Surface simplification using a discrete curvature norm

Sun Jeong Kim, Chang Hun Kim, David Levin

Research output: Contribution to journalArticlepeer-review

86 Citations (Scopus)


This paper proposes a mesh simplification algorithm using a discrete curvature norm. Most of the simplification algorithms are using a distance metric to date. The distance metric is very efficient to measure geometric error, but it is difficult to distinguish important shape features such as a high-curvature region even though it has a small distance metric. We suggest a discrete curvature norm to measure geometric error for such features. During simplification the new vertex resulted from an edge collapse takes a position using a butterfly subdivision mask to minimize geometric error. This paper shows that simplification results have smaller geometric errors than previous works, when a discrete curvature norm and a distance metric are together applied to its criterion.

Original languageEnglish
Pages (from-to)657-663
Number of pages7
JournalComputers and Graphics (Pergamon)
Issue number5
Publication statusPublished - 2002 Oct


  • Discrete curvatures
  • Edge collapse
  • Level of detail
  • Multiresolution modeling
  • Surface simplification

ASJC Scopus subject areas

  • General Engineering
  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design


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