Interpolation-Based Extraction of Representative Isosurfaces

  • Oliver FernandesEmail author
  • Steffen Frey
  • Thomas Ertl
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10072)


We propose a novel technique for the automatic, similarity-based selection of representative surfaces. While our technique can be applied to any set of manifolds, we particularly focus on isosurfaces from volume data. We select representatives from sets of surfaces stemming from varying isovalues or time-dependent data. For selection, our approach interpolates between surfaces using a minimum cost flow solver, and determines whether the interpolate adequately represents the actual surface in-between. For this, we employ the Hausdorff distance as an intuitive measure of the similarity of two components. In contrast to popular contour tree-based approaches which are limited to changes in topology, our approach also accounts for geometric deviations. For interactive visualization, we employ a combination of surface renderings and a graph view that depicts the selected surfaces and their relation. We finally demonstrate the applicability and utility of our approach by means of several data sets from different areas.


Point Cloud Hausdorff Distance Bucky Ball Minimum Cost Flow Marching Cube 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was primarily funded by Deutsche Forschungsgemeinschaft (DFG) under grant SPP 1648 (ExaScaleFSA).


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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.VISUS Visualization Research InstituteUniversity of StuttgartStuttgartGermany

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