Repository logo
 
Publication

4D Light Field Disparity Map estimation using Krawtchouk Polynomials

2020-11Conference paper Open access
Simple item page
datacite.subject.sdg03:Saúde de Qualidade
datacite.subject.sdg10:Reduzir as Desigualdades
datacite.subject.sdg11:Cidades e Comunidades Sustentáveis
dc.contributor.authorLourenco, Rui
dc.contributor.authorRivero-Castillo, Daniel
dc.contributor.authorThomaz, Lucas A.
dc.contributor.authorAssuncao, Pedro A. A.
dc.contributor.authorTavora, Luis M. N.
dc.contributor.authorFaria, Sergio M. M. de
dc.date.accessioned2025-07-16T16:57:45Z
dc.date.available2025-07-16T16:57:45Z
dc.date.issued2020-11
dc.descriptionEISBN - 978-1-7281-8750-1
dc.descriptionArticle number - 9286454; Conference date - 9 November 2020 - 12 November 2020; Conference code - 165865
dc.description.abstractThis work presents an improved method to estimate disparity maps obtained from light field cameras using a novel edge detection algorithm based on Krawtchouk polynomials. The proposed method takes advantage of these polynomials to determine gradient information and find the edges based on automatically estimated weak and strong thresholds. The calculated edges in the gray scale epipolar plane image representation of a light field are then used to improve the accuracy of object boundaries in the the disparity map. The proposed method achieves better results when compared to other edge detection algorithms, both in terms of objective and subjective quality, specifically by reducing the mean squared error and the artifacts in the object boundaries. Furthermore, on average, the proposed method outperforms the state-of-the-art depth estimation algorithms, in terms of the objective quality of the final disparity map, namely for the commonly used HCI dataset.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.citationR. Lourenco, D. Rivero-Castillo, L. A. Thomaz, P. A. A. Assuncao, L. M. N. Tavora and S. M. M. de Faria, "4D Light Field Disparity Map estimation using Krawtchouk Polynomials," 2020 Tenth International Conference on Image Processing Theory, Tools and Applications (IPTA), Paris, France, 2020, pp. 1-6, doi: https://doi.org/10.1109/IPTA50016.2020.9286454.
dc.identifier.doi10.1109/ipta50016.2020.9286454
dc.identifier.eissn2154-512X
dc.identifier.isbn978-1-7281-8751-8
dc.identifier.isbn978-1-7281-8750-1
dc.identifier.issn2154-5111
dc.identifier.urihttp://hdl.handle.net/10400.8/13679
dc.language.isoeng
dc.peerreviewedyes
dc.publisherIEEE Canada
dc.relation.hasversionhttps://ieeexplore.ieee.org/document/9286454
dc.relation.ispartof2020 Tenth International Conference on Image Processing Theory, Tools and Applications (IPTA)
dc.rights.uriN/A
dc.subjectLight Field
dc.subjectDisparity
dc.subjectDepth
dc.subjectEdge Detection
dc.subjectKrawtchouk Polynomials
dc.subjectStructure Tensor
dc.title4D Light Field Disparity Map estimation using Krawtchouk Polynomialseng
dc.typeconference paper
dspace.entity.typePublication
oaire.citation.conferenceDate2020-11
oaire.citation.conferencePlaceParis, France
oaire.citation.title2020 10th International Conference on Image Processing Theory, Tools and Applications, IPTA 2020
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameThomaz
person.familyNameAssunção
person.familyNamede Oliveira Pegado de Noronha E Távora
person.familyNameFaria
person.givenNameLucas
person.givenNamePedro
person.givenNameLuís Miguel
person.givenNameSergio
person.identifier.ciencia-id6811-3984-C17B
person.identifier.ciencia-id121C-FADA-D750
person.identifier.ciencia-id8815-4101-28DD
person.identifier.orcid0000-0002-1004-7772
person.identifier.orcid0000-0001-9539-8311
person.identifier.orcid0000-0002-8580-1979
person.identifier.orcid0000-0002-0993-9124
person.identifier.ridA-4827-2017
person.identifier.ridC-5245-2011
person.identifier.scopus-author-id6701838347
person.identifier.scopus-author-id14027853900
relation.isAuthorOfPublication5aaecc29-3e2f-49a6-9fd9-7000d9f6085f
relation.isAuthorOfPublication25649bb9-f135-48e8-8d0f-3706b86701d3
relation.isAuthorOfPublication71940f24-f333-4ab6-abf6-00c7119a07c2
relation.isAuthorOfPublicationf69bd4d6-a6ef-4d20-8148-575478909661
relation.isAuthorOfPublication.latestForDiscovery5aaecc29-3e2f-49a6-9fd9-7000d9f6085f

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
4D Light Field Disparity Map estimation using Krawtchouk Polynomials.pdf
Size:
526.42 KB
Format:
Adobe Portable Document Format
Description:
This work presents an improved method to estimate disparity maps obtained from light field cameras using a novel edge detection algorithm based on Krawtchouk polynomials. The proposed method takes advantage of these polynomials to determine gradient information and find the edges based on automatically estimated weak and strong thresholds. The calculated edges in the gray scale epipolar plane image representation of a light field are then used to improve the accuracy of object boundaries in the the disparity map. The proposed method achieves better results when compared to other edge detection algorithms, both in terms of objective and subjective quality, specifically by reducing the mean squared error and the artifacts in the object boundaries. Furthermore, on average, the proposed method outperforms the state-of-the-art depth estimation algorithms, in terms of the objective quality of the final disparity map, namely for the commonly used HCI dataset.
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.32 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

ESTG - Comunicações em conferências e congressos internacionais