Visual-Interactive Segmentation of Multivariate Time Series
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Date
2016
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
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.
Description
@inproceedings{10.2312: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}
}