Visual-Interactive Segmentation of Multivariate Time Series

dc.contributor.authorBernard, Jürgenen_US
dc.contributor.authorDobermann, Eduarden_US
dc.contributor.authorBögl, Markusen_US
dc.contributor.authorRöhlig, Martinen_US
dc.contributor.authorVögele, Annaen_US
dc.contributor.authorKohlhammer, Jörnen_US
dc.contributor.editorNatalia Andrienko and Michael Sedlmairen_US
dc.date.accessioned2016-06-09T09:32:10Z
dc.date.available2016-06-09T09:32:10Z
dc.date.issued2016en_US
dc.description.abstractChoosing 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.en_US
dc.description.sectionheadersTemporal Data Analysisen_US
dc.description.seriesinformationEuroVis Workshop on Visual Analytics (EuroVA)en_US
dc.identifier.doi10.2312/eurova.20161121en_US
dc.identifier.isbn978-3-03868-016-1en_US
dc.identifier.issn-en_US
dc.identifier.pages31-35en_US
dc.identifier.urihttps://diglib.eg.org/handle/10.2312/eurova20161121
dc.identifier.urihttps://doi.org/10.2312/eurova.20161121en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectI.3.6 [Computer Graphics]en_US
dc.subjectMethodology and Techniquesen_US
dc.subjectInteraction techniquesen_US
dc.titleVisual-Interactive Segmentation of Multivariate Time Seriesen_US
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