Surface simplification using a discrete curvature norm

Sun Jeong Kim, Chang Hun Kim, David Levin

    Research output: Contribution to journalArticlepeer-review

    91 Citations (Scopus)

    Abstract

    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)
    Volume26
    Issue number5
    DOIs
    Publication statusPublished - 2002 Oct

    Keywords

    • 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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