3D scene reconstruction and understanding from single shot pictures

Augmented reality mixes computer generated graphics with real imaging using computer vision techniques. However, nowadays, augmented reality is still a very young field of research, and its applications usually involve predefi ned tags. This thesis has been directed to use computer vision and arti c...

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Detalhes bibliográficos
Autor: García González, Alfredo
Formato: tesis de maestría
Fecha de publicación:2012
País:España
Recursos:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2099.1/16427
Acesso em linha:https://hdl.handle.net/2099.1/16427
Access Level:acceso abierto
Palavra-chave:Augmented reality
Computer vision
Machine learning
Three-dimensional imaging
Realitat augmentada
Visió per ordinador
Aprenentatge automàtic
Imatges tridimensionals
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic
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spelling 3D scene reconstruction and understanding from single shot picturesDepth evaluation from a single imageGarcía González, AlfredoAugmented realityComputer visionMachine learningThree-dimensional imagingRealitat augmentadaVisió per ordinadorAprenentatge automàticImatges tridimensionalsÀrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàticAugmented reality mixes computer generated graphics with real imaging using computer vision techniques. However, nowadays, augmented reality is still a very young field of research, and its applications usually involve predefi ned tags. This thesis has been directed to use computer vision and arti cial intelligence techniques to explore the viability of using natural landmarks as key points for computer graphics reference. Moreover, there are many techniques that infer 3D scenes from images like stereo-vision, structures from motion, depth images, shape from shading, etc. The aim of this work is to find a way of doing this from one single shot image. Finally, new virtual elements will be integrated on the final scene using contextual colors. The followed methodology has been to automatically segment an image in small planar surfaces using di fferent granularities of small regions. Each region is assumed to likely lie on only one planar surface, and thus it the 3D face that it came from can be inferred. The normal vector of the planes corresponding to the 3D faces are approximated along a discrete set of orientations. In addition, some regions do not have a regular orientation and thus, they are assumed as a texturized or porous region. Inferring the fi nal 3D orientation and location from the set of labelled regions is a non-trivial task. This work proposes a method based on the coherent topology of the neighborhood. The 3D position of each point of a region is found and a 3D scenario can be obtained. After that, the regions of the original images are textured in the 3D reconstructed faces. Finally, a color transfer approach is used to integrate new 3D objects inside the final scene.Universitat Politècnica de CatalunyaPuig Puig, AnnaPujol Vila, Oriol20122012-09-0120122012-10-30master thesishttp://purl.org/coar/resource_type/c_bdccNAhttp://purl.org/coar/version/c_be7fb7dd8ff6fe43info:eu-repo/semantics/masterThesisapplication/pdfhttps://hdl.handle.net/2099.1/16427reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution-NonCommercial-NoDerivs 3.0 Spainhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2099.1/164272026-05-27T15:37:01Z
dc.title.none.fl_str_mv 3D scene reconstruction and understanding from single shot pictures
Depth evaluation from a single image
title 3D scene reconstruction and understanding from single shot pictures
spellingShingle 3D scene reconstruction and understanding from single shot pictures
García González, Alfredo
Augmented reality
Computer vision
Machine learning
Three-dimensional imaging
Realitat augmentada
Visió per ordinador
Aprenentatge automàtic
Imatges tridimensionals
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic
title_short 3D scene reconstruction and understanding from single shot pictures
title_full 3D scene reconstruction and understanding from single shot pictures
title_fullStr 3D scene reconstruction and understanding from single shot pictures
title_full_unstemmed 3D scene reconstruction and understanding from single shot pictures
title_sort 3D scene reconstruction and understanding from single shot pictures
dc.creator.none.fl_str_mv García González, Alfredo
author García González, Alfredo
author_facet García González, Alfredo
author_role author
dc.contributor.none.fl_str_mv Puig Puig, Anna
Pujol Vila, Oriol
dc.subject.none.fl_str_mv Augmented reality
Computer vision
Machine learning
Three-dimensional imaging
Realitat augmentada
Visió per ordinador
Aprenentatge automàtic
Imatges tridimensionals
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic
topic Augmented reality
Computer vision
Machine learning
Three-dimensional imaging
Realitat augmentada
Visió per ordinador
Aprenentatge automàtic
Imatges tridimensionals
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic
description Augmented reality mixes computer generated graphics with real imaging using computer vision techniques. However, nowadays, augmented reality is still a very young field of research, and its applications usually involve predefi ned tags. This thesis has been directed to use computer vision and arti cial intelligence techniques to explore the viability of using natural landmarks as key points for computer graphics reference. Moreover, there are many techniques that infer 3D scenes from images like stereo-vision, structures from motion, depth images, shape from shading, etc. The aim of this work is to find a way of doing this from one single shot image. Finally, new virtual elements will be integrated on the final scene using contextual colors. The followed methodology has been to automatically segment an image in small planar surfaces using di fferent granularities of small regions. Each region is assumed to likely lie on only one planar surface, and thus it the 3D face that it came from can be inferred. The normal vector of the planes corresponding to the 3D faces are approximated along a discrete set of orientations. In addition, some regions do not have a regular orientation and thus, they are assumed as a texturized or porous region. Inferring the fi nal 3D orientation and location from the set of labelled regions is a non-trivial task. This work proposes a method based on the coherent topology of the neighborhood. The 3D position of each point of a region is found and a 3D scenario can be obtained. After that, the regions of the original images are textured in the 3D reconstructed faces. Finally, a color transfer approach is used to integrate new 3D objects inside the final scene.
publishDate 2012
dc.date.none.fl_str_mv 2012
2012-09-01
2012
2012-10-30
dc.type.none.fl_str_mv master thesis
http://purl.org/coar/resource_type/c_bdcc
NA
http://purl.org/coar/version/c_be7fb7dd8ff6fe43
dc.type.openaire.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
dc.identifier.none.fl_str_mv https://hdl.handle.net/2099.1/16427
url https://hdl.handle.net/2099.1/16427
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universitat Politècnica de Catalunya
publisher.none.fl_str_mv Universitat Politècnica de Catalunya
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869406066391908352
score 15,301603

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