A Multi-scale Approach to 3D Scattered Data Interpolation with Compactly Supported Basis Functions

  • Authors:
  • Yutaka Ohtake;Alexander Belyaev;Hans-Peter Seidel

  • Affiliations:
  • -;-;-

  • Venue:
  • SMI '03 Proceedings of the Shape Modeling International 2003
  • Year:
  • 2003

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Abstract

In this paper, we propose a hierarchical approach to 3Dscattered data interpolation with compactly supported basisfunctions. Our numerical experiments suggest that theapproach integrates the best aspects of scattered data fittingwith locally and globally supported basis functions.Employing locally supported functions leads to an efficientcomputational procedure, while a coarse-to-fine hierarchymakes our method insensitive to the density of scattereddata and allows us to restore large parts of missed data.Given a point cloud distributed along a surface, we firstuse spatial down sampling to construct a coarse-to-fine hierarchyof point sets. Then we interpolate the sets startingfrom the coarsest level. We interpolate a point set of the hierarchy,as an offsetting of the interpolating function computedat the previous level. Fig. 1 shows an original pointset (the leftmost image) and its coarse-to-fine hierarchy ofinterpolated sets.According to our numerical experiments, the method isessentially faster than the state-of-art scattered data approximationwith globally supported RBFs [9] and muchsimpler to implement.