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dc.contributor.authorKaiser, Adrienen_US
dc.contributor.authorZepeda, José Alonso Ybanezen_US
dc.contributor.authorBoubekeur, Tamyen_US
dc.contributor.editorPierre Benard and Daniel Sykoraen_US
dc.date.accessioned2017-04-22T16:43:36Z
dc.date.available2017-04-22T16:43:36Z
dc.date.issued2017
dc.identifier.issn1017-4656
dc.identifier.urihttp://dx.doi.org/10.2312/egp.20171039
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/egp20171039
dc.description.abstractModern consumer depth cameras are widely used for 3D capture in indoor environments, for applications such as modeling, robotics or gaming. Nevertheless, their use is limited by their low resolution, with frames often corrupted with noise, missing data and temporal inconsistencies. In order to cope with all these issues, we present Proxy Clouds, a multiplanar superstructure for real-time processing of RGB-D data. By generating a single set of planar proxies from raw RGB-D data and updating it through time, several processing primitives can be applied to improve the quality of the RGB-D stream or lighten further operations. We illustrate the use of Proxy Clouds on several applications, including noise and temporal flickering removal, hole filling, resampling, color processing and compression. We present experiments performed with our framework in indoor scenes of different natures captured with a consumer depth sensor.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectI.4.3 [Computing Methodologies / Image Processing and Computer Vision]
dc.subjectEnhancement
dc.subjectGeometric Correction
dc.titleProxy Clouds for RGB-D Stream Processing: A Previewen_US
dc.description.seriesinformationEG 2017 - Posters
dc.description.sectionheadersPosters
dc.identifier.doi10.2312/egp.20171039
dc.identifier.pages9-10


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