Anisotropic Diffusion of Surface Normals for Feature Preserving Surface Reconstruction

Abstract

For 3D surface reconstruction problems with noisy and incomplete range data measured from complex scenes with arbitrary topologies, a low-level representation, such as level set surfaces, is used. Such surface reconstruction is typically accomplished by minimizing a weighted sum of data-model discrepancy and model smoothness terms. This paper introduces a new nonlinear model smoothness term for surface reconstruction based on variations of the surface normals. A direct solution requires solving a fourth-order partial differential equation "PDE", which is very difficult with conventional numerical techniques. Our solution is based on processing the normals separately from the surface, which allows us to separate the problem into two second-order PDEs. The proposed method can smooth complex, noisy surfaces, while preserving sharp, geometric features, and it is a natural generalization of edge-preserving methods in image processing, such as anisotropic diffusion.

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Document Details

Document Type
Technical Report
Publication Date
Apr 18, 2003
Accession Number
ADA496496

Entities

People

  • Ross Whitaker
  • Tolga Tasdizen

Organizations

  • University of Utah

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Computations
  • Curvature
  • Differential Equations
  • Diffusion
  • Equations
  • Estimators
  • Geometry
  • Information Operations
  • Mathematical Analysis
  • Measurement
  • Shape
  • Three Dimensional

Fields of Study

  • Mathematics

Readers

  • Computer Vision.
  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)
  • Regression Analysis.