Computing and Visualizing Time-Varying Merge Trees for High-Dimensional Data View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2017

AUTHORS

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

ABSTRACT

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. More... »

PAGES

87-101

References to SciGraph publications

  • 2009. Isocontour based Visualization of Time-varying Scalar Fields in MATHEMATICAL FOUNDATIONS OF SCIENTIFIC VISUALIZATION, COMPUTER GRAPHICS, AND MASSIVE DATA EXPLORATION
  • 2010-09-14. Feature Tracking Using Reeb Graphs in TOPOLOGICAL METHODS IN DATA ANALYSIS AND VISUALIZATION
  • 2002-11. Topological Persistence and Simplification in DISCRETE & COMPUTATIONAL GEOMETRY
  • 2001-02. Visualization of time-dependent data with feature tracking and event detection in THE VISUAL COMPUTER
  • Book

    TITLE

    Topological Methods in Data Analysis and Visualization IV

    ISBN

    978-3-319-44682-0
    978-3-319-44684-4

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-319-44684-4_5

    DOI

    http://dx.doi.org/10.1007/978-3-319-44684-4_5

    DIMENSIONS

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