Logo do repositório
 
Publicação

Multiview layered depth image

2017-01-01Artigo científico Acesso aberto
Ver registo simples
dc.contributor.authorPereira, João Madeiras
dc.contributor.authorGaspar, José António
dc.contributor.authorFernandes, Carla
dc.contributor.authorAnjos, Rafael Kuffner dos
dc.contributor.institutionCentro em Rede de Investigação em Antropologia (CRIA - NOVA FCSH)
dc.contributor.institutionCentro de Investigação em Comunicação, Informação e Cultura Digital (CIC. Digital)
dc.contributor.pblVaclav Skala Union Agency
dc.date.accessioned2019-05-08T22:15:11Z
dc.date.available2019-05-08T22:15:11Z
dc.date.issued2017-01-01
dc.description.abstractLayered Depth Images (LDI) compactly represent multiview images and videos and have widespread usage in image-based rendering applications. In its typical use case scenario of representing a scanned environment, it has proven to be a less costly alternative than separate viewpoint encoding. However, higher quality laser scanner hardware and different user interaction paradigms have emerged, creating scenarios where traditional LDIs have considerably lower efficacy. Wide-baseline setups create surfaces aligned to the viewing rays producing a greater amount of sparsely populated layers. Free viewpoint visualization suffers from the variant quantization of depths on the LDI algorithm, reducing resolution of the dataset in uneven directions. This paper presents an alternative representation to the LDI, in which each layer of data is positioned in different viewpoints that coincide with the original scanning viewpoints. A redundancy removal algorithm based on world-space distances as opposed to to image-space is discussed, ensuring points are evenly distributed and are not viewpoint dependent. We compared our proposed representation with traditional LDIs and viewpoint dependent encoding. Results showed the multiview LDI (MVLDI) creates a smaller number of layers and removes higher amounts of redundancy than traditional LDIs, ensuring no relevant portion of data is discarded in wider baseline setups.en
dc.description.versionpublishersversion
dc.description.versionpublished
dc.format.extent8
dc.format.extent10661219
dc.identifier.issn1213-6972
dc.identifier.otherPURE: 11794162
dc.identifier.otherPURE UUID: 379e4352-558c-4ebb-a729-0a12640015b5
dc.identifier.otherScopus: 85027255830
dc.identifier.urihttp://www.scopus.com/inward/record.url?scp=85027255830&partnerID=8YFLogxK
dc.identifier.urlhttps://www.scopus.com/pages/publications/85027255830
dc.language.isoeng
dc.peerreviewedyes
dc.subjectImage-based representation
dc.subjectPoint clouds
dc.subjectVideo-based rendering
dc.subjectSoftware
dc.subjectComputer Graphics and Computer-Aided Design
dc.subjectComputational Mathematics
dc.titleMultiview layered depth imageen
dc.typejournal article
degois.publication.firstPage115
degois.publication.issue2
degois.publication.lastPage122
degois.publication.titleJournal of WSCG
degois.publication.volume25
dspace.entity.typePublication
rcaap.rightsopenAccess

Ficheiros

Principais
A mostrar 1 - 1 de 1
Miniatura
Nome:
_2017_Journal_WSCG_No_2_49_56.pdf
Tamanho:
10.17 MB
Formato:
Adobe Portable Document Format
Ver/Abrir

Coleções

FCSH: ICNOVA - Artigos em revista internacional com arbitragem científica