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Results of measuring immersion in a cricket simulation game for improved VR with real-time time-of-flight performance capture

Research Output: Chapter in Book/Report/Conference proceeding Conference contribution Peer-review

Abstract

The research presented in this paper involves the design and implementation of a system that measured player responses in a virtual reality simulation game by including an innovative improved real-time animated avatar feature. The research was conducted on the notion that an avatar animated using real-time motion capture would enhance the player's immersion by increasing their sense of presence. When playing VR games that were commercially available, it was discovered that the user's avatar (Virtual agent) had a limited character and feature set, usually depending on the handset controllers provided with the base system. The inputs from these controllers were observed as inadequate to generate the entire body's animation. This research attempted to solve this problem by implementing full body marker-less motion capture for the improvisation of the user-avatar animation in real-time in a VR game. This was achieved by the implementation of Time-of-flight camera tracking to add positional data to the native PC-VR tracking. A Cricket batting simulation was developed to demonstrate the implementation of the combined tracking for immersive gameplay and replay experience. Hence, this enabled VR users and VR esports spectators to experience a better real-time animated Cricket action. Additionally, the research aimed to measure immersion by improving on the existing measuring techniques (Witmer and Singer, 1998), to measure the immersion by conducting experiments engaging humans to use the system [12]. The research's user-based studies involved collecting both qualitative and quantitative measures from 45 users in 2 phases of experimentation. This improved the immersion measurement by a novel rigorous analysis following Freeman's [14] and Scholerb's [15] method applied to a VR simulation and UI interactions. Data collection was verified by novel concurrency checks to eliminate unreliable user data by repeating and rephrasing the questions in multiple instances. The qualitative findings are briefly discussed in this article.

Publication Information

Output type

Research Output: Chapter in Book/Report/Conference proceeding Conference contribution Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 704-709 (6 pages)

Publication milestones

  • Published - 24/12/2024

Publication status

Published - 24/12/2024

Publisher

Institute of Electrical and Electronics Engineers Inc., United States

Publication series

  • Publication series name: 2024 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering, MetroXRAINE 2024 - Proceedings

ISBN (Print)

9798350378009

ISBN (Electronic)

9798350378009

External Publication IDs

  • handle.net: 10547/626850
  • Scopus: 85216103070

Host publication title

2024 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering, MetroXRAINE 2024 - Proceedings

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