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dc.contributor.authorWang, Jiachenen_US
dc.contributor.authorWu, Yihongen_US
dc.contributor.authorZhang, Xiaolongen_US
dc.contributor.authorZeng, Yixinen_US
dc.contributor.authorZhou, Zhengen_US
dc.contributor.authorZhang, Huien_US
dc.contributor.authorXie, Xiaoen_US
dc.contributor.authorWu, Yingcaien_US
dc.contributor.editorBujack, Roxanaen_US
dc.contributor.editorArchambault, Danielen_US
dc.contributor.editorSchreck, Tobiasen_US
dc.date.accessioned2023-06-10T06:16:46Z
dc.date.available2023-06-10T06:16:46Z
dc.date.issued2023
dc.identifier.issn1467-8659
dc.identifier.urihttps://doi.org/10.1111/cgf.14825
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf14825
dc.description.abstractAnticipation skill is important for elite racquet sports players. Successful anticipation allows them to predict the actions of the opponent better and take early actions in matches. Existing studies of anticipation behaviors, largely based on the analysis of in-lab behaviors, failed to capture the characteristics of in-situ anticipation behaviors in real matches. This research proposes a data-driven approach for research on anticipation behaviors to gain more accurate and reliable insight into anticipation skills. Collaborating with domain experts in table tennis, we develop a complete solution that includes data collection, the development of a model to evaluate anticipation behaviors, and the design of a visual analytics system called Tac-Anticipator. Our case study reveals the strengths and weaknesses of top table tennis players' anticipation behaviors. In a word, our work enriches the research methods and guidelines for visual analytics of anticipation behaviors.en_US
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectCCS Concepts: Human-centered computing -> Visual analytics; Information systems -> Data mining
dc.subjectHuman centered computing
dc.subjectVisual analytics
dc.subjectInformation systems
dc.subjectData mining
dc.titleTac-Anticipator: Visual Analytics of Anticipation Behaviors in Table Tennis Matchesen_US
dc.description.seriesinformationComputer Graphics Forum
dc.description.sectionheadersSocial Sciences and Sport
dc.description.volume42
dc.description.number3
dc.identifier.doi10.1111/cgf.14825
dc.identifier.pages223-234
dc.identifier.pages12 pages


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  • 42-Issue 3
    EuroVis 2023 - Conference Proceedings

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