Dynamic Visual Abstraction of Soccer Movement


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SACHA, Dominik, Feeras AL-MASOUDI, Manuel STEIN, Tobias SCHRECK, Daniel KEIM, Gennady ANDRIENKO, Halldór JANETZKO, 2017. Dynamic Visual Abstraction of Soccer Movement. Eurographics Conference on Visualization (EuroVis) 2017. Barcelona, 12. Jun 2017 - 16. Jun 2017. In: HEER, Jeffrey, ed. and others. EuroVis 2017 Eurographics / IEEE VGTC Conference on Visualization 2017. Eurographics Conference on Visualization (EuroVis) 2017. Barcelona, 12. Jun 2017 - 16. Jun 2017, pp. 305-315. ISSN 0167-7055. eISSN 1467-8659

@inproceedings{Sacha2017-07-04Dynam-39673, title={Dynamic Visual Abstraction of Soccer Movement}, year={2017}, doi={10.1111/cgf.13189}, number={36,3}, issn={0167-7055}, series={Computer Graphics Forum}, booktitle={EuroVis 2017 Eurographics / IEEE VGTC Conference on Visualization 2017}, pages={305--315}, editor={Heer, Jeffrey}, author={Sacha, Dominik and Al-Masoudi, Feeras and Stein, Manuel and Schreck, Tobias and Keim, Daniel and Andrienko, Gennady and Janetzko, Halldór} }

<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bibo="http://purl.org/ontology/bibo/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > <rdf:Description rdf:about="https://kops.uni-konstanz.de/rdf/resource/123456789/39673"> <dc:creator>Stein, Manuel</dc:creator> <dc:contributor>Janetzko, Halldór</dc:contributor> <dc:contributor>Al-Masoudi, Feeras</dc:contributor> <dc:creator>Andrienko, Gennady</dc:creator> <dc:contributor>Sacha, Dominik</dc:contributor> <dc:creator>Al-Masoudi, Feeras</dc:creator> <dc:contributor>Andrienko, Gennady</dc:contributor> <dcterms:title>Dynamic Visual Abstraction of Soccer Movement</dcterms:title> <dc:creator>Schreck, Tobias</dc:creator> <dc:language>eng</dc:language> <dc:contributor>Stein, Manuel</dc:contributor> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2017-07-27T08:33:48Z</dc:date> <dcterms:rights rdf:resource="http://nbn-resolving.de/urn:nbn:de:bsz:352-20150914100631302-4485392-8"/> <dcterms:abstract xml:lang="eng">Trajectory-based visualization of coordinated movement data within a bounded area, such as player and ball movement within a soccer pitch, can easily result in visual crossings, overplotting, and clutter. Trajectory abstraction can help to cope with these issues, but it is a challenging problem to select the right level of abstraction (LoA) for a given data set and analysis task. We present a novel dynamic approach that combines trajectory simplification and clustering techniques with the goal to support interpretation and understanding of movement patterns. Our technique provides smooth transitions between different abstraction types that can be computed dynamically and on-the-fly. This enables the analyst to effectively navigate and explore the space of possible abstractions in large trajectory data sets. Additionally, we provide a proof of concept for supporting the analyst in determining the LoA semi-automatically with a recommender system. Our approach is illustrated and evaluated by case studies, quantitative measures, and expert feedback. We further demonstrate that it allows analysts to solve a variety of analysis tasks in the domain of soccer.</dcterms:abstract> <dcterms:issued>2017-07-04</dcterms:issued> <dc:creator>Sacha, Dominik</dc:creator> <dc:creator>Keim, Daniel</dc:creator> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2017-07-27T08:33:48Z</dcterms:available> <dc:contributor>Keim, Daniel</dc:contributor> <dc:creator>Janetzko, Halldór</dc:creator> <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/39673"/> <dc:contributor>Schreck, Tobias</dc:contributor> </rdf:Description> </rdf:RDF>

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