Graphical models and point pattern matching

Detalhes bibliográficos
Autor(a) principal: Caetano, Tiberio Silva
Data de Publicação: 2006
Outros Autores: Caelli, Terry, Schuurmans, Dale, Barone, Dante Augusto Couto
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFRGS
Texto Completo: http://hdl.handle.net/10183/27603
Resumo: This paper describes a novel solution to the rigid point pattern matching problem in Euclidean spaces of any dimension. Although we assume rigid motion, jitter is allowed. We present a noniterative, polynomial time algorithm that is guaranteed to find an optimal solution for the noiseless case. First, we model point pattern matching as a weighted graph matching problem, where weights correspond to Euclidean distances between nodes. We then formulate graph matching as a problem of finding a maximum probability configuration in a graphical model By using graph rigidity arguments, we prove that a sparse graphical model yields equivalent results to the fully connected model in the noiseless case. This allows us to obtain an algorithm that runs in polynomial time and is provably optimal for exact matching between noiseless point sets. For inexact matching, we can still apply the same algorithm to find approximately optimal solutions. Experimental results obtained by our approach show improvements in accuracy over current methods, particularly when matching patterns of different sizes.
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spelling Caetano, Tiberio SilvaCaelli, TerrySchuurmans, DaleBarone, Dante Augusto Couto2011-01-29T06:00:36Z20060162-8828http://hdl.handle.net/10183/27603000585735This paper describes a novel solution to the rigid point pattern matching problem in Euclidean spaces of any dimension. Although we assume rigid motion, jitter is allowed. We present a noniterative, polynomial time algorithm that is guaranteed to find an optimal solution for the noiseless case. First, we model point pattern matching as a weighted graph matching problem, where weights correspond to Euclidean distances between nodes. We then formulate graph matching as a problem of finding a maximum probability configuration in a graphical model By using graph rigidity arguments, we prove that a sparse graphical model yields equivalent results to the fully connected model in the noiseless case. This allows us to obtain an algorithm that runs in polynomial time and is provably optimal for exact matching between noiseless point sets. For inexact matching, we can still apply the same algorithm to find approximately optimal solutions. Experimental results obtained by our approach show improvements in accuracy over current methods, particularly when matching patterns of different sizes.application/pdfengIEEE transactions on pattern analysis and machine intelligence. New York. Vol. 28, n. 10 (Oct. 2006), p. 1646-1663Computação gráficaReconhecimento : PadroesPoint pattern matchingGraph matchingGraphical modelsMarkov random fieldsJunction tree algorithmGraphical models and point pattern matchingEstrangeiroinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSORIGINAL000585735.pdf000585735.pdfTexto completo (inglês)application/pdf2454125http://www.lume.ufrgs.br/bitstream/10183/27603/1/000585735.pdff48a2a0f6b170d907e60d9554b9b48f8MD51TEXT000585735.pdf.txt000585735.pdf.txtExtracted Texttext/plain92535http://www.lume.ufrgs.br/bitstream/10183/27603/2/000585735.pdf.txtee29bcb15ef267ec55ce1e70e92512dcMD52THUMBNAIL000585735.pdf.jpg000585735.pdf.jpgGenerated Thumbnailimage/jpeg2182http://www.lume.ufrgs.br/bitstream/10183/27603/3/000585735.pdf.jpg8bb329e286884a9e9aa2d83c1cb986d2MD5310183/276032021-06-13 04:33:59.334477oai:www.lume.ufrgs.br:10183/27603Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2021-06-13T07:33:59Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false
dc.title.pt_BR.fl_str_mv Graphical models and point pattern matching
title Graphical models and point pattern matching
spellingShingle Graphical models and point pattern matching
Caetano, Tiberio Silva
Computação gráfica
Reconhecimento : Padroes
Point pattern matching
Graph matching
Graphical models
Markov random fields
Junction tree algorithm
title_short Graphical models and point pattern matching
title_full Graphical models and point pattern matching
title_fullStr Graphical models and point pattern matching
title_full_unstemmed Graphical models and point pattern matching
title_sort Graphical models and point pattern matching
author Caetano, Tiberio Silva
author_facet Caetano, Tiberio Silva
Caelli, Terry
Schuurmans, Dale
Barone, Dante Augusto Couto
author_role author
author2 Caelli, Terry
Schuurmans, Dale
Barone, Dante Augusto Couto
author2_role author
author
author
dc.contributor.author.fl_str_mv Caetano, Tiberio Silva
Caelli, Terry
Schuurmans, Dale
Barone, Dante Augusto Couto
dc.subject.por.fl_str_mv Computação gráfica
Reconhecimento : Padroes
topic Computação gráfica
Reconhecimento : Padroes
Point pattern matching
Graph matching
Graphical models
Markov random fields
Junction tree algorithm
dc.subject.eng.fl_str_mv Point pattern matching
Graph matching
Graphical models
Markov random fields
Junction tree algorithm
description This paper describes a novel solution to the rigid point pattern matching problem in Euclidean spaces of any dimension. Although we assume rigid motion, jitter is allowed. We present a noniterative, polynomial time algorithm that is guaranteed to find an optimal solution for the noiseless case. First, we model point pattern matching as a weighted graph matching problem, where weights correspond to Euclidean distances between nodes. We then formulate graph matching as a problem of finding a maximum probability configuration in a graphical model By using graph rigidity arguments, we prove that a sparse graphical model yields equivalent results to the fully connected model in the noiseless case. This allows us to obtain an algorithm that runs in polynomial time and is provably optimal for exact matching between noiseless point sets. For inexact matching, we can still apply the same algorithm to find approximately optimal solutions. Experimental results obtained by our approach show improvements in accuracy over current methods, particularly when matching patterns of different sizes.
publishDate 2006
dc.date.issued.fl_str_mv 2006
dc.date.accessioned.fl_str_mv 2011-01-29T06:00:36Z
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dc.identifier.issn.pt_BR.fl_str_mv 0162-8828
dc.identifier.nrb.pt_BR.fl_str_mv 000585735
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dc.language.iso.fl_str_mv eng
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dc.relation.ispartof.pt_BR.fl_str_mv IEEE transactions on pattern analysis and machine intelligence. New York. Vol. 28, n. 10 (Oct. 2006), p. 1646-1663
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