Robust diameter-based thickness estimation of 3D objects

  • Authors:
  • Xavier Rolland-Nevière;Gwenaël Doërr;Pierre Alliez

  • Affiliations:
  • -;-;-

  • Venue:
  • Graphical Models
  • Year:
  • 2013

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Abstract

We propose a robust thickness estimation approach for 3D objects based on the Shape Diameter Function (SDF). Our method first applies a modified strategy to estimate the local diameter with increased accuracy. We then compute a scale-dependent robust thickness estimate from a point cloud, constructed using this local diameter estimation and a variant of a robust distance function. The robustness of our method is benchmarked against several operations such as remeshing, geometric noise and artifacts common in triangle soups. The experimental results show a more stable local thickness estimation than the original SDF, and consistent segmentation results on defect-laden inputs.