Single Image, Context Aware Action Estimation in Sports

Christian Lanius, Daisuke Kobayashi, Kazushige Ouchi, Yoshimitsu Aoki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Sports video analysis enables professional teams to prepare and practice more efficiently than ever before. It allows the team to work on their weak points and analyze upcoming opponents' strategies. As segmentation is a well researched topic, we assume a sports video where each frame is segmented into actors. We show that the location of the actors is correlated to their action. We develop a model to predict each actor's action in a context consistent and location aware manner. The set of context actors is an unordered set, thus we propose a permutation invariant structure for our classifier. We evaluate a location and a context aware network for single image sports action recognition on two datasets. One is an existing dataset of volleyball games. We present a new dataset for actor recognition in rugby. We compare the results to using only the image of the actor.

Original languageEnglish
Title of host publicationProceedings - 14th International Conference on Signal Image Technology and Internet Based Systems, SITIS 2018
EditorsRichard Chbeir, Gabriella Sanniti di Baja, Luigi Gallo, Kokou Yetongnon, Albert Dipanda, Modesto Castrillon-Santana
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages664-671
Number of pages8
ISBN (Electronic)9781538693858
DOIs
Publication statusPublished - 2018 Jul 2
Event14th International Conference on Signal Image Technology and Internet Based Systems, SITIS 2018 - Las Palmas de Gran Canaria, Spain
Duration: 2018 Nov 262018 Nov 29

Publication series

NameProceedings - 14th International Conference on Signal Image Technology and Internet Based Systems, SITIS 2018

Conference

Conference14th International Conference on Signal Image Technology and Internet Based Systems, SITIS 2018
CountrySpain
CityLas Palmas de Gran Canaria
Period18/11/2618/11/29

Keywords

  • Context
  • Deep-learning
  • Sports action recognition

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition

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