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SIGGRAPH Asia 2013 - Course "surface- and volume-based techniques for shape modeling and analysis"

  • National Research Council of Italy
  • Louisiana State University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Extending a shape-driven map to the interior of the input shape and to the surrounding volume is a difficult problem since it typically relies on the integration of shape-based and volumetric information, together with smoothness conditions, interpolating constraints, preservation of feature values at both a local and global level. In this context, this course revises the main out-of-sample approximation schemes for both 3D shapes and d-dimensional data, and provides a unified discussion on the integration of surface- and volume-based shape information. Then, it describes the application of shape-based and volumetric techniques to shape modeling and analysis through the definition of volumetric shape descriptors; shape processing through volumetric parameterization and polycube splines; feature-driven approximation through kernels and radial basis functions. We also discuss the Hamilton's Ricci flow, which is a powerful tool to compute the conformal structure of the shapes and to design Riemannian metrics of manifolds by prescribed curvatures and shape descriptors using conformal welding. We conclude the presentation by discussing applications to shape analysis and medicine, open problems, and future perspectives.

Original languageEnglish
Title of host publicationSIGGRAPH Asia 2013 Courses, SA 2013
DOIs
StatePublished - 2013
EventSIGGRAPH Asia 2013 Courses, SA 2013 - Hong Kong, Hong Kong
Duration: Nov 19 2013Nov 22 2013

Publication series

NameSIGGRAPH Asia 2013 Courses, SA 2013

Conference

ConferenceSIGGRAPH Asia 2013 Courses, SA 2013
Country/TerritoryHong Kong
CityHong Kong
Period11/19/1311/22/13

Keywords

  • Conformal structure
  • Heat diffusion equation
  • Implicit approximation
  • Laplace-Beltrami operator
  • Manifold learning
  • Medicine and bio-informatics
  • Ricci flow
  • Riemannian surface and metric
  • Shape modeling and analysis
  • Volume parameterization

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