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PassNet

Deep learning for automatic detection of soccer events from broadcasted video

Soccer analytics is attracting increasing interest in academia and industry, thanks to the availability of data that describe all the spatio-temporal events that occur in each match. These events (e.g., passes, shots, fouls) are collected by human operators manually, con- stituting a considerable cost for data providers in terms of time and economic resources. In this paper, we describe PassNet, a method to rec- ognize the most frequent events in soccer, i.e., passes, from video streams. Our model combines a set of artificial neural networks that perform fea- ture extraction from video streams, object detection to identify the posi- tions of the ball and the players, and classification of frame sequences as passes or not passes. We test PassNet on different scenarios, depending on the similarity of conditions to the match used for training. Our results show good classification results and significant improvement in the accu- racy of pass detection with respect to baseline classifiers, even when the match’s video conditions of the test and training sets are considerably different. PassNet is the first step towards an automated event annota- tion system that may break the time and the costs for event annotation, enabling data collections for minor and non-professional divisions, youth leagues and, in general, competitions whose matches are not currently annotated by data providers.

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Additional Info
Field Value
Accessibility Both
AccessibilityMode Download
Availability On-Line
Basic rights Download
CreationDate 2021-05-24
Creator Cintia, Paolo, paolo.cintia@gmail.com, orcid.org/0000-0002-8085-9338
Field/Scope of use Research only
Group Health Studies
Owner Cintia, Paolo, paolo.cintia@gmail.com, orcid.org/0000-0002-8085-9338
ProgrammingLanguage Python
RelatedPaper https://bitbucket.org/ghentdatascience/ecmlpkdd20-papers/raw/master/ADS/sub_1083.pdf
Sublicense rights No
Territory of use World Wide
Thematic Cluster Other
system:type Method
Management Info
Field Value
Source https://github.com/jonpappalord/PassNet
Author Cintia Paolo
Maintainer Cintia Paolo
Version 1
Last Updated 12 September 2023, 09:18 (CEST)
Created 24 May 2021, 13:02 (CEST)