A fully automatic depth estimation algorithm for multi-focus plenoptic cameras: coarse and dense aproaches

Detalhes bibliográficos
Autor(a) principal: Ferreira, Rodrigo Miguel Belo Leal Toste
Data de Publicação: 2016
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10316/40485
Resumo: Dissertação de Mestrado Integrado em Engenharia Electrotécnica e de Computadores apresentada à Faculdade de Ciências e Tecnologia da Universidade de Coimbra
id RCAP_9cac5a84cffaa76712bbb1504f670496
oai_identifier_str oai:estudogeral.uc.pt:10316/40485
network_acronym_str RCAP
network_name_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository_id_str 7160
spelling A fully automatic depth estimation algorithm for multi-focus plenoptic cameras: coarse and dense aproachesCâmeras Plenópticascampo de luzestimação de profundidadeall in focusdados plenópticos simuladosRaytrixLytroPlenoptic cameraslight elddepth estimationall in focussynthetic plenopticdataRaytrixLytroDissertação de Mestrado Integrado em Engenharia Electrotécnica e de Computadores apresentada à Faculdade de Ciências e Tecnologia da Universidade de CoimbraLight field cameras capture a scene’s multi-directional light field with one image, allowing the estimation of depth of the captured scene and focus the image after it has been taken. In this thesis, we introduce a fully automatic method for depth estimation from a single plenoptic image running a RANSAC-like algorithm for feature matching. We filter the estimated depth points on a global and fine scale, allowing a more accurate depth estimation. The novelty about our approach is the global method to back project correspondences found using photometric similarity to obtain a 3D virtual point cloud. We use a smart mixture of lenses with different focal-lengths in a multiple depth map refining phase, generating a dense depth map. This depth map is then used to generate very high quality all-in-focus renders. We also introduce a new method for detection and correction of highly blurred areas, which greatly improves the depth estimation of the scene and subsequently the all-in-focus as well. As far as the author knows, our algorithm is the first fully automatic (zero intervention) method to process multi-focus plenoptic images. On the previous work a plenoptic data simulator was introduced which allows us to create plenoptic datasets with specific parameters. Knowing the depth ground truth of these datasets we are able to test and improve our algorithm and provide guidelines for future work. Tests with simulated datasets and real images are presented and show very good accuracy of the method presented. We also compare our results with other methods, being able to achieve comparable results to the state of the art with substantial less processing time. A short paper was submitted and accepted to Eurographics 2016, the 37th Annual Conference of the European Association for Computer Graphics and a full paper was also submitted to ICCP 2016, an International Conference on Computer Photography.2016-02-24info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesishttp://hdl.handle.net/10316/40485http://hdl.handle.net/10316/40485TID:201673746engFerreira, Rodrigo Miguel Belo Leal Tosteinfo: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:RCAAP2022-02-21T14:53:21Zoai:estudogeral.uc.pt:10316/40485Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:58:10.765710Repositório 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 A fully automatic depth estimation algorithm for multi-focus plenoptic cameras: coarse and dense aproaches
title A fully automatic depth estimation algorithm for multi-focus plenoptic cameras: coarse and dense aproaches
spellingShingle A fully automatic depth estimation algorithm for multi-focus plenoptic cameras: coarse and dense aproaches
Ferreira, Rodrigo Miguel Belo Leal Toste
Câmeras Plenópticas
campo de luz
estimação de profundidade
all in focus
dados plenópticos simulados
Raytrix
Lytro
Plenoptic cameras
light eld
depth estimation
all in focus
synthetic plenopticdata
Raytrix
Lytro
title_short A fully automatic depth estimation algorithm for multi-focus plenoptic cameras: coarse and dense aproaches
title_full A fully automatic depth estimation algorithm for multi-focus plenoptic cameras: coarse and dense aproaches
title_fullStr A fully automatic depth estimation algorithm for multi-focus plenoptic cameras: coarse and dense aproaches
title_full_unstemmed A fully automatic depth estimation algorithm for multi-focus plenoptic cameras: coarse and dense aproaches
title_sort A fully automatic depth estimation algorithm for multi-focus plenoptic cameras: coarse and dense aproaches
author Ferreira, Rodrigo Miguel Belo Leal Toste
author_facet Ferreira, Rodrigo Miguel Belo Leal Toste
author_role author
dc.contributor.author.fl_str_mv Ferreira, Rodrigo Miguel Belo Leal Toste
dc.subject.por.fl_str_mv Câmeras Plenópticas
campo de luz
estimação de profundidade
all in focus
dados plenópticos simulados
Raytrix
Lytro
Plenoptic cameras
light eld
depth estimation
all in focus
synthetic plenopticdata
Raytrix
Lytro
topic Câmeras Plenópticas
campo de luz
estimação de profundidade
all in focus
dados plenópticos simulados
Raytrix
Lytro
Plenoptic cameras
light eld
depth estimation
all in focus
synthetic plenopticdata
Raytrix
Lytro
description Dissertação de Mestrado Integrado em Engenharia Electrotécnica e de Computadores apresentada à Faculdade de Ciências e Tecnologia da Universidade de Coimbra
publishDate 2016
dc.date.none.fl_str_mv 2016-02-24
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/10316/40485
http://hdl.handle.net/10316/40485
TID:201673746
url http://hdl.handle.net/10316/40485
identifier_str_mv TID:201673746
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.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
_version_ 1799133872385949696

Registros relacionados