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Topological and Statistical Methods for Complex Data pp 111–124Cite as

3D Symmetric Tensor Fields: What We Know and Where To Go Next

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Part of the book series: Mathematics and Visualization ((MATHVISUAL))

Abstract

Tensor fields are an active research topic in scientific visualization, medical imaging, image processing, and computer graphics. Not only are tensor fields of great importance in many of these domains, they also contain complicated and intriguing structures which make them an interesting subject of study even from a purely theoretical point of view. In this book chapter, we will review some important recent findings about 3D tensors by the research communities and provide our view on the most pressing problems in the study of 3D symmetric tensor fields.

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Author information

Authors and Affiliations

  1. School of Electrical Engineering and Computer Science, 2111 Kelley Engineering Center, Oregon State University, Corvallis, OR, 97331, USA

    Eugene Zhang

  2. School of Electrical Engineering and Computer Science, 3117 Kelley Engineering Center, Oregon State University, Corvallis, OR, 97331, USA

    Yue Zhang

Authors
  1. Eugene Zhang
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  2. Yue Zhang
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Corresponding author

Correspondence to Eugene Zhang .

Editor information

Editors and Affiliations

  1. Sandia National Laboratories, MS 9152, Livermore, California, USA

    Janine Bennett

  2. CEA CESTA, CS 60001, Le Barp CEDEX, France

    Fabien Vivodtzev

  3. School of Computing and SCI Institute, University of Utah, Salt Lake City, Utah, USA

    Valerio Pascucci

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Zhang, E., Zhang, Y. (2015). 3D Symmetric Tensor Fields: What We Know and Where To Go Next. In: Bennett, J., Vivodtzev, F., Pascucci, V. (eds) Topological and Statistical Methods for Complex Data. Mathematics and Visualization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44900-4_7

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