Enhancement of RGB-D image alignment using fiducial markers

Detalhes bibliográficos
Autor(a) principal: Madeira, Tiago de Matos Ferreira
Data de Publicação: 2019
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10773/29603
Resumo: 3D reconstruction is the creation of three-dimensional models from the captured shape and appearance of real objects. It is a field that has its roots in several areas within computer vision and graphics, and has gained high importance in others, such as architecture, robotics, autonomous driving, medicine, and archaeology. Most of the current model acquisition technologies are based on LiDAR, RGB-D cameras, and image-based approaches such as visual SLAM. Despite the improvements that have been achieved, methods that rely on professional instruments and operation result in high costs, both capital and logistical. In this dissertation, we develop an optimization procedure capable of enhancing the 3D reconstructions created using a consumer level RGB-D hand-held camera, a product that is widely available, easily handled, with a familiar interface to the average smartphone user, through the utilisation of fiducial markers placed in the environment. Additionally, a tool was developed to allow the removal of said fiducial markers from the texture of the scene, as a complement to mitigate a downside of the approach taken, but that may prove useful in other contexts.
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spelling Enhancement of RGB-D image alignment using fiducial markersComputer VisionGeometric OptimizationCamera Calibration3D ReconstructionInpaintingFiducial MarkersPoint CloudsProjection of 3D points3D reconstruction is the creation of three-dimensional models from the captured shape and appearance of real objects. It is a field that has its roots in several areas within computer vision and graphics, and has gained high importance in others, such as architecture, robotics, autonomous driving, medicine, and archaeology. Most of the current model acquisition technologies are based on LiDAR, RGB-D cameras, and image-based approaches such as visual SLAM. Despite the improvements that have been achieved, methods that rely on professional instruments and operation result in high costs, both capital and logistical. In this dissertation, we develop an optimization procedure capable of enhancing the 3D reconstructions created using a consumer level RGB-D hand-held camera, a product that is widely available, easily handled, with a familiar interface to the average smartphone user, through the utilisation of fiducial markers placed in the environment. Additionally, a tool was developed to allow the removal of said fiducial markers from the texture of the scene, as a complement to mitigate a downside of the approach taken, but that may prove useful in other contexts.A reconstrução 3D é a criação de modelos tridimensionais a partir da forma e aparência capturadas de objetos reais. É um campo que teve origem em diversos ramos da visão computacional e computação gráfica, e que ganhou grande importância em áreas como a arquitetura, robótica, condução autónoma, medicina e arqueologia. A maioria das tecnologias de aquisição de modelos atuais são baseadas em LiDAR, câmeras RGB-D e abordagens baseadas em imagens, como o SLAM visual. Apesar das melhorias que foram alcançadas, os métodos que dependem de instrumentos profissionais e da sua operação resultam em elevados custos, tanto de capital, como logísticos. Nesta dissertação foi desenvolvido um processo de otimização capaz de melhorar as reconstruções 3D criadas usando uma câmera RGB-D portátil, disponível ao nível do consumidor, de fácil manipulação e que tem uma interface familiar para o utilizador de smartphones, através da utilização de marcadores fiduciais colocados no ambiente. Além disso, uma ferramenta foi desenvolvida para permitir a remoção dos ditos marcadores fiduciais da textura da cena, como um complemento para mitigar uma desvantagem da abordagem adotada, mas que pode ser útil em outros contextos.2020-10-26T15:27:06Z2019-07-01T00:00:00Z2019-07info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10773/29603engMadeira, Tiago de Matos Ferreirainfo: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:RCAAP2024-02-22T11:57:17Zoai:ria.ua.pt:10773/29603Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:01:53.822244Repositório 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 Enhancement of RGB-D image alignment using fiducial markers
title Enhancement of RGB-D image alignment using fiducial markers
spellingShingle Enhancement of RGB-D image alignment using fiducial markers
Madeira, Tiago de Matos Ferreira
Computer Vision
Geometric Optimization
Camera Calibration
3D Reconstruction
Inpainting
Fiducial Markers
Point Clouds
Projection of 3D points
title_short Enhancement of RGB-D image alignment using fiducial markers
title_full Enhancement of RGB-D image alignment using fiducial markers
title_fullStr Enhancement of RGB-D image alignment using fiducial markers
title_full_unstemmed Enhancement of RGB-D image alignment using fiducial markers
title_sort Enhancement of RGB-D image alignment using fiducial markers
author Madeira, Tiago de Matos Ferreira
author_facet Madeira, Tiago de Matos Ferreira
author_role author
dc.contributor.author.fl_str_mv Madeira, Tiago de Matos Ferreira
dc.subject.por.fl_str_mv Computer Vision
Geometric Optimization
Camera Calibration
3D Reconstruction
Inpainting
Fiducial Markers
Point Clouds
Projection of 3D points
topic Computer Vision
Geometric Optimization
Camera Calibration
3D Reconstruction
Inpainting
Fiducial Markers
Point Clouds
Projection of 3D points
description 3D reconstruction is the creation of three-dimensional models from the captured shape and appearance of real objects. It is a field that has its roots in several areas within computer vision and graphics, and has gained high importance in others, such as architecture, robotics, autonomous driving, medicine, and archaeology. Most of the current model acquisition technologies are based on LiDAR, RGB-D cameras, and image-based approaches such as visual SLAM. Despite the improvements that have been achieved, methods that rely on professional instruments and operation result in high costs, both capital and logistical. In this dissertation, we develop an optimization procedure capable of enhancing the 3D reconstructions created using a consumer level RGB-D hand-held camera, a product that is widely available, easily handled, with a familiar interface to the average smartphone user, through the utilisation of fiducial markers placed in the environment. Additionally, a tool was developed to allow the removal of said fiducial markers from the texture of the scene, as a complement to mitigate a downside of the approach taken, but that may prove useful in other contexts.
publishDate 2019
dc.date.none.fl_str_mv 2019-07-01T00:00:00Z
2019-07
2020-10-26T15:27:06Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
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url http://hdl.handle.net/10773/29603
dc.language.iso.fl_str_mv eng
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