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    Visual-Interactive Segmentation of Multivariate Time Series

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    Date
    2016
    Author
    Bernard, Jürgen
    Dobermann, Eduard
    Bögl, Markus
    Röhlig, Martin
    Vögele, Anna
    Kohlhammer, Jörn
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    Abstract
    Choosing appropriate time series segmentation algorithms and relevant parameter values is a challenging problem. In order to choose meaningful candidates it is important that different segmentation results are comparable. We propose a Visual Analytics (VA) approach to address these challenges in the scope of human motion capture data, a special type of multivariate time series data. In our prototype, users can interactively select from a rich set of segmentation algorithm candidates. In an overview visualization, the results of these segmentations can be compared and adjusted with regard to visualizations of raw data. A similarity-preserving colormap further facilitates visual comparison and labeling of segments. We present our prototype and demonstrate how it can ease the choice of winning candidates from a set of results for the segmentation of human motion capture data.
    BibTeX
    @inproceedings {eurova.20161121,
    booktitle = {EuroVis Workshop on Visual Analytics (EuroVA)},
    editor = {Natalia Andrienko and Michael Sedlmair},
    title = {{Visual-Interactive Segmentation of Multivariate Time Series}},
    author = {Bernard, Jürgen and Dobermann, Eduard and Bögl, Markus and Röhlig, Martin and Vögele, Anna and Kohlhammer, Jörn},
    year = {2016},
    publisher = {The Eurographics Association},
    ISSN = {-},
    ISBN = {978-3-03868-016-1},
    DOI = {10.2312/eurova.20161121}
    }
    URI
    http://dx.doi.org/10.2312/eurova.20161121
    https://diglib.eg.org:443/handle/10
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    Eurographics Association copyright © 2013 - 2020 
    Send Feedback | Contact - Imprint | Data Privacy Policy | Disable Google Analytics
    Theme by @mire NV
    System hosted at  Graz University of Technology.
    TUGFhA