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dc.contributor.authorVáša, Libor
dc.contributor.authorSkala, Václav
dc.date.accessioned2014-06-11T09:57:27Z
dc.date.available2014-06-11T09:57:27Z
dc.date.issued2010
dc.identifier.citationComputer Graphics Forum. 2010, vol. 29, is. 6, p. 1921–1933.en
dc.identifier.issn0167-7055
dc.identifier.urihttp://hdl.handle.net/11025/11335
dc.identifier.urihttp://dx.doi.org/10.1111/j.1467-8659.2010.01659.x
dc.description.abstractThe task of dynamic mesh compression seeks to find a compact representation of a surface animation, while the artifacts introduced by the representation are as small as possible. In this paper we present two geometric predictors, which are suitable for PCA based compression schemes. The predictors exploit the knowledge about the geometrical meaning of the data, which allows a more accurate prediction, and thus a more compact representation. We also provide rate/distortion curves showing that our approach outperforms the current PCA-based compression methods by more than 20%.en
dc.format12 s.
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherWileyen
dc.relation.ispartofseriesComputer Graphics Forumen
dc.rightsThis is the pre-peer reviewed version of the following article: VÁŠA, L. and Václav SKALA. Geometry-Driven Local Neighbourhood Based Predictors for Dynamic Mesh Compression. Computer Graphics Forum, 2010, vol. 29, is. 6, p. 1921–1933. doi: 10.1111/j.1467-8659.2010.01659.x., which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1111/j.1467-8659.2010.01659.x/abstract.en
dc.subjectpočítačová grafikacs
dc.subjectkomprese datcs
dc.subjectdynamické sítěcs
dc.subjectpredikcecs
dc.subjectanimacecs
dc.titleGeometry driven local neighbourhood based predictors for dynamic mesh compressionen
dc.typepreprintcs
dc.typepreprinten
dc.rights.accessopenAccessen
dc.type.versiondraften
dc.subject.translatedcomputer graphicsen
dc.subject.translateddata compressionen
dc.subject.translateddynamic networksen
dc.subject.translatedpredictionen
dc.subject.translatedanimationen
dc.identifier.doi10.1111/j.1467-8659.2010.01659.x
dc.type.statusPeer-revieweden
Appears in Collections:Preprinty / Preprints (KIV)

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