction and so that the initial model may be closer to the true geometry of the scene. The approach is to take advantage of known calibration information of some of the images, to estimate cali- bration information of uncalibrated views, calibration information is therefore extended to images where visual features of the same objects are detected. The approach is based on the standard fundamental ma- trix, and extended versions of the fundamental matrix that embed the radial distortion model, named radial fundamental matrices. It is shown that the distortion model may be extracted from radial funda- mental matrices, along with the standard fundamental matrix, and that the focal length may be subse- quently estimated from it. By integrating a few of methods, the number of images that can be used in a large scale 3D reconstruction may be augmented and a better geometric model may be reconstructed. With this approach, the initial values of the parameters and the reconstructed geometry are close to the true solution, so that an optimization step may converge without getting stuck in local minima.
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spelling Autocalibration for Structure from MotionStructure from Motion (SfM)CalibrationFocal lengthRadial distortionRadial fundamental matrixThis paper is about the estimation of calibration parameters of images to be used in Structure from Mo- tion (SfM) pipelines and 3D reconstruction from image feature correspondences. It addresses the estima- tion of calibration parameters when they are not available, so that additional images may be included in the 3D reconstruction and so that the initial model may be closer to the true geometry of the scene. The approach is to take advantage of known calibration information of some of the images, to estimate cali- bration information of uncalibrated views, calibration information is therefore extended to images where visual features of the same objects are detected. The approach is based on the standard fundamental ma- trix, and extended versions of the fundamental matrix that embed the radial distortion model, named radial fundamental matrices. It is shown that the distortion model may be extracted from radial funda- mental matrices, along with the standard fundamental matrix, and that the focal length may be subse- quently estimated from it. By integrating a few of methods, the number of images that can be used in a large scale 3D reconstruction may be augmented and a better geometric model may be reconstructed. With this approach, the initial values of the parameters and the reconstructed geometry are close to the true solution, so that an optimization step may converge without getting stuck in local minima.Computer Vision and Image Understanding2019-06-12T13:55:02Z2017-04-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/11110/1742oai:ciencipca.ipca.pt:11110/1742engJosé Henrique Brito (2017), “Autocalibration for Structure from Motion”, Computer Vision and Image Understanding - Special Issue: Large-Scale 3D Modeling of Urban Indoor or Outdoor Scenes from Images and Range Scans, vol. 157, pp 240-2541077-3142http://hdl.handle.net/11110/1742metadata only accessinfo:eu-repo/semantics/openAccessBrito, José Henriquereponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2022-09-05T12:53:06Zoai:ciencipca.ipca.pt:11110/1742Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T15:02:03.468946Repositório 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 Autocalibration for Structure from Motion
title Autocalibration for Structure from Motion
spellingShingle Autocalibration for Structure from Motion
Brito, José Henrique
Structure from Motion (SfM)
Calibration
Focal length
Radial distortion
Radial fundamental matrix
title_short Autocalibration for Structure from Motion
title_full Autocalibration for Structure from Motion
title_fullStr Autocalibration for Structure from Motion
title_full_unstemmed Autocalibration for Structure from Motion
title_sort Autocalibration for Structure from Motion
author Brito, José Henrique
author_facet Brito, José Henrique
author_role author
dc.contributor.author.fl_str_mv Brito, José Henrique
dc.subject.por.fl_str_mv Structure from Motion (SfM)
Calibration
Focal length
Radial distortion
Radial fundamental matrix
topic Structure from Motion (SfM)
Calibration
Focal length
Radial distortion
Radial fundamental matrix
description This paper is about the estimation of calibration parameters of images to be used in Structure from Mo- tion (SfM) pipelines and 3D reconstruction from image feature correspondences. It addresses the estima- tion of calibration parameters when they are not available, so that additional images may be included in the 3D reconstruction and so that the initial model may be closer to the true geometry of the scene. The approach is to take advantage of known calibration information of some of the images, to estimate cali- bration information of uncalibrated views, calibration information is therefore extended to images where visual features of the same objects are detected. The approach is based on the standard fundamental ma- trix, and extended versions of the fundamental matrix that embed the radial distortion model, named radial fundamental matrices. It is shown that the distortion model may be extracted from radial funda- mental matrices, along with the standard fundamental matrix, and that the focal length may be subse- quently estimated from it. By integrating a few of methods, the number of images that can be used in a large scale 3D reconstruction may be augmented and a better geometric model may be reconstructed. With this approach, the initial values of the parameters and the reconstructed geometry are close to the true solution, so that an optimization step may converge without getting stuck in local minima.
publishDate 2017
dc.date.none.fl_str_mv 2017-04-01T00:00:00Z
2019-06-12T13:55:02Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/11110/1742
oai:ciencipca.ipca.pt:11110/1742
url http://hdl.handle.net/11110/1742
identifier_str_mv oai:ciencipca.ipca.pt:11110/1742
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv José Henrique Brito (2017), “Autocalibration for Structure from Motion”, Computer Vision and Image Understanding - Special Issue: Large-Scale 3D Modeling of Urban Indoor or Outdoor Scenes from Images and Range Scans, vol. 157, pp 240-254
1077-3142
http://hdl.handle.net/11110/1742
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info:eu-repo/semantics/openAccess
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dc.publisher.none.fl_str_mv Computer Vision and Image Understanding
publisher.none.fl_str_mv Computer Vision and Image Understanding
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
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institution RCAAP
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collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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