Automatic camera pose initialization, using scale, rotation and luminance invariant natural feature tracking
Autor(a) principal: | |
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Data de Publicação: | 2008 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10071/26681 |
Resumo: | The solution to the camera registration and tracking problem serves Augmented Reality, in order to provide an enhancement to the user’s cognitive perception of the real world and his/her situational awareness. By analyzing the five most representative tracking and feature detection techniques, we have concluded that the Camera Pose Initialization (CPI) problem, a relevant sub-problem in the overall camera tracking problem, is still far from being solved using straightforward and non-intrusive methods. The assessed techniques often use user inputs (i.e. mouse clicking) or auxiliary artifacts (i.e. fiducial markers) to solve the CPI problem. This paper presents a novel approach to real-time scale, rotation and luminance invariant natural feature tracking, in order to solve the CPI problem using totally automatic procedures. The technique is applicable for the case of planar objects with arbitrary topologies and natural textures, and can be used in Augmented Reality. We also present a heuristic method for feature clustering, which has revealed to be efficient and reliable. The presented work uses this novel feature detection technique as a baseline for a real-time and robust planar texture tracking algorithm, which combines optical flow, backprojection and template matching techniques. The paper presents also performance and precision results of the proposed technique. |
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Automatic camera pose initialization, using scale, rotation and luminance invariant natural feature trackingCamera pose initializationFeature detection and trackingAugmented realityTexture trackingScale invariantRotation invariantLuminance invariantThe solution to the camera registration and tracking problem serves Augmented Reality, in order to provide an enhancement to the user’s cognitive perception of the real world and his/her situational awareness. By analyzing the five most representative tracking and feature detection techniques, we have concluded that the Camera Pose Initialization (CPI) problem, a relevant sub-problem in the overall camera tracking problem, is still far from being solved using straightforward and non-intrusive methods. The assessed techniques often use user inputs (i.e. mouse clicking) or auxiliary artifacts (i.e. fiducial markers) to solve the CPI problem. This paper presents a novel approach to real-time scale, rotation and luminance invariant natural feature tracking, in order to solve the CPI problem using totally automatic procedures. The technique is applicable for the case of planar objects with arbitrary topologies and natural textures, and can be used in Augmented Reality. We also present a heuristic method for feature clustering, which has revealed to be efficient and reliable. The presented work uses this novel feature detection technique as a baseline for a real-time and robust planar texture tracking algorithm, which combines optical flow, backprojection and template matching techniques. The paper presents also performance and precision results of the proposed technique.University of West Bohemia2022-12-19T14:12:26Z2008-01-01T00:00:00Z2008-01-012022-12-19T14:09:29Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10071/26681eng1213-6972Bastos, R.Dias, M. S.info: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:RCAAP2023-11-09T17:57:10Zoai:repositorio.iscte-iul.pt:10071/26681Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:29:28.180759Repositório 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 |
Automatic camera pose initialization, using scale, rotation and luminance invariant natural feature tracking |
title |
Automatic camera pose initialization, using scale, rotation and luminance invariant natural feature tracking |
spellingShingle |
Automatic camera pose initialization, using scale, rotation and luminance invariant natural feature tracking Bastos, R. Camera pose initialization Feature detection and tracking Augmented reality Texture tracking Scale invariant Rotation invariant Luminance invariant |
title_short |
Automatic camera pose initialization, using scale, rotation and luminance invariant natural feature tracking |
title_full |
Automatic camera pose initialization, using scale, rotation and luminance invariant natural feature tracking |
title_fullStr |
Automatic camera pose initialization, using scale, rotation and luminance invariant natural feature tracking |
title_full_unstemmed |
Automatic camera pose initialization, using scale, rotation and luminance invariant natural feature tracking |
title_sort |
Automatic camera pose initialization, using scale, rotation and luminance invariant natural feature tracking |
author |
Bastos, R. |
author_facet |
Bastos, R. Dias, M. S. |
author_role |
author |
author2 |
Dias, M. S. |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Bastos, R. Dias, M. S. |
dc.subject.por.fl_str_mv |
Camera pose initialization Feature detection and tracking Augmented reality Texture tracking Scale invariant Rotation invariant Luminance invariant |
topic |
Camera pose initialization Feature detection and tracking Augmented reality Texture tracking Scale invariant Rotation invariant Luminance invariant |
description |
The solution to the camera registration and tracking problem serves Augmented Reality, in order to provide an enhancement to the user’s cognitive perception of the real world and his/her situational awareness. By analyzing the five most representative tracking and feature detection techniques, we have concluded that the Camera Pose Initialization (CPI) problem, a relevant sub-problem in the overall camera tracking problem, is still far from being solved using straightforward and non-intrusive methods. The assessed techniques often use user inputs (i.e. mouse clicking) or auxiliary artifacts (i.e. fiducial markers) to solve the CPI problem. This paper presents a novel approach to real-time scale, rotation and luminance invariant natural feature tracking, in order to solve the CPI problem using totally automatic procedures. The technique is applicable for the case of planar objects with arbitrary topologies and natural textures, and can be used in Augmented Reality. We also present a heuristic method for feature clustering, which has revealed to be efficient and reliable. The presented work uses this novel feature detection technique as a baseline for a real-time and robust planar texture tracking algorithm, which combines optical flow, backprojection and template matching techniques. The paper presents also performance and precision results of the proposed technique. |
publishDate |
2008 |
dc.date.none.fl_str_mv |
2008-01-01T00:00:00Z 2008-01-01 2022-12-19T14:12:26Z 2022-12-19T14:09:29Z |
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/10071/26681 |
url |
http://hdl.handle.net/10071/26681 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
1213-6972 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
University of West Bohemia |
publisher.none.fl_str_mv |
University of West Bohemia |
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 |
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1799134856811118592 |