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DiagSplit: parallel, crack-free, adaptive tessellation for micropolygon rendering

Published: 01 December 2009 Publication History

Abstract

We present DiagSplit, a parallel algorithm for adaptively tessellating displaced parametric surfaces into high-quality, crack-free micropolygon meshes. DiagSplit modifies the split-dice tessellation algorithm to allow splits along non-isoparametric directions in the surface's parametric domain, and uses a dicing scheme that supports unique tessellation factors for each subpatch edge. Edge tessellation factors are computed using only information local to subpatch edges. These modifications allow all subpatches generated by DiagSplit to be processed independently without introducing T-junctions or mesh cracks and without incurring the tessellation overhead of binary dicing. We demonstrate that DiagSplit produces output that is better (in terms of image quality and number of micropolygons produced) than existing parallel tessellation schemes, and as good as highly adaptive split-dice implementations that are less amenable to parallelization.

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cover image ACM Conferences
SIGGRAPH Asia '09: ACM SIGGRAPH Asia 2009 papers
December 2009
669 pages
ISBN:9781605588582
DOI:10.1145/1661412
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 01 December 2009

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Author Tags

  1. micropolygons
  2. real-time rendering
  3. tessellation

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SA09
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SA09: SIGGRAPH ASIA 2009
December 16 - 19, 2009
Yokohama, Japan

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SIGGRAPH Asia '09 Paper Acceptance Rate 70 of 275 submissions, 25%;
Overall Acceptance Rate 178 of 869 submissions, 20%

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