License: Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported license (CC BY-NC-ND 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/DFU.Vol2.SciViz.2011.222
URN: urn:nbn:de:0030-drops-32941
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2011/3294/
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Molchanov, Vladimir ; Rosenthal, Paul ; Linsen, Lars

Variational Level-Set Detection of Local Isosurfaces from Unstructured Point-based Volume Data

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Abstract

A standard approach for visualizing scalar volume data is the extraction of isosurfaces. The most efficient methods for surface extraction operate on regular grids. When data is given on unstructured point-based samples, regularization can be applied but may introduce interpolation errors. We propose a method for smooth isosurface visualization that operates directly on unstructured point-based volume data avoiding any resampling. We derive a variational formulation for smooth local isosurface extraction using an implicit surface representation in form of a level-set approach, deploying Moving Least Squares (MLS) approximation, and operating on a kd-tree. The locality of our approach has two aspects: first, our algorithm extracts only those components of the isosurface, which intersect a subdomain of interest; second, the action of the main term in the governing equation is concentrated near the current isosurface position. Both aspects reduce the computation times per level-set iteration. As for most level-set methods a reinitialization
procedure is needed, but we also consider a modified algorithm where this step is eliminated. The final isosurface is extracted in form of a point cloud representation. We present a novel point completion
scheme that allows us to handle highly adaptive point sample distributions. Subsequently, splat-based or mere (shaded) point rendering is applied. We apply our method to several synthetic and real-world data sets to demonstrate its validity and efficiency.

BibTeX - Entry

@InCollection{molchanov_et_al:DFU:2011:3294,
  author =	{Vladimir Molchanov and Paul Rosenthal and Lars Linsen},
  title =	{{Variational Level-Set Detection of Local Isosurfaces from Unstructured Point-based Volume Data}},
  booktitle =	{Scientific Visualization: Interactions, Features, Metaphors},
  pages =	{222--239},
  series =	{Dagstuhl Follow-Ups},
  ISBN =	{978-3-939897-26-2},
  ISSN =	{1868-8977},
  year =	{2011},
  volume =	{2},
  editor =	{Hans Hagen},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2011/3294},
  URN =		{urn:nbn:de:0030-drops-32941},
  doi =		{10.4230/DFU.Vol2.SciViz.2011.222},
  annote =	{Keywords: Level-set, isosurface extraction, visualization in astrophysics, particle simulations}
}

Keywords: Level-set, isosurface extraction, visualization in astrophysics, particle simulations
Collection: Scientific Visualization: Interactions, Features, Metaphors
Issue Date: 2011
Date of publication: 26.10.2011

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