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dc.contributor.authorVelisavljević, Vladanen
dc.contributor.authorDorea, Camiloen
dc.contributor.authorChakareski, Jacoben
dc.contributor.authorde Queiroz, Ricardoen
dc.date.accessioned2017-09-25T11:39:13Z
dc.date.available2017-09-25T11:39:13Z
dc.date.issued2017-09-22
dc.identifier.citationVelisavljevic V., Dorea C., Chakareski J., de Queiroz R. (2017) 'Convexity characterization of virtual view reconstruction error in multi-view imaging', IEEE Multimedia Signal Processing - Luton, IEEE.en
dc.identifier.isbn9781509036486
dc.identifier.doi10.1109/MMSP.2017.8122225
dc.identifier.urihttp://hdl.handle.net/10547/622235
dc.description.abstractVirtual view synthesis is a key component of multi-view imaging systems that enable visual immersion environments for emerging applications, e.g., virtual reality and 360-degree video. Using a small collection of captured reference viewpoints, this technique reconstructs any view of a remote scene of interest navigated by a user, to enhance the perceived immersion experience. We carry out a convexity characterization analysis of the virtual view reconstruction error that is caused by compression of the captured multi-view content. This error is expressed as a function of the virtual viewpoint coordinate relative to the captured reference viewpoints. We derive fundamental insights about the nature of this dependency and formulate a prediction framework that is able to accurately predict the specific dependency shape, convex or concave, for given reference views, multi-view content and compression settings. We are able to integrate our analysis into a proof-of-concept coding framework and demonstrate considerable benefits over a baseline approach.
dc.language.isoenen
dc.publisherIEEEen
dc.relation.urlhttps://ieeexplore.ieee.org/document/8122225/
dc.subjectmulti-view imagingen
dc.titleConvexity characterization of virtual view reconstruction error in multi-view imagingen
dc.title.alternativeProceedings to IEEE MMSP 2017en
dc.typeConference papers, meetings and proceedingsen
dc.date.updated2017-09-25T11:16:34Z
html.description.abstractVirtual view synthesis is a key component of multi-view imaging systems that enable visual immersion environments for emerging applications, e.g., virtual reality and 360-degree video. Using a small collection of captured reference viewpoints, this technique reconstructs any view of a remote scene of interest navigated by a user, to enhance the perceived immersion experience. We carry out a convexity characterization analysis of the virtual view reconstruction error that is caused by compression of the captured multi-view content. This error is expressed as a function of the virtual viewpoint coordinate relative to the captured reference viewpoints. We derive fundamental insights about the nature of this dependency and formulate a prediction framework that is able to accurately predict the specific dependency shape, convex or concave, for given reference views, multi-view content and compression settings. We are able to integrate our analysis into a proof-of-concept coding framework and demonstrate considerable benefits over a baseline approach.


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