Bernard, JürgenDobermann, EduardBögl, MarkusRöhlig, MartinVögele, AnnaKohlhammer, JörnNatalia Andrienko and Michael Sedlmair2016-06-092016-06-092016978-3-03868-016-1-https://diglib.eg.org/handle/10.2312/eurova20161121https://doi.org/10.2312/eurova.20161121Choosing 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.I.3.6 [Computer Graphics]Methodology and TechniquesInteraction techniques10.2312/eurova.2016112131-35