Training assistant: Strengthen your tactical nous with proficient virtual basketball players

Wan Lun Tsai, Min Chun Hu

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

Abstract

Tactic training plays a crucial role in basketball offensive plays. With the aid of virtual reality, we propose a framework to improve the effectiveness and experience of tactic learning. The framework consists of a tactic input device and a wireless VR interaction system, which allows the user to conveniently input target tactic and practice in a high-fidelity circumstance. By the assistance of our VR training system, the user can vividly experience how the tactics are executed by viewing from the a specific player's viewing direction. Additionally, tactic movement guidance, action hint of how to offense aggressively, and virtual defenders are rendered in our system to make the training more realistic. By using the proposed framework, players can strengthen their tactical nous and improve the efficiency of tactic training.

Original languageEnglish
Title of host publicationACM SIGGRAPH 2018 Posters, SIGGRAPH 2018
PublisherAssociation for Computing Machinery, Inc
ISBN (Print)9781450358170
DOIs
Publication statusPublished - 2018 Aug 12
EventACM SIGGRAPH 2018 Posters - International Conference on Computer Graphics and Interactive Techniques, SIGGRAPH 2018 - Vancouver, Canada
Duration: 2018 Aug 122018 Aug 16

Publication series

NameACM SIGGRAPH 2018 Posters, SIGGRAPH 2018

Other

OtherACM SIGGRAPH 2018 Posters - International Conference on Computer Graphics and Interactive Techniques, SIGGRAPH 2018
CountryCanada
CityVancouver
Period18-08-1218-08-16

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All Science Journal Classification (ASJC) codes

  • Computer Graphics and Computer-Aided Design
  • Software

Cite this

Tsai, W. L., & Hu, M. C. (2018). Training assistant: Strengthen your tactical nous with proficient virtual basketball players. In ACM SIGGRAPH 2018 Posters, SIGGRAPH 2018 [a28] (ACM SIGGRAPH 2018 Posters, SIGGRAPH 2018). Association for Computing Machinery, Inc. https://doi.org/10.1145/3230744.3230807