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Computational Geometry
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Computational Geometry
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Multivariate topology simplification

Authors: Amit Chattopadhyay; Hamish A. Carr; David J. Duke; Zhao Geng; Osamu Saeki;

Multivariate topology simplification

Abstract

Topological simplification of scalar and vector fields is well-established as an effective method for analysing and visualising complex data sets. For multi-field data, topological analysis requires simultaneous advances both mathematically and computationally. We propose a robust multivariate topology simplification method based on ``lip''-pruning from the Reeb Space. Mathematically, we show that the projection of the Jacobi Set of multivariate data into the Reeb Space produces a Jacobi Structure that separates the Reeb Space into simple components. We also show that the dual graph of these components gives rise to a Reeb Skeleton that has properties similar to the scalar contour tree and Reeb Graph, for topologically simple domains. We then introduce a range measure to give a scaling-invariant total ordering of the components or features that can be used for simplification. Computationally, we show how to compute Jacobi Structure, Reeb Skeleton, Range and Geometric Measures in the Joint Contour Net (an approximation of the Reeb Space) and that these can be used for visualisation similar to the contour tree or Reeb Graph.

Under Review in Journal

Country
United Kingdom
Keywords

Computational Geometry (cs.CG), FOS: Computer and information sciences, Reeb space, Multivariate topology, Multi-dimensional Reeb graph, simplification, multivariate topology, multi-dimensional Reeb graph, Jacobi set, Simplification, Jacobi structure, Numerical aspects of computer graphics, image analysis, and computational geometry, Computer graphics; computational geometry (digital and algorithmic aspects), Computer Science - Computational Geometry, Reeb skeleton

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    influence
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
14
Top 10%
Top 10%
Top 10%
Green
hybrid