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Data-driven quasi-interpolant spline surfaces for point cloud approximation

Sammendrag

In this paper we investigate a local surface approximation, the Weighted Quasi Interpolant Spline Approximation (wQISA), specifically designed for large and noisy point clouds. We briefly describe the properties of the wQISA representation and introduce a novel data-driven implementation, which combines prediction capability and complexity efficiency. We provide an extended comparative analysis with other continuous approximations on real data, including different types of surfaces and levels of noise, such as 3D models, terrain data and digital environmental data.
Les publikasjonen

Kategori

Vitenskapelig artikkel

Oppdragsgiver

  • EC/H2020 / 675789

Språk

Engelsk

Forfatter(e)

  • Andrea Raffo
  • Silvia Biasotti

Institusjon(er)

  • Universitetet i Oslo
  • SINTEF Digital / Mathematics and Cybernetics
  • Consiglio Nazionale delle Ricerche

År

2020

Publisert i

Computers & graphics

ISSN

0097-8493

Årgang

89

Side(r)

144 - 155

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