Spline-based feature curves from point-sampled geometry

Joel Daniels, Tilo Ochotta, Linh K. Ha, Cláudio T. Silva

Research output: Contribution to journalArticlepeer-review

Abstract

Defining sharp features in a 3D model facilitates a better understanding of the surface and aids geometric processing and graphics applications, such as reconstruction, filtering, simplification, reverse engineering, visualization, and non-photo realism. We present a robust method that identifies sharp features in a point-based model by returning a set of smooth spline curves aligned along the edges. Our feature extraction leverages the concepts of robust moving least squares to locally project points to potential features. The algorithm processes these points to construct arc-length parameterized spline curves fit using an iterative refinement method, aligning smooth and continuous curves through the feature points. We demonstrate the benefits of our method with three applications: surface segmentation, surface meshing and point-based compression.

Original languageEnglish (US)
Pages (from-to)449-462
Number of pages14
JournalVisual Computer
Volume24
Issue number6
DOIs
StatePublished - Jun 2008

Keywords

  • B-splines
  • Feature extraction
  • Moving least squares
  • Point-based modeling
  • Robust statistics

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Computer Graphics and Computer-Aided Design

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