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Summary: Tensor Field Reconstruction Based on Eigenvector
and Eigenvalue Interpolation
Ingrid Hotz1
, Jaya Sreevalsan-Nair1
, Hans Hagen2
, and
Bernd Hamann1
1 Institute for Data Analysis and Visualization (IDAV)
Department of Computer Science, University of California
Davis CA 95616, USA
{ihotz,sreevals,hamann}@cs.ucdavis.edu
2 Computergrafics Lab, University of Kaiserslautern, Germany
hagen@informatik.uni-kl.de
Abstract
Interpolation is an essential step in the visualization process. While most data from simulations
or experiments are discrete many visualization methods are based on smooth, continuous data
approximation or interpolation methods. We introduce a new interpolation method for sym-
metrical tensor fields given on a triangulated domain. Differently from standard tensor field
interpolation, which is based on the tensor components, we use tensor invariants, eigenvectors
and eigenvalues, for the interpolation. This interpolation minimizes the number of eigenvectors
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