An implementation of the partitioned Levenberg-Marquardt algorithm for applications in computer vision.
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Publication Date: | 2009 |
Other Authors: | , , |
Format: | Article |
Language: | por |
Source: | Revista Semina: Ciências Exatas e Tecnológicas (Online) |
Download full: | https://ojs.uel.br/revistas/uel/index.php/semexatas/article/view/4734 |
Summary: | At several applications of computer vision is necessary to estimate parameters for a specific model which best fits an experimental data set. For these cases, a minimization algorithm might be used and one of the most popular is the Levenberg-Marquardt algorithm. Although several free applies from this algorithm are available, any of them has great features when the resolution of problem has a sparse Jacobian matrix . In this case, it is possible to have a great reduce in the algorithm's complexity. This work presents a Levenberg-Marquardt algorithm implemented in cases which has a sparse Jacobian matrix. To illustrate this algorithm application, the camera calibration with 1D pattern is applied to solve the problem. Empirical results show that this method is able to figure out satisfactorily with few iterations, even with noise presence. |
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An implementation of the partitioned Levenberg-Marquardt algorithm for applications in computer vision.Uma implementação do algoritmo Levenberg-Marquardt dividido para aplicações em visão computacional.Levenberg-Marquardt algorithmMonocular CalibrationNewton's.Software systemAlgoritmo Levenberg-MarquardtCalibração MonocularAlgoritmo de Newton.Sistema de softwareAt several applications of computer vision is necessary to estimate parameters for a specific model which best fits an experimental data set. For these cases, a minimization algorithm might be used and one of the most popular is the Levenberg-Marquardt algorithm. Although several free applies from this algorithm are available, any of them has great features when the resolution of problem has a sparse Jacobian matrix . In this case, it is possible to have a great reduce in the algorithm's complexity. This work presents a Levenberg-Marquardt algorithm implemented in cases which has a sparse Jacobian matrix. To illustrate this algorithm application, the camera calibration with 1D pattern is applied to solve the problem. Empirical results show that this method is able to figure out satisfactorily with few iterations, even with noise presence.Em diversas aplicações da visão computacional, é necessário estimar-se, em um modelo, os parâmetros que melhor se ajustam a um conjunto de dados experimentais. Nesses casos, um algoritmo de minimização pode ser utilizado. Dentre estes, um dos mais conhecidos é o Levenberg-Marquardt. Apesar de diversas implementações de tal algoritmo estarem disponíveis livremente, nenhuma delas leva em consideração quando a solução do problema conduz a uma matriz jacobiana esparsa. Nesses casos, é possível reduzir significativamente a complexidade do algoritmo. Neste trabalho, apresenta-se uma implementação do algoritmo Levenberg-Marquardt para os casos em que a matriz jacobiana do problema é esparsa. Além disso, para ilustrar a aplicação do algoritmo, ele é aplicado a solução do problema de calibração monocular com gabaritos de uma única dimensão. Resultados empíricos mostram que o método converge satisfatoriamente em apenas algumas poucas iterações, mesmo na presença de ruído.State University of Londrina2009-07-15info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionAvaliado pelos paresapplication/pdfhttps://ojs.uel.br/revistas/uel/index.php/semexatas/article/view/473410.5433/1679-0375.2009v30n1p51Semina: Ciências Exatas e Tecnológicas; Vol. 30 No. 1 (2009); 51-62Semina: Ciências Exatas e Tecnológicas; v. 30 n. 1 (2009); 51-621679-03751676-5451reponame:Revista Semina: Ciências Exatas e Tecnológicas (Online)instname:Universidade Estadual de Londrina (UEL)instacron:UELporhttps://ojs.uel.br/revistas/uel/index.php/semexatas/article/view/4734/4092Copyright (c) 2018 Semina: Exact and Technological Sciencesinfo:eu-repo/semantics/openAccessFrança, José Alexandre deFrança, Maria Bernadete de MoraisKoyama, Marcela HitomiSilva, Tiago Polizer da2010-09-21T19:37:53Zoai:ojs2.ojs.uel.br:article/4734Revistahttps://ojs.uel.br/revistas/uel/index.php/semexatas/indexPUBhttps://ojs.uel.br/revistas/uel/index.php/semexatas/oaiseminaexatas@uel.br || periodicosuel@uel.br1679-03751676-5451opendoar:2010-09-21T19:37:53Revista Semina: Ciências Exatas e Tecnológicas (Online) - Universidade Estadual de Londrina (UEL)false |
dc.title.none.fl_str_mv |
An implementation of the partitioned Levenberg-Marquardt algorithm for applications in computer vision. Uma implementação do algoritmo Levenberg-Marquardt dividido para aplicações em visão computacional. |
title |
An implementation of the partitioned Levenberg-Marquardt algorithm for applications in computer vision. |
spellingShingle |
An implementation of the partitioned Levenberg-Marquardt algorithm for applications in computer vision. França, José Alexandre de Levenberg-Marquardt algorithm Monocular Calibration Newton's. Software system Algoritmo Levenberg-Marquardt Calibração Monocular Algoritmo de Newton. Sistema de software |
title_short |
An implementation of the partitioned Levenberg-Marquardt algorithm for applications in computer vision. |
title_full |
An implementation of the partitioned Levenberg-Marquardt algorithm for applications in computer vision. |
title_fullStr |
An implementation of the partitioned Levenberg-Marquardt algorithm for applications in computer vision. |
title_full_unstemmed |
An implementation of the partitioned Levenberg-Marquardt algorithm for applications in computer vision. |
title_sort |
An implementation of the partitioned Levenberg-Marquardt algorithm for applications in computer vision. |
author |
França, José Alexandre de |
author_facet |
França, José Alexandre de França, Maria Bernadete de Morais Koyama, Marcela Hitomi Silva, Tiago Polizer da |
author_role |
author |
author2 |
França, Maria Bernadete de Morais Koyama, Marcela Hitomi Silva, Tiago Polizer da |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
França, José Alexandre de França, Maria Bernadete de Morais Koyama, Marcela Hitomi Silva, Tiago Polizer da |
dc.subject.por.fl_str_mv |
Levenberg-Marquardt algorithm Monocular Calibration Newton's. Software system Algoritmo Levenberg-Marquardt Calibração Monocular Algoritmo de Newton. Sistema de software |
topic |
Levenberg-Marquardt algorithm Monocular Calibration Newton's. Software system Algoritmo Levenberg-Marquardt Calibração Monocular Algoritmo de Newton. Sistema de software |
description |
At several applications of computer vision is necessary to estimate parameters for a specific model which best fits an experimental data set. For these cases, a minimization algorithm might be used and one of the most popular is the Levenberg-Marquardt algorithm. Although several free applies from this algorithm are available, any of them has great features when the resolution of problem has a sparse Jacobian matrix . In this case, it is possible to have a great reduce in the algorithm's complexity. This work presents a Levenberg-Marquardt algorithm implemented in cases which has a sparse Jacobian matrix. To illustrate this algorithm application, the camera calibration with 1D pattern is applied to solve the problem. Empirical results show that this method is able to figure out satisfactorily with few iterations, even with noise presence. |
publishDate |
2009 |
dc.date.none.fl_str_mv |
2009-07-15 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Avaliado pelos pares |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://ojs.uel.br/revistas/uel/index.php/semexatas/article/view/4734 10.5433/1679-0375.2009v30n1p51 |
url |
https://ojs.uel.br/revistas/uel/index.php/semexatas/article/view/4734 |
identifier_str_mv |
10.5433/1679-0375.2009v30n1p51 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://ojs.uel.br/revistas/uel/index.php/semexatas/article/view/4734/4092 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2018 Semina: Exact and Technological Sciences info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2018 Semina: Exact and Technological Sciences |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
State University of Londrina |
publisher.none.fl_str_mv |
State University of Londrina |
dc.source.none.fl_str_mv |
Semina: Ciências Exatas e Tecnológicas; Vol. 30 No. 1 (2009); 51-62 Semina: Ciências Exatas e Tecnológicas; v. 30 n. 1 (2009); 51-62 1679-0375 1676-5451 reponame:Revista Semina: Ciências Exatas e Tecnológicas (Online) instname:Universidade Estadual de Londrina (UEL) instacron:UEL |
instname_str |
Universidade Estadual de Londrina (UEL) |
instacron_str |
UEL |
institution |
UEL |
reponame_str |
Revista Semina: Ciências Exatas e Tecnológicas (Online) |
collection |
Revista Semina: Ciências Exatas e Tecnológicas (Online) |
repository.name.fl_str_mv |
Revista Semina: Ciências Exatas e Tecnológicas (Online) - Universidade Estadual de Londrina (UEL) |
repository.mail.fl_str_mv |
seminaexatas@uel.br || periodicosuel@uel.br |
_version_ |
1841186544075931648 |