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Progressive compression of geometry information with smooth intermediate meshes

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dc.contributor.authorPark, Taejung-
dc.contributor.authorLee, Haeyoung-
dc.contributor.authorKim, Chang-hun-
dc.date.accessioned2022-07-05T08:42:36Z-
dc.date.available2022-07-05T08:42:36Z-
dc.date.created2022-07-05-
dc.date.issued2007-
dc.identifier.issn0302-9743-
dc.identifier.urihttps://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/29926-
dc.description.abstractWe present a new geometry compression algorithm for manifold 3D meshes based on octree coding. For a given mesh, regular volume grids are built with an adaptive octree. For each grid point, a binary sign, which indicates inside or outside of the mesh, is generated based on the distance to the mesh. In each leaf cell having a vertex, a least square fitting plane is created for a localized geometry range with signs. Finally, quantized geometry information is locally encoded. We demonstrate that the octree with signs can be used to predict the vertex positions. As a result, the proposed method generates competitive bitrates compared to the current state-of-art progressive geometry coder. Our method also shows better rate-distortion performance during decompression or transmission with improved smoothness.-
dc.language영어-
dc.language.isoen-
dc.publisherSPRINGER-VERLAG BERLIN-
dc.titleProgressive compression of geometry information with smooth intermediate meshes-
dc.typeArticle-
dc.contributor.affiliatedAuthorLee, Haeyoung-
dc.identifier.wosid000247329100012-
dc.identifier.bibliographicCitationPATTERN RECOGNITION AND IMAGE ANALYSIS, PT 2, PROCEEDINGS, v.4478, pp.89 - +-
dc.relation.isPartOfPATTERN RECOGNITION AND IMAGE ANALYSIS, PT 2, PROCEEDINGS-
dc.citation.titlePATTERN RECOGNITION AND IMAGE ANALYSIS, PT 2, PROCEEDINGS-
dc.citation.volume4478-
dc.citation.startPage89-
dc.citation.endPage+-
dc.type.rimsART-
dc.type.docTypeProceedings Paper-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaImaging Science & Photographic Technology-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.relation.journalWebOfScienceCategoryComputer Science, Theory & Methods-
dc.relation.journalWebOfScienceCategoryImaging Science & Photographic Technology-
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