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Combining Qualitative and Quantitative Analysis in Football with SportSense
ConferencePaper (Artikel, die in Tagungsbänden erschienen sind)
 
ID 4523930
Author(s) Seidenschwarz, Philipp; Jonsson, Adalsteinn; Rauschenbach, Fabian; Rumo, Martin; Probst, Lukas; Schuldt, Heiko
Author(s) at UniBasel Schuldt, Heiko
Seidenschwarz, Philipp German
Probst, Lukas
Year 2019
Title Combining Qualitative and Quantitative Analysis in Football with SportSense
Book title (Conference Proceedings) Proceedings of the 2nd International Workshop on Multimedia Content Analysis in Sports
Place of Conference Nice, France
Publisher ACM
Pages 34-41
ISSN/ISBN 978-1-4503-6911-4
Abstract The task of performance analysts and coaches in football (and other team sports) is manifold: they need to assess the performance of individual players of their team, they need to monitor the interaction between players of their team and their tactical compliance, and they need to analyze other teams. For this, they usually have to consider various sources of information: video footage, tracking data, event data, and aggregated statistics. On the basis of this information, analysts have to generate quantitative summaries of events including their spatial and temporal distribution, and the qualitative assessment of individual events by considering the associated video footage. In this paper, we present SportSense, a system for sports video retrieval, that seamlessly combines quantitative and qualitative analysis. For this, SportSense provides dedicated filters that help analysts in selecting the events they are interested in. Moreover, it supports the comparative analysis of stored queries with respect to specific parameters. Essentially, SportSense allows to easily switch between qualitative and quantitative analyses to support coaches and analysts in a best possible way in their task. Based on a user study, we show the effectiveness of the proposed approach.
URL https://doi.org/10.1145/3347318.3355519
edoc-URL https://edoc.unibas.ch/73836/
Full Text on edoc No
Digital Object Identifier DOI 10.1145/3347318.3355519
 
   

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