Iterative filtering of SIFT keypoint matches for multi-view registration in Distributed Video Coding

Detalhes bibliográficos
Autor(a) principal: Lucian Ciobanu
Data de Publicação: 2011
Outros Autores: Luís Corte Real
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://repositorio.inesctec.pt/handle/123456789/1874
Resumo: Multi-view registration is an essential step in order to generate the side information for multi-view Distributed Video Coding. As stated in our previous work (Ciobanu and Côrte-Real, Multimed Tools Appl 48(3):411-436, 2010) it can be achieved by SIFT (scale-invariant feature transform) generated keypoint matches. The registration accuracy is vital for the adequate generation of side information and it directly depends on the reliable match of possibly all the available point to point correlations between two complete-overlapped views. We propose a solution to this problem based on iterative filtering of SIFT-generated keypoint matches, using the Hough transform and block matching. It aims the generic, real-life and constraint-free scenarios having an arbitrarily close angle between the two views. Practical results show an overall significant reduction of the outliers while maintaining a high rate of correct matches.
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spelling Iterative filtering of SIFT keypoint matches for multi-view registration in Distributed Video CodingMulti-view registration is an essential step in order to generate the side information for multi-view Distributed Video Coding. As stated in our previous work (Ciobanu and Côrte-Real, Multimed Tools Appl 48(3):411-436, 2010) it can be achieved by SIFT (scale-invariant feature transform) generated keypoint matches. The registration accuracy is vital for the adequate generation of side information and it directly depends on the reliable match of possibly all the available point to point correlations between two complete-overlapped views. We propose a solution to this problem based on iterative filtering of SIFT-generated keypoint matches, using the Hough transform and block matching. It aims the generic, real-life and constraint-free scenarios having an arbitrarily close angle between the two views. Practical results show an overall significant reduction of the outliers while maintaining a high rate of correct matches.2017-11-16T12:55:42Z2011-01-01T00:00:00Z2011info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://repositorio.inesctec.pt/handle/123456789/1874engLucian CiobanuLuís Corte Realinfo: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:RCAAP2023-05-15T10:19:53Zoai:repositorio.inesctec.pt:123456789/1874Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:52:23.686910Repositório 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 Iterative filtering of SIFT keypoint matches for multi-view registration in Distributed Video Coding
title Iterative filtering of SIFT keypoint matches for multi-view registration in Distributed Video Coding
spellingShingle Iterative filtering of SIFT keypoint matches for multi-view registration in Distributed Video Coding
Lucian Ciobanu
title_short Iterative filtering of SIFT keypoint matches for multi-view registration in Distributed Video Coding
title_full Iterative filtering of SIFT keypoint matches for multi-view registration in Distributed Video Coding
title_fullStr Iterative filtering of SIFT keypoint matches for multi-view registration in Distributed Video Coding
title_full_unstemmed Iterative filtering of SIFT keypoint matches for multi-view registration in Distributed Video Coding
title_sort Iterative filtering of SIFT keypoint matches for multi-view registration in Distributed Video Coding
author Lucian Ciobanu
author_facet Lucian Ciobanu
Luís Corte Real
author_role author
author2 Luís Corte Real
author2_role author
dc.contributor.author.fl_str_mv Lucian Ciobanu
Luís Corte Real
description Multi-view registration is an essential step in order to generate the side information for multi-view Distributed Video Coding. As stated in our previous work (Ciobanu and Côrte-Real, Multimed Tools Appl 48(3):411-436, 2010) it can be achieved by SIFT (scale-invariant feature transform) generated keypoint matches. The registration accuracy is vital for the adequate generation of side information and it directly depends on the reliable match of possibly all the available point to point correlations between two complete-overlapped views. We propose a solution to this problem based on iterative filtering of SIFT-generated keypoint matches, using the Hough transform and block matching. It aims the generic, real-life and constraint-free scenarios having an arbitrarily close angle between the two views. Practical results show an overall significant reduction of the outliers while maintaining a high rate of correct matches.
publishDate 2011
dc.date.none.fl_str_mv 2011-01-01T00:00:00Z
2011
2017-11-16T12:55:42Z
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