Autocalibration for Structure from Motion
Autor(a) principal: | |
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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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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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7160 |
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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 |
dc.rights.driver.fl_str_mv |
metadata only access info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
metadata only access |
eu_rights_str_mv |
openAccess |
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 |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
|
_version_ |
1799129890706948096 |