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dc.contributor.authorBeck, Fabianen_US
dc.contributor.authorBurch, Michaelen_US
dc.contributor.authorWeiskopf, Danielen_US
dc.contributor.editorMatthias Hullin and Marc Stamminger and Tino Weinkaufen_US
dc.date.accessioned2016-10-10T08:04:17Z
dc.date.available2016-10-10T08:04:17Z
dc.date.issued2016
dc.identifier.isbn978-3-03868-025-3
dc.identifier.issn-
dc.identifier.urihttp://dx.doi.org/10.2312/vmv.20161342
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/vmv20161342
dc.description.abstractIn sports, large amounts of data are measured and stored with the help of modern sensors and electronic devices. In particular, for endurance sports events, time-varying data are recorded and can be used to analyze the athletes' performance. Finding patterns and issues can help better understand results in sports competitions, which is of interest for the athletes, sports managers, and trainers alike. In this paper, we introduce a matrix-based approach to visually compare similar and dissimilar periods in performances of athletes. We differentiate the performances and visually encode these differences as color-coded matrix cells. The strengths of our approach are illustrated in a case study investigating the performances of two riders in the prologue of Tour de France 2012.en_US
dc.publisherThe Eurographics Associationen_US
dc.titleA Matrix-Based Visual Comparison of Time Series Sports Dataen_US
dc.description.seriesinformationVision, Modeling & Visualization
dc.description.sectionheadersExploring Trees and Time Series
dc.identifier.doi10.2312/vmv.20161342
dc.identifier.pages53-60


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  • VMV16
    ISBN 978-3-03868-025-3

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