Convexity characterization of virtual view reconstruction error in multi-view imaging

2.50
Hdl Handle:
http://hdl.handle.net/10547/622235
Title:
Convexity characterization of virtual view reconstruction error in multi-view imaging
Authors:
Velisavljević, Vladan ( 0000-0001-9980-9368 ) ; Dorea, C.; Chakareski, Jacob; de Queiroz, R.
Other Titles:
Proceedings to IEEE MMSP 2017
Abstract:
Virtual 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.
Citation:
Velisavljevic 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.
Publisher:
IEEE
Issue Date:
22-Sep-2017
URI:
http://hdl.handle.net/10547/622235
Type:
Conference papers, meetings and proceedings
Language:
en
ISBN:
9781509036486
Appears in Collections:
Engineering

Full metadata record

DC FieldValue Language
dc.contributor.authorVelisavljević, Vladanen
dc.contributor.authorDorea, C.en
dc.contributor.authorChakareski, Jacoben
dc.contributor.authorde Queiroz, R.en
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.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.en
dc.language.isoenen
dc.publisherIEEEen
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-
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