Convexity characterization of virtual view reconstruction error in multi-view imaging
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Other TitlesProceedings to IEEE MMSP 2017
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.
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.
TypeConference papers, meetings and proceedings