Computing and visualizing time-varying merge trees for high-dimensional data

Oesterling, Patrick; Heine, Christian; Weber, Gunther H.; Morozov, Dmitry; Scheuermann, Gerik

doi:10.1007/978-3-319-44684-4_5

Title: Computing and visualizing time-varying merge trees for high-dimensional data

Book · Sat Jun 03 00:00:00 EDT 2017

DOI:https://doi.org/10.1007/978-3-319-44684-4_5· OSTI ID:1393102

Oesterling, Patrick ^[1]; Heine, Christian ^[2]; Weber, Gunther H. ^[3]; Morozov, Dmitry ^[3]; Scheuermann, Gerik ^[1]

Univ. of Leipzig (Germany)
Univ. of Kaiserslautern (Germany)
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

We introduce a new method that identifies and tracks features in arbitrary dimensions using the merge tree -- a structure for identifying topological features based on thresholding in scalar fields. This method analyzes the evolution of features of the function by tracking changes in the merge tree and relates features by matching subtrees between consecutive time steps. Using the time-varying merge tree, we present a structural visualization of the changing function that illustrates both features and their temporal evolution. We demonstrate the utility of our approach by applying it to temporal cluster analysis of high-dimensional point clouds.

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Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)

DOE Contract Number:: AC02-05CH11231

OSTI ID:: 1393102

Resource Relation:: Related Information: Book Title: Mathematics and Visualization

Country of Publication:: United States

Language:: English

References (22)

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