Fractional Reyes-Style Adaptive Tessellation for Continuous Level of Detail

In this paper we present a fractional parametric splitting scheme for Reyes‐style adaptive tessellation. Our parallel algorithm generates crack‐free tessellation from a parametric surface, which is also free of sudden temporal changes under animation. Continuous level of detail is not addressed by e...

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Vydáno v:Computer graphics forum Ročník 33; číslo 7; s. 191 - 198
Hlavní autoři: Liktor, G., Pan, M., Dachsbacher, C.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Oxford Blackwell Publishing Ltd 01.10.2014
Témata:
Algorithms
Analysis
Categories and Subject Descriptors (according to ACM CCS)
Computer graphics
I.3.1 [Hardware Architecture]: Parallel processing
I.3.5 [Computational Geometry and Object Modeling]: Curve
I.3.5 [Computational Geometry and Object Modeling]: Curve, surface, solid and object representations
solid and object representations
Studies
surface
Topological manifolds
ISSN:0167-7055, 1467-8659
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Popis
Shrnutí:In this paper we present a fractional parametric splitting scheme for Reyes‐style adaptive tessellation. Our parallel algorithm generates crack‐free tessellation from a parametric surface, which is also free of sudden temporal changes under animation. Continuous level of detail is not addressed by existing Reyes‐style methods, since these aim to produce subpixel‐sized micropolygons, where topology changes are no longer noticeable. Using our method, rendering pipelines that use larger triangles, thus sensitive to geometric popping, may also benefit from the quality of the split‐dice tessellation stages of Reyes. We demonstrate results on a real‐time GPU implementation, going beyond the limited quality and resolution of the hardware tessellation unit. In contrast to previous split‐dice methods, our split stage is compatible with the fractional hardware tessellation scheme that has been designed for continuous level of detail.
Bibliografie:ArticleID:CGF12487
Supporting Information
ark:/67375/WNG-T9Z7WBRL-X
istex:87A5FE9425ECD8D79EB38F9708AC860CA5892685
SourceType-Scholarly Journals-1
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ISSN:0167-7055
1467-8659
DOI:10.1111/cgf.12487