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Erschienen in:
Overview and State-of-the-Art of Uncertainty Visualization Kapitel lesen Erstes Kapitel lesen

2014 | OriginalPaper | Buchkapitel

16. Visual Exploration of Multivariate Volume Data Based on Clustering

verfasst von : Lars Linsen

Erschienen in: Scientific Visualization

Verlag: Springer London

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Abstract

The attribute space of a multivariate volume data set is hard to handle interactively in the context of volume visualization when more than three attributes are involved. Automatic or semi-automatic approaches such as involving clustering help to reduce the complexity of the problem. Clustering methods segment the attribute space, and the segmentation can be exploited for visual exploration of the volume data. We discuss user-guided and automatic clustering approaches of the multi-dimensional attribute space and visual representations of the results. Coordinated views of object-space volume visualization with attribute-space clustering results can be applied for interactive visual exploration of the multivariate volume data and even for interactive modification of the clustering results. Respective methods are presented and discussed and future directions are outlined.

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Vorheriges Kapitel Interactive Visual Exploration and Analysis
Nächstes Kapitel Feature-Based Visualization of Multifields
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Metadaten
Titel
Visual Exploration of Multivariate Volume Data Based on Clustering
verfasst von
Lars Linsen
Copyright-Jahr
2014
Verlag
Springer London
Buch
Scientific Visualization

Print ISBN: 978-1-4471-6496-8

Electronic ISBN: 978-1-4471-6497-5

Copyright-Jahr: 2014

DOI
https://doi.org/10.1007/978-1-4471-6497-5_16

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