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ISPRS Int. J. Geo-Inf. 2016, 5(11), 208; doi:10.3390/ijgi5110208

Recognition of Repetitive Movement Patterns—The Case of Football Analysis

Institute for Cartography and Geoinformatics, Leibniz University Hanover, Appelstraße 9a, Hannover 30167, Germany
Academic Editor: Wolfgang Kainz
Received: 9 September 2016 / Revised: 28 October 2016 / Accepted: 7 November 2016 / Published: 9 November 2016
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Abstract

Analyzing sports like football is interesting not only for the sports team itself, but also for the public and the media. Both have recognized that using more detailed analyses of the teams’ behavior increases their attractiveness and also their performance. For this reason, the games and the individual players are recorded using specially developed tracking systems. The tracking solution usually comes with elementary analysis software allowing for basic statistical information extraction. Going beyond these simple statistics is a challenging task. However, it is worthwhile when it provides a better view into the tactics of team or the typical movements of an individual player. In this paper an approach for the recognition of movement patterns as an advanced analysis method is presented, which uses the players’ trajectories as input data. Besides individual movement patterns it is also able to detect patterns in relation to group movements. A detailed description is followed by a discussion of the approach, where different experiments on real trajectory datasets, even from other contexts than football, show the method’s benefits and features. View Full-Text
Keywords: spatio-temporal analysis; pattern recognition; trajectory; football analysis spatio-temporal analysis; pattern recognition; trajectory; football analysis
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Feuerhake, U. Recognition of Repetitive Movement Patterns—The Case of Football Analysis. ISPRS Int. J. Geo-Inf. 2016, 5, 208.

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