Adaptive fourier-based surface reconstruction

  • Authors:
  • Oliver Schall;Alexander Belyaev;Hans-Peter Seidel

  • Affiliations:
  • Computer Graphics Group, Max-Planck-Institut für Informatik, Saarbrücken, Germany;Computer Graphics Group, Max-Planck-Institut für Informatik, Saarbrücken, Germany;Computer Graphics Group, Max-Planck-Institut für Informatik, Saarbrücken, Germany

  • Venue:
  • GMP'06 Proceedings of the 4th international conference on Geometric Modeling and Processing
  • Year:
  • 2006

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Abstract

In this paper, we combine Kazhdan's FFT-based approach to surface reconstruction from oriented points with adaptive subdivision and partition of unity blending techniques. The advantages of our surface reconstruction method include a more robust surface restoration in regions where the surface bends close to itself and a lower memory consumption. The latter allows us to achieve a higher reconstruction accuracy than the original global approach. Furthermore, our reconstruction process is guided by a global error control achieved by computing the Hausdorff distance of selected input samples to intermediate reconstructions.