Steklov Spectral Geometry for Extrinsic Shape Analysis

Abstract

We propose using the Dirichlet-to-Neumann operator as an extrinsic alternative to the Laplacian for spectral geometry processing and shape analysis. Intrinsic approaches, usually based on the Laplace–Beltrami operator, cannot capture the spatial embedding of a shape up to rigid motion, and many previous extrinsic methods lack theoretical justification. Instead, we consider the Steklov eigenvalue problem, computing the spectrum of the Dirichlet-to-Neumann operator of a surface bounding a volume. A remarkable property of this operator is that it completely encodes volumetric geometry. We use the boundary element method (BEM) to discretize the operator, accelerated by hierarchical numerical schemes and preconditioning; this pipeline allows us to solve eigenvalue and linear problems on large-scale meshes despite the density of the Dirichlet-to-Neumann discretization. We further demonstrate that our operators naturally fit into existing frameworks for geometry processing, making a shift from intrinsic to extrinsic geometry as simple as substituting the Laplace–Beltrami operator with the Dirichlet-to-Neumann operator.

Document Details

Document Type
Pub Defense Publication
Publication Date
Dec 14, 2018
Source ID
10.1145/3152156

Entities

People

  • Iosif Polterovich
  • Justin Solomon
  • Mirela Ben-chen
  • Yu Wang

Organizations

  • Army Research Office
  • Canada Excellence Research Chairs
  • European Research Council
  • Fonds de Recherche du Québec Nature et technologies
  • Israel Science Foundation
  • Massachusetts Institute of Technology
  • National Science Foundation
  • Natural Sciences and Engineering Research Council
  • Technion – Israel Institute of Technology
  • Thomas and Stacey Siebel Foundation
  • Université de Montréal

Tags

Readers

  • Computer Vision.
  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)
  • Materials Science and Engineering.