Surface simplification using a discrete curvature norm

Sun Jeong Kim, Chang Hun Kim*, David Levin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


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
Issue number5
StatePublished - Oct 2002


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


Dive into the research topics of 'Surface simplification using a discrete curvature norm'. Together they form a unique fingerprint.

Cite this