Feature-preserving surface reconstruction from unoriented, noisy point data

  • Wang J
  • Yu Z
  • Zhu W
 et al. 
  • 17

    Readers

    Mendeley users who have this article in their library.
  • 6

    Citations

    Citations of this article.

Abstract

We propose a robust method for surface mesh reconstruction from unorganized, unoriented, noisy and outlier-ridden 3D point data. A kernel-based scale estimator is introduced to estimate the scale of inliers of the input data. The best tangent planes are computed for all points based on mean shift clustering and adaptive scale sample consensus, followed by detecting and removing outliers. Subsequently, we estimate the normals for the remaining points and smooth the noise using a surface fitting and projection strategy. As a result, the outliers and noise are removed and filtered, while the original sharp features are well preserved. We then adopt an existing method to reconstruct surface meshes from the processed point data. To preserve sharp features of the generated meshes that are often blurred during reconstruction, we describe a two-step approach to effectively recover original sharp features. A number of examples are presented to demonstrate the effectiveness and robustness of our method. We propose a robust method for surface mesh reconstruction from unorganized, unoriented, noisy and outlierridden 3D point data. A kernel-based scale estimator is introduced to estimate the scale of inliers of the input data. The best tangent planes are computed for all points based on mean shift clustering and adaptive scale sample consensus, followed by detecting and removing outliers. We estimate the normals for the remaining points and smooth the noise using a surface fitting and projection strategy. We then adopt an existing method to reconstruct surface meshes from the processed point data. We then describe a two-step approach to effectively recover original sharp features. © 2013 The Authors Computer Graphics Forum © 2013 The Eurographics Association and Blackwell Publishing Ltd.

Author-supplied keywords

  • feature-preserving reconstruction
  • robust statistics
  • surface reconstruction
  • unoriented noisy point data

Get free article suggestions today

Mendeley saves you time finding and organizing research

Sign up here
Already have an account ?Sign in

Find this document

Cite this document

Choose a citation style from the tabs below

Save time finding and organizing research with Mendeley

Sign up for free