Player falling detection in soccer matches video

Ramana ORUGANTI, Roland GOECKE

Research output: A Conference proceeding or a Chapter in BookConference contributionpeer-review

Abstract

In recent years, most sports such as Soccer are recorded during the actual game and analysed later on by the coaches for training their teams to perform better in the future. The training can be in several aspects such as avoiding fouls,
injuries, improving passes and tactics. Automatic detection/retrieval of such specific events from the video database will be of great assistance to the coaches. In this paper, we analyse Soccer match videos with the objective to detect two events – players playing or falling. Player falling, often leading to injury can be costly for the players’ health and also the team performance as a whole.
Original languageEnglish
Title of host publicationProceedings of the large scale sports analysis workshop, 21st ACM SIGKDD Conference on knowledge discovery and data mining
EditorsThornsten Joachims, Geoff Webb
Place of PublicationSydney
PublisherAssociation for Computing Machinery (ACM)
Pages1-4
Number of pages4
Volume1
ISBN (Print)9781450336642
Publication statusPublished - 2015
Event21st ACM SIGKDD Conference on knowledge discovery and data mining - Sydney, Sydney, Australia
Duration: 10 Aug 201513 Aug 2015
http://www.kdd.org/kdd2015/ (Conference detail)

Conference

Conference21st ACM SIGKDD Conference on knowledge discovery and data mining
Abbreviated titleKDD 2015
Country/TerritoryAustralia
CitySydney
Period10/08/1513/08/15
Internet address

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