Video Annotation Tool using Human Pose Estimation for Sports Training

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2 Citations (Scopus)


This paper presents and discusses the integration of human pose estimation techniques into an existing web-based multimodal video annotation tool, applying it to the sports context, where basketball is the first case study. The relevance of video analysis extends across many fields of work (e.g., professional sports, education). In sports, systematic, detailed analysis using videos of players and teams is vital to evaluate many aspects of both training and competition. MotionNotes annotation tool now combines human pose and motion information with existing traditional annotation mechanisms (e.g., text and drawings annotations), allowing users to add further details to their annotation work. The paper reports feedback from a pilot study based on a participatory workshop involving people with relevant competitive experience in basketball. Based on this use case feedback, we conclude with an outlook of future iterations for our video annotation tool.

Original languageEnglish
Title of host publicationProceedings of MUM 2022, the 21st International Conference on Mobile and Ubiquitous Multimedia
EditorsTanja Doring, Susanne Boll, Ashley Colley, Augusto Esteves, João Guerreiro
Place of PublicationNew York
PublisherACM - Association for Computing Machinery
Number of pages4
ISBN (Electronic)9781450398213
Publication statusPublished - 27 Nov 2022
Event21st International Conference on Mobile and Ubiquitous Multimedia, MUM 2022 - Lisbon, Portugal
Duration: 27 Nov 202230 Nov 2022

Publication series

NameACM International Conference Proceeding Series
PublisherAssociation for Computing Machinery


Conference21st International Conference on Mobile and Ubiquitous Multimedia, MUM 2022


  • Human Pose and Motion
  • People Tracking
  • Performing Sports
  • Video Analysis
  • Video Annotation


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