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Robust Depth Estimation From Multi-Focus Plenoptic Images

2020-10Conference paper Open access
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datacite.subject.fosCiências Naturais::Ciências da Computação e da Informação
datacite.subject.sdg03:Saúde de Qualidade
datacite.subject.sdg10:Reduzir as Desigualdades
datacite.subject.sdg11:Cidades e Comunidades Sustentáveis
dc.contributor.authorCunha, Francisco
dc.contributor.authorThomaz, Lucas
dc.contributor.authorTavora, Luis M. N.
dc.contributor.authorAssunção, Pedro A. A.
dc.contributor.authorFonseca-Pinto, Rui
dc.contributor.authorFaria, Sérgio M. M.
dc.date.accessioned2025-07-09T14:29:47Z
dc.date.available2025-07-09T14:29:47Z
dc.date.issued2020-10
dc.descriptionEISBN - 978-1-7281-6395-6
dc.descriptionArticle number - 9190674; Conference name - 2020 IEEE International Conference on Image Processing, ICIP 2020; Conference city - Abu Dhabi; Conference date - 25 October 2020 - 28 October 2020; Conference code - 165772
dc.description.abstractThis paper describes a robust depth estimation algorithm for multi-focus plenoptic images. The main feature of the proposed method consists of a hybrid template matching scheme built-upon intensity and local phase information, which adapts to the blurriness of neighbouring lenslet microimages. By reducing the impact of defocusblur on the template matching accuracy, the proposed method efficiently handles the varying triangulation baseline over the depth-of-field, thus discarding the need for scene-related information such as the expected range of disparities. Experimental results demonstrate the robustness of the proposed method over the most used commercially available depth estimation algorithm, achieving a reduction of 73% on the depth estimation error.eng
dc.description.sponsorshipThis work was supported by Programa Operacional Regional do Centro, project PLenoISLA POCI-01-0145-FEDER-028325 and by FCT/MCTES through national funds and when applicable co-funded EU funds under the project UIDB/EEA/50008/2020, Portugal.
dc.identifier.citationF. Cunha, L. A. Thomaz, L. M. N. Tavora, P. A. A. Assunção, R. Fonseca-Pinto and S. M. M. Faria, "Robust Depth Estimation From Multi-Focus Plenoptic Images," 2020 IEEE International Conference on Image Processing (ICIP), Abu Dhabi, United Arab Emirates, 2020, pp. 2626-2630, doi: https://doi.org/10.1109/ICIP40778.2020.9190674.
dc.identifier.doi10.1109/icip40778.2020.9190674
dc.identifier.eissn2381-8549
dc.identifier.isbn978-1-7281-6396-3
dc.identifier.isbn978-1-7281-6395-6
dc.identifier.issn15224880
dc.identifier.urihttp://hdl.handle.net/10400.8/13587
dc.language.isoeng
dc.peerreviewedyes
dc.publisherIEEE Canada
dc.relation.hasversionhttps://ieeexplore.ieee.org/document/9190674
dc.relation.ispartof2020 IEEE International Conference on Image Processing (ICIP)
dc.rights.uriN/A
dc.subjectLight Field
dc.subjectDepth Estimation
dc.subjectMulti-focus
dc.subjectLenslet
dc.titleRobust Depth Estimation From Multi-Focus Plenoptic Imageseng
dc.typeconference paper
dspace.entity.typePublication
oaire.citation.conferenceDate2020-10
oaire.citation.conferencePlaceAbu Dhabi, United Arab Emirates
oaire.citation.endPage2630
oaire.citation.startPage2626
oaire.citation.titleProceedings - International Conference on Image Processing, ICIP
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameThomaz
person.familyNamede Oliveira Pegado de Noronha E Távora
person.familyNameAssunção
person.familyNameFonseca-Pinto
person.familyNameFaria
person.givenNameLucas
person.givenNameLuís Miguel
person.givenNamePedro
person.givenNameRui
person.givenNameSergio
person.identifier.ciencia-id121C-FADA-D750
person.identifier.ciencia-id6811-3984-C17B
person.identifier.ciencia-id681D-C547-B184
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person.identifier.orcid0000-0001-6774-5363
person.identifier.orcid0000-0002-0993-9124
person.identifier.ridA-4827-2017
person.identifier.ridK-9449-2014
person.identifier.ridC-5245-2011
person.identifier.scopus-author-id6701838347
person.identifier.scopus-author-id26039086400
person.identifier.scopus-author-id14027853900
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This paper describes a robust depth estimation algorithm for multi-focus plenoptic images. The main feature of the proposed method consists of a hybrid template matching scheme built-upon intensity and local phase information, which adapts to the blurriness of neighbouring lenslet microimages. By reducing the impact of defocusblur on the template matching accuracy, the proposed method efficiently handles the varying triangulation baseline over the depth-of-field, thus discarding the need for scene-related information such as the expected range of disparities. Experimental results demonstrate the robustness of the proposed method over the most used commercially available depth estimation algorithm, achieving a reduction of 73% on the depth estimation error.
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