3D global trajectory and multi-view local motion combined player action recognition in volleyball analysis

Yang Liu*, Shuyi Huang, Xina Cheng, Takeshi Ikenaga

*Corresponding author for this work

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

1 Citation (Scopus)


Volleyball video analysis is important for developing applications such as player evaluation system or tactic analysis system. Among its different topics, player action recognition serves as an elementary building brick for understanding player’s behavior. Most conventional player action recognition methods have limits in real volleyball game due to the occlusion and intra-class variation problems. This paper proposes a 3D global trajectory and multi-view local motion combined volleyball player action recognition method. 3D global trajectory extracts global motion feature through 3D trajectories, which hides the unstable and incomplete 2D motion feature caused by the above problems. Multi-view local motion gets detailed local motion feature of arms and legs in multiple viewpoints and removes clutter features caused by occlusion problem. Through the combination, global 3D feature and local motion feature mutually promote each other and the actions are recognized well. Experiments are conducted on game videos from the Semifinal and Final Game of 2014 Japan Inter High School Games of Men’s Volleyball in Tokyo Metropolitan Gymnasium. The experiments show the combing result accuracy achieves 98.39%, 95.50%, 96.86%, 96.98% for spike, block, receive, toss respectively and improve 11.33% averagely than the sing-view local motion based result.

Original languageEnglish
Title of host publicationAdvances in Multimedia Information Processing – PCM 2018 - 19th Pacific-Rim Conference on Multimedia, 2018, Proceedings
EditorsChong-Wah Ngo, Toshihiko Yamasaki, Richang Hong, Meng Wang, Wen-Huang Cheng
PublisherSpringer Verlag
Number of pages11
ISBN (Print)9783030007638
Publication statusPublished - 2018
Event19th Pacific-Rim Conference on Multimedia, PCM 2018 - Hefei, China
Duration: 2018 Sept 212018 Sept 22

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11166 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other19th Pacific-Rim Conference on Multimedia, PCM 2018


  • Intra-class variation
  • Occlusion
  • Player action recognition
  • Volleyball analysis

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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