The shape space of discrete orthogonal geodesic nets

Michael Rabinovich, Tim Hoffmann, Olga Sorkine-Hornung

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

Discrete orthogonal geodesic nets (DOGs) are a quad mesh analogue of developable surfaces. In this work we study continuous deformations on these discrete objects. Our main theoretical contribution is the characterization of the shape space of DOGs for a given net connectivity. We show that generally, this space is locally a manifold of a fixed dimension, apart from a set of singularities, implying that DOGs are continuously deformable. Smooth fiows can be constructed by a smooth choice of vectors on the manifold's tangent spaces, selected to minimize a desired objective function under a given metric. We show how to compute such vectors by solving a linear system, and we use our findings to devise a geometrically meaningful way to handle singular points. We base our shape space metric on a novel DOG Laplacian operator, which is proved to converge under sampling of an analytical orthogonal geodesic net. We further show how to extend the shape space of DOGs by supporting creases and curved folds and apply the developed tools in an editing system for developable surfaces that supports arbitrary bending, stretching, cutting, (curved) folds, as well as smoothing and subdivision operations.

Original languageEnglish
Article number228
JournalACM Transactions on Graphics
Volume37
Issue number6
DOIs
StatePublished - Nov 2018

Keywords

  • Developable surfaces
  • Discrete differential geometry
  • Geodesic nets
  • Shape modelling
  • Shape space

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