Adaptive Cube Tessellation for Topologically Correct Isosurfaces

Three dimensional datasets representing scalar fields are frequently rendered using isosurfaces. For datasets arranged as a cubic lattice, the marching cubes algorithm is the most used isosurface extraction method. However, the marching cubes algorithm produces some ambiguities which have been solved using different approaches that normally imply a more complex process. One of them is to tessellate the cubes into tetrahedra, and by using a similar method (marching tetrahedra), to build the isosurface. The main drawback of other tessellations is that they do not produce the same isosurface topologies as those generated by improved marching cubes algorithms. We propose an adaptive tessellation that, being independent of the isovalue, preserves the topology. Moreover the tessellationallows the isosurface to evolve continuously when the isovalue is changed continuously.

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Publication Details

Journal
Hochschule Düsseldorf
Published
2024-11-27
DOI
https://doi.org/10.20385/1860-2037/5.2008.3
Primary Topic
Topological and Geometric Data Analysis
Type
article
Field-Weighted Citation Impact
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article

Adaptive Cube Tessellation for Topologically Correct Isosurfaces

Hochschule Düsseldorf
Topological and Geometric Data Analysis
article

Adaptive Cube Tessellation for Topologically Correct Isosurfaces

article en

Abstract

Three dimensional datasets representing scalar fields are frequently rendered using isosurfaces. For datasets arranged as a cubic lattice, the marching cubes algorithm is the most used isosurface extraction method. However, the marching cubes algorithm produces some ambiguities which have been solved using different approaches that normally imply a more complex process. One of them is to tessellate the cubes into tetrahedra, and by using a similar method (marching tetrahedra), to build the isosurface. The main drawback of other tessellations is that they do not produce the same isosurface topologies as those generated by improved marching cubes algorithms. We propose an adaptive tessellation that, being independent of the isovalue, preserves the topology. Moreover the tessellationallows the isosurface to evolve continuously when the isovalue is changed continuously.

Hochschule Düsseldorf
Universidad de Granada (ES)
Openalex Percentile: Top 55%
Topological and Geometric Data Analysis
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