A GPU-based adaptive algorithm for non-rigid surface registration

Detalhes bibliográficos
Autor(a) principal: Souza, Antonio Carlos dos Santos
Data de Publicação: 2015
Outros Autores: Macedo, Márcio Cerqueira de Farias, Apolinário Júnior, Antonio Lopes
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UFBA
Texto Completo: http://repositorio.ufba.br/ri/handle/ri/21058
Resumo: Non-rigid surface registration is fundamental when accurate tracking or reconstruction of 3D deformable shapes is desirable. However, the majority of non-rigid registration methods are not as fast as the ones developed in the field of rigid registration. Fast methods for non-rigid surface registration are particularly interesting for markerless augmented reality applications, in which the object being used as marker can support non-rigid user interaction. In this paper, we present an adaptive algorithm for non-rigid surface registration. Taking advantage from this adaptivity and the parallelism of the GPU, we show that the proposed algorithm is capable to achieve near real-time performance with an approach as accurate as the ones proposed in the literature.
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spelling Souza, Antonio Carlos dos SantosMacedo, Márcio Cerqueira de FariasApolinário Júnior, Antonio LopesSouza, Antonio Carlos dos SantosMacedo, Márcio Cerqueira de FariasApolinário Júnior, Antonio Lopes2016-12-14T12:23:33Z2016-12-14T12:23:33Z2015-08-27978-1-4799-1727-32375-5334http://repositorio.ufba.br/ri/handle/ri/21058Non-rigid surface registration is fundamental when accurate tracking or reconstruction of 3D deformable shapes is desirable. However, the majority of non-rigid registration methods are not as fast as the ones developed in the field of rigid registration. Fast methods for non-rigid surface registration are particularly interesting for markerless augmented reality applications, in which the object being used as marker can support non-rigid user interaction. In this paper, we present an adaptive algorithm for non-rigid surface registration. Taking advantage from this adaptivity and the parallelism of the GPU, we show that the proposed algorithm is capable to achieve near real-time performance with an approach as accurate as the ones proposed in the literature.Submitted by Márcio Macedo (marciocfmacedo@hotmail.com) on 2016-12-13T15:58:25Z No. of bitstreams: 1 A GPU-Based Adaptive Algorithm for Non-Rigid Surface Registration.pdf: 1682196 bytes, checksum: b07e6602b875e9cfcc2ed43617311c30 (MD5)Approved for entry into archive by Vanessa Reis (vanessa.jamile@ufba.br) on 2016-12-14T12:23:33Z (GMT) No. of bitstreams: 1 A GPU-Based Adaptive Algorithm for Non-Rigid Surface Registration.pdf: 1682196 bytes, checksum: b07e6602b875e9cfcc2ed43617311c30 (MD5)Made available in DSpace on 2016-12-14T12:23:33Z (GMT). No. of bitstreams: 1 A GPU-Based Adaptive Algorithm for Non-Rigid Surface Registration.pdf: 1682196 bytes, checksum: b07e6602b875e9cfcc2ed43617311c30 (MD5) Previous issue date: 2015-08-27Fundação de Amparo à Pesquisa do Estado da Bahia (FAPESB) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Arles, FranceIEEEBrasilhttp://dx.doi.org/10.1109/VR.2015.7223409reponame:Repositório Institucional da UFBAinstname:Universidade Federal da Bahia (UFBA)instacron:UFBAA GPU-based adaptive algorithm for non-rigid surface registrationinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/openAccessengORIGINALA GPU-Based Adaptive Algorithm for Non-Rigid Surface Registration.pdfA GPU-Based Adaptive Algorithm for Non-Rigid Surface Registration.pdfapplication/pdf1682196https://repositorio.ufba.br/bitstream/ri/21058/1/A%20GPU-Based%20Adaptive%20Algorithm%20for%20Non-Rigid%20Surface%20Registration.pdfb07e6602b875e9cfcc2ed43617311c30MD51LICENSElicense.txtlicense.txttext/plain1345https://repositorio.ufba.br/bitstream/ri/21058/2/license.txtff6eaa8b858ea317fded99f125f5fcd0MD52TEXTA GPU-Based Adaptive Algorithm for Non-Rigid Surface Registration.pdf.txtA GPU-Based Adaptive Algorithm for Non-Rigid Surface Registration.pdf.txtExtracted texttext/plain10938https://repositorio.ufba.br/bitstream/ri/21058/3/A%20GPU-Based%20Adaptive%20Algorithm%20for%20Non-Rigid%20Surface%20Registration.pdf.txt6192c4324d73bc037e63dc847a7f78c0MD53ri/210582022-08-08 12:00:20.507oai:repositorio.ufba.br:ri/21058VGVybW8gZGUgTGljZW7vv71hLCBu77+9byBleGNsdXNpdm8sIHBhcmEgbyBkZXDvv71zaXRvIG5vIFJlcG9zaXTvv71yaW8gSW5zdGl0dWNpb25hbCBkYSBVRkJBLgoKIFBlbG8gcHJvY2Vzc28gZGUgc3VibWlzc++/vW8gZGUgZG9jdW1lbnRvcywgbyBhdXRvciBvdSBzZXUgcmVwcmVzZW50YW50ZSBsZWdhbCwgYW8gYWNlaXRhciAKZXNzZSB0ZXJtbyBkZSBsaWNlbu+/vWEsIGNvbmNlZGUgYW8gUmVwb3NpdO+/vXJpbyBJbnN0aXR1Y2lvbmFsIGRhIFVuaXZlcnNpZGFkZSBGZWRlcmFsIGRhIEJhaGlhIApvIGRpcmVpdG8gZGUgbWFudGVyIHVtYSBj77+9cGlhIGVtIHNldSByZXBvc2l077+9cmlvIGNvbSBhIGZpbmFsaWRhZGUsIHByaW1laXJhLCBkZSBwcmVzZXJ2Ye+/ve+/vW8uIApFc3NlcyB0ZXJtb3MsIG7vv71vIGV4Y2x1c2l2b3MsIG1hbnTvv71tIG9zIGRpcmVpdG9zIGRlIGF1dG9yL2NvcHlyaWdodCwgbWFzIGVudGVuZGUgbyBkb2N1bWVudG8gCmNvbW8gcGFydGUgZG8gYWNlcnZvIGludGVsZWN0dWFsIGRlc3NhIFVuaXZlcnNpZGFkZS4KCiBQYXJhIG9zIGRvY3VtZW50b3MgcHVibGljYWRvcyBjb20gcmVwYXNzZSBkZSBkaXJlaXRvcyBkZSBkaXN0cmlidWnvv73vv71vLCBlc3NlIHRlcm1vIGRlIGxpY2Vu77+9YSAKZW50ZW5kZSBxdWU6CgogTWFudGVuZG8gb3MgZGlyZWl0b3MgYXV0b3JhaXMsIHJlcGFzc2Fkb3MgYSB0ZXJjZWlyb3MsIGVtIGNhc28gZGUgcHVibGljYe+/ve+/vWVzLCBvIHJlcG9zaXTvv71yaW8KcG9kZSByZXN0cmluZ2lyIG8gYWNlc3NvIGFvIHRleHRvIGludGVncmFsLCBtYXMgbGliZXJhIGFzIGluZm9ybWHvv73vv71lcyBzb2JyZSBvIGRvY3VtZW50bwooTWV0YWRhZG9zIGVzY3JpdGl2b3MpLgoKIERlc3RhIGZvcm1hLCBhdGVuZGVuZG8gYW9zIGFuc2Vpb3MgZGVzc2EgdW5pdmVyc2lkYWRlIGVtIG1hbnRlciBzdWEgcHJvZHXvv73vv71vIGNpZW5077+9ZmljYSBjb20gCmFzIHJlc3Ryae+/ve+/vWVzIGltcG9zdGFzIHBlbG9zIGVkaXRvcmVzIGRlIHBlcmnvv71kaWNvcy4KCiBQYXJhIGFzIHB1YmxpY2Hvv73vv71lcyBzZW0gaW5pY2lhdGl2YXMgcXVlIHNlZ3VlbSBhIHBvbO+/vXRpY2EgZGUgQWNlc3NvIEFiZXJ0bywgb3MgZGVw77+9c2l0b3MgCmNvbXB1bHPvv71yaW9zIG5lc3NlIHJlcG9zaXTvv71yaW8gbWFudO+/vW0gb3MgZGlyZWl0b3MgYXV0b3JhaXMsIG1hcyBtYW5077+9bSBhY2Vzc28gaXJyZXN0cml0byAKYW8gbWV0YWRhZG9zIGUgdGV4dG8gY29tcGxldG8uIEFzc2ltLCBhIGFjZWl0Ye+/ve+/vW8gZGVzc2UgdGVybW8gbu+/vW8gbmVjZXNzaXRhIGRlIGNvbnNlbnRpbWVudG8KIHBvciBwYXJ0ZSBkZSBhdXRvcmVzL2RldGVudG9yZXMgZG9zIGRpcmVpdG9zLCBwb3IgZXN0YXJlbSBlbSBpbmljaWF0aXZhcyBkZSBhY2Vzc28gYWJlcnRvLgo=Repositório InstitucionalPUBhttp://192.188.11.11:8080/oai/requestopendoar:19322022-08-08T15:00:20Repositório Institucional da UFBA - Universidade Federal da Bahia (UFBA)false
dc.title.pt_BR.fl_str_mv A GPU-based adaptive algorithm for non-rigid surface registration
title A GPU-based adaptive algorithm for non-rigid surface registration
spellingShingle A GPU-based adaptive algorithm for non-rigid surface registration
Souza, Antonio Carlos dos Santos
title_short A GPU-based adaptive algorithm for non-rigid surface registration
title_full A GPU-based adaptive algorithm for non-rigid surface registration
title_fullStr A GPU-based adaptive algorithm for non-rigid surface registration
title_full_unstemmed A GPU-based adaptive algorithm for non-rigid surface registration
title_sort A GPU-based adaptive algorithm for non-rigid surface registration
author Souza, Antonio Carlos dos Santos
author_facet Souza, Antonio Carlos dos Santos
Macedo, Márcio Cerqueira de Farias
Apolinário Júnior, Antonio Lopes
author_role author
author2 Macedo, Márcio Cerqueira de Farias
Apolinário Júnior, Antonio Lopes
author2_role author
author
dc.contributor.author.fl_str_mv Souza, Antonio Carlos dos Santos
Macedo, Márcio Cerqueira de Farias
Apolinário Júnior, Antonio Lopes
Souza, Antonio Carlos dos Santos
Macedo, Márcio Cerqueira de Farias
Apolinário Júnior, Antonio Lopes
description Non-rigid surface registration is fundamental when accurate tracking or reconstruction of 3D deformable shapes is desirable. However, the majority of non-rigid registration methods are not as fast as the ones developed in the field of rigid registration. Fast methods for non-rigid surface registration are particularly interesting for markerless augmented reality applications, in which the object being used as marker can support non-rigid user interaction. In this paper, we present an adaptive algorithm for non-rigid surface registration. Taking advantage from this adaptivity and the parallelism of the GPU, we show that the proposed algorithm is capable to achieve near real-time performance with an approach as accurate as the ones proposed in the literature.
publishDate 2015
dc.date.issued.fl_str_mv 2015-08-27
dc.date.accessioned.fl_str_mv 2016-12-14T12:23:33Z
dc.date.available.fl_str_mv 2016-12-14T12:23:33Z
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dc.identifier.issn.none.fl_str_mv 2375-5334
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dc.publisher.none.fl_str_mv IEEE
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