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The Visual Computer

, Volume 28, Issue 6–8, pp 775–785 | Cite as

Feature-varying skeletonization

Intuitive control over the target feature size and output skeleton topology
  • Chris G. WillcocksEmail author
  • Frederick W. B. Li
Original Article

Abstract

Current skeletonization algorithms strive to produce a single centered result which is homotopic and insensitive to surface noise. However, this traditional approach may not well capture the main parts of complex models, and may even produce poor results for applications such as animation. Instead, we approximate model topology through a target feature size ω, where undesired features smaller than ω are smoothed, and features larger than ω are retained into groups called bones. This relaxed feature-varying strategy allows applications to generate robust and meaningful results without requiring additional parameter tuning, even for damaged, noisy, complex, or high genus models.

Keywords

Automatic Skeletonization Contraction Feature abstraction Surface noise Topology 

Notes

Acknowledgements

The work described in this paper was supported by a UK EPSRC grant (Project Number: EP/G009635/1). Special thanks go to Anna Willcocks for all her love and support.

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Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  1. 1.School of Engineering and Computing SciencesDurham UniversityDurhamEngland

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