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

Abstract

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.
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Category

Academic article

Language

English

Author(s)

  • Andrea Raffo
  • Silvia Biasotti

Affiliation

  • SINTEF Digital / Mathematics and Cybernetics
  • National Research Council
  • University of Oslo

Year

2020

Published in

Computers & graphics

ISSN

0097-8493

Volume

89

Page(s)

144 - 155

View this publication at Norwegian Research Information Repository