Abstract
We propose a topology-based segmentation of 2D symmetric tensor fields, which results in cells bounded by tensorlines. We are particularly interested in the influence of the interpolation scheme on the topology, considering eigenvector-based and component-wise linear interpolation. When using eigenvector-based interpolation the most significant modification to the standard topology extraction algorithm is the insertion of additional vertices at degenerate points. A subsequent Delaunay re-triangulation leads to connections between close degenerate points. These new connections create degenerate edges and tri angles.When comparing the resulting topology per triangle with the one obtained by component-wise linear interpolation the results are qualitatively similar, but our approach leads to a less “cluttered” segmentation.
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Acknowledgements
This work was supported in part by the German Research Foundation (DFG) through a Junior Research Group Leader award (Emmy Noether Program), and in part by the the National Science Foundation under contract CCF-0702817. We thank our colleagues at the Zuse Institute Berlin and the Institute for Data Analysis and Visualization (IDAV), UC Davis.
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Sreevalsan-Nair, J., Auer, C., Hamann, B., Hotz, I. (2011). Eigenvector-based Interpolation and Segmentation of 2D Tensor Fields. In: Pascucci, V., Tricoche, X., Hagen, H., Tierny, J. (eds) Topological Methods in Data Analysis and Visualization. Mathematics and Visualization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15014-2_12
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DOI: https://doi.org/10.1007/978-3-642-15014-2_12
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