GEncode: Geometry-driven compression for General Meshes

Performances of actual mesh compression algorithms vary significantly depending on the type of model it encodes. These methods rely on prior assumptions on the mesh to be efficient, such as regular connectivity, simple topology and similarity between its elements. However, these priors are implicit...

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Vydané v:Computer graphics forum Ročník 25; číslo 4; s. 685 - 695
Hlavní autori: Lewiner, Thomas, Craizer, Marcos, Lopes, Hélio, Pesco, Sinésio, Velho, Luiz, Medeiros, Esdras
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Oxford, UK Blackwell Publishing Ltd 01.12.2006
Predmet:
Algorithms
and object representations
arbitrary dimension
arbitrary meshes
Computer graphics
Computer programming
Data compression
E.4 Coding and Information Theory: Data compaction and compression
Geometry
geometry-driven techniques
I.3.5 Computer Graphics: Curve
I.3.5 Computer Graphics: Curve, surface, solid, and object representations
mesh compression
solid
Studies
surface
Topology
ISSN:0167-7055, 1467-8659
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Shrnutí:Performances of actual mesh compression algorithms vary significantly depending on the type of model it encodes. These methods rely on prior assumptions on the mesh to be efficient, such as regular connectivity, simple topology and similarity between its elements. However, these priors are implicit in usual schemes, harming their suitability for specific models. In particular, connectivity‐driven schemes are difficult to generalize to higher dimensions and to handle topological singularities. GEncode is a new single‐rate, geometry‐driven compression scheme where prior knowledge of the mesh is plugged into the coder in an explicit manner. It encodes meshes of arbitrary dimension without topological restrictions, but can incorporate topological properties, such as manifoldness, to improve the compression ratio. Prior knowledge of the geometry is taken as an input of the algorithm, represented by a function of the local geometry. This suits particularly well for scanned and remeshed models, where exact geometric priors are available. Compression results surfaces and volumes are competitive with existing schemes.
Bibliografia:ark:/67375/WNG-PKNC7B3R-P
ArticleID:CGF990
istex:6A6D1E6D5B153E5A09E1FA52EE326BF0C2E2685B
SourceType-Scholarly Journals-1
ObjectType-Feature-1
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ObjectType-Article-2
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ISSN:0167-7055
1467-8659
DOI:10.1111/j.1467-8659.2006.00990.x