Creating 3D object descriptors using a genetic algorithm
Autor(a) principal: | |
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Data de Publicação: | 2013 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.6/3694 |
Resumo: | In the technological world that we live in, the need for computer vision became almost as important as human vision. We are surrounded be all kinds of machines that need to have their own virtual eyes. The most developed cars have software that can analyze traffic signs in order to warn the driver about the eventsontheroad. Whenwesendaspacerovertootherplanetitisimportantthatitcananalyzetheground in order to avoid obstacles that would lead to its destruction. Thereisstillmuchworktobedoneinthefieldofcomputervisionwiththeviewtoimprovetheperformance and speed of recognition tasks. There are many available descriptors used for 3D point cloud recognition and some of them are explained in this thesis. The aim of this work is to design descriptors that can match correctly 3D point clouds. The idea is to use artificial intelligence, in the form of a GA to obtain optimized parameters for the descriptors. For this purpose the PCL [RC11] is used, which deals with the manipulation of 3D points data. The created descriptors are explained and experiments are done to illustrate their performance. The main conclusions are that there is still much work to be done in shape recognition. The descriptor developed in this thesis that use only color information is better than the descriptors that use only shape data. Although we have achieved descriptors withgoodperformanceinthisthesis,therecouldbeawaytoimprovethemevenmore. As the descriptor that use only color data is better than the shape-only descriptors, we can expect that there is a better way to represent the shape of an object. Humans can recognize better objects by shape than by color, what makes us wonder if there is a way to improve the techniques used for shape description. |
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Creating 3D object descriptors using a genetic algorithmGenetic algorithmGenetic algorithm - Object 3DIn the technological world that we live in, the need for computer vision became almost as important as human vision. We are surrounded be all kinds of machines that need to have their own virtual eyes. The most developed cars have software that can analyze traffic signs in order to warn the driver about the eventsontheroad. Whenwesendaspacerovertootherplanetitisimportantthatitcananalyzetheground in order to avoid obstacles that would lead to its destruction. Thereisstillmuchworktobedoneinthefieldofcomputervisionwiththeviewtoimprovetheperformance and speed of recognition tasks. There are many available descriptors used for 3D point cloud recognition and some of them are explained in this thesis. The aim of this work is to design descriptors that can match correctly 3D point clouds. The idea is to use artificial intelligence, in the form of a GA to obtain optimized parameters for the descriptors. For this purpose the PCL [RC11] is used, which deals with the manipulation of 3D points data. The created descriptors are explained and experiments are done to illustrate their performance. The main conclusions are that there is still much work to be done in shape recognition. The descriptor developed in this thesis that use only color information is better than the descriptors that use only shape data. Although we have achieved descriptors withgoodperformanceinthisthesis,therecouldbeawaytoimprovethemevenmore. As the descriptor that use only color data is better than the shape-only descriptors, we can expect that there is a better way to represent the shape of an object. Humans can recognize better objects by shape than by color, what makes us wonder if there is a way to improve the techniques used for shape description.Alexandre, Luís Filipe Barbosa de AlmeidauBibliorumWegrzyn, Dominik2015-07-08T11:41:33Z2013-0620132013-06-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10400.6/3694enginfo: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:RCAAP2023-12-15T09:40:11Zoai:ubibliorum.ubi.pt:10400.6/3694Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T00:45:02.905210Repositório 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 |
Creating 3D object descriptors using a genetic algorithm |
title |
Creating 3D object descriptors using a genetic algorithm |
spellingShingle |
Creating 3D object descriptors using a genetic algorithm Wegrzyn, Dominik Genetic algorithm Genetic algorithm - Object 3D |
title_short |
Creating 3D object descriptors using a genetic algorithm |
title_full |
Creating 3D object descriptors using a genetic algorithm |
title_fullStr |
Creating 3D object descriptors using a genetic algorithm |
title_full_unstemmed |
Creating 3D object descriptors using a genetic algorithm |
title_sort |
Creating 3D object descriptors using a genetic algorithm |
author |
Wegrzyn, Dominik |
author_facet |
Wegrzyn, Dominik |
author_role |
author |
dc.contributor.none.fl_str_mv |
Alexandre, Luís Filipe Barbosa de Almeida uBibliorum |
dc.contributor.author.fl_str_mv |
Wegrzyn, Dominik |
dc.subject.por.fl_str_mv |
Genetic algorithm Genetic algorithm - Object 3D |
topic |
Genetic algorithm Genetic algorithm - Object 3D |
description |
In the technological world that we live in, the need for computer vision became almost as important as human vision. We are surrounded be all kinds of machines that need to have their own virtual eyes. The most developed cars have software that can analyze traffic signs in order to warn the driver about the eventsontheroad. Whenwesendaspacerovertootherplanetitisimportantthatitcananalyzetheground in order to avoid obstacles that would lead to its destruction. Thereisstillmuchworktobedoneinthefieldofcomputervisionwiththeviewtoimprovetheperformance and speed of recognition tasks. There are many available descriptors used for 3D point cloud recognition and some of them are explained in this thesis. The aim of this work is to design descriptors that can match correctly 3D point clouds. The idea is to use artificial intelligence, in the form of a GA to obtain optimized parameters for the descriptors. For this purpose the PCL [RC11] is used, which deals with the manipulation of 3D points data. The created descriptors are explained and experiments are done to illustrate their performance. The main conclusions are that there is still much work to be done in shape recognition. The descriptor developed in this thesis that use only color information is better than the descriptors that use only shape data. Although we have achieved descriptors withgoodperformanceinthisthesis,therecouldbeawaytoimprovethemevenmore. As the descriptor that use only color data is better than the shape-only descriptors, we can expect that there is a better way to represent the shape of an object. Humans can recognize better objects by shape than by color, what makes us wonder if there is a way to improve the techniques used for shape description. |
publishDate |
2013 |
dc.date.none.fl_str_mv |
2013-06 2013 2013-06-01T00:00:00Z 2015-07-08T11:41:33Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.6/3694 |
url |
http://hdl.handle.net/10400.6/3694 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
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.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 |
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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) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799136347002241024 |