From Movement to Events : Improving Soccer Match Annotations

Stein, Manuel; Seebacher, Daniel; Karge, Tassilo; Polk, Tom; Grossniklaus, Michael; Keim, Daniel A.

From Movement to Events : Improving Soccer Match Annotations

Files

Stein_2-1obn1hbizozoa1.pdf(285.7 KB)

Date

2019

Publication type

Contribution to a conference collection

Publication status

Published

Published in

MultiMedia Modeling : 25th International Conference, MMM 2019, Proceedings, Part I / Kompatsiaris, Ioannis; Huet, Benoit; Mezaris, Vasileios; Gurrin, Cathal; Cheng, Wen-Huang; Vrochidis, Stefanos (ed.). - Cham : Springer International Publishing, 2019. - (Lecture Notes in Computer Science ; 11295). - pp. 130-142. - ISSN 0302-9743. - eISSN 1611-3349. - ISBN 978-3-030-05709-1

Abstract

Match analysis has become an important task in everyday work at professional soccer clubs in order to improve team performance. Video analysts regularly spend up to several days analyzing and summarizing matches based on tracked and annotated match data. Although there already exists extensive capabilities to track the movement of players and the ball from multimedia data sources such as video recordings, there is no capability to sufficiently detect dynamic and complex events within these data. As a consequence, analysts have to rely on manually created annotations, which are very time-consuming and expensive to create. We propose a novel method for the semi-automatic definition and detection of events based entirely on movement data of players and the ball. Incorporating Allen’s interval algebra into a visual analytics system, we enable analysts to visually define as well as search for complex, hierarchical events. We demonstrate the usefulness of our approach by quantitatively comparing our automatically detected events with manually annotated events from a professional data provider as well as several expert interviews. The results of our evaluation show that the required annotation time for complete matches by using our system can be reduced to a few seconds while achieving a similar level of performance.

Subject (DDC)

004 Computer Science

Keywords

Visual analytics, Sport analytics, Event analysis

Conference

MultiMedia Modeling : 25th International Conference, Jan 8, 2019 - Jan 11, 2019, Thessaloniki, Greece

Cite This

ISO 690

STEIN, Manuel, Daniel SEEBACHER, Tassilo KARGE, Tom POLK, Michael GROSSNIKLAUS, Daniel A. KEIM, 2019. From Movement to Events : Improving Soccer Match Annotations. MultiMedia Modeling : 25th International Conference. Thessaloniki, Greece, Jan 8, 2019 - Jan 11, 2019. In: KOMPATSIARIS, Ioannis, ed., Benoit HUET, ed., Vasileios MEZARIS, ed., Cathal GURRIN, ed., Wen-Huang CHENG, ed., Stefanos VROCHIDIS, ed.. MultiMedia Modeling : 25th International Conference, MMM 2019, Proceedings, Part I. Cham:Springer International Publishing, pp. 130-142. ISSN 0302-9743. eISSN 1611-3349. ISBN 978-3-030-05709-1. Available under: doi: 10.1007/978-3-030-05710-7_11

BibTex

@inproceedings{Stein2019Movem-44519,
  year={2019},
  doi={10.1007/978-3-030-05710-7_11},
  title={From Movement to Events : Improving Soccer Match Annotations},
  number={11295},
  isbn={978-3-030-05709-1},
  issn={0302-9743},
  publisher={Springer International Publishing},
  address={Cham},
  series={Lecture Notes in Computer Science},
  booktitle={MultiMedia Modeling : 25th International Conference, MMM 2019, Proceedings, Part I},
  pages={130--142},
  editor={Kompatsiaris, Ioannis and Huet, Benoit and Mezaris, Vasileios and Gurrin, Cathal and Cheng, Wen-Huang and Vrochidis, Stefanos},
  author={Stein, Manuel and Seebacher, Daniel and Karge, Tassilo and Polk, Tom and Grossniklaus, Michael and Keim, Daniel A.}
}

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Bibliography of Konstanz

Yes