research-article

Exploring Visualizations for Precisely Guiding Bare Hand Gestures in Virtual Reality

Authors:

Ben Lafreniere,

Jian ZhaoAuthors Info & Claims

CHI '24: Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems

Article No.: 636, Pages 1 - 19

https://doi.org/10.1145/3613904.3642935

Published: 11 May 2024 Publication History

Abstract

Bare hand interaction in augmented or virtual reality (AR/VR) systems, while intuitive, often results in errors and frustration. However, existing methods, such as a static icon or a dynamic tutorial, can only inform simple and coarse hand gestures and lack corrective feedback. This paper explores various visualizations for enhancing precise hand interaction in VR. Through a comprehensive two-part formative study with 11 participants, we identified four types of essential information for visual guidance and designed different visualizations that manifest these information types. We further distilled four visual designs and conducted a controlled lab study with 15 participants to assess their effectiveness for various single- and double-handed gestures. Our results demonstrate that visual guidance significantly improved users’ gesture performance, reducing time and workload while increasing confidence. Moreover, we found that the visualization did not disrupt most users’ immersive VR experience or their perceptions of hand tracking and gesture recognition reliability.

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Cited By

Yaseen Kwon OKim JJamil SLee JUllah F(2024)Next-Gen Dynamic Hand Gesture Recognition: MediaPipe, Inception-v3 and LSTM-Based Enhanced Deep Learning ModelElectronics10.3390/electronics1316323313:16(3233)Online publication date: 15-Aug-2024
https://doi.org/10.3390/electronics13163233

Index Terms

Exploring Visualizations for Precisely Guiding Bare Hand Gestures in Virtual Reality
1. Human-centered computing
2. Social and professional topics
  1. Professional topics
    1. History of computing
      1. History of computing theory

Index terms have been assigned to the content through auto-classification.

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CHI '24: Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems

May 2024

18961 pages

ISBN:9798400703300

DOI:10.1145/3613904

Editors:
Florian Floyd Mueller
Monash University
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Penny Kyburz
The Australian National University
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Julie R. Williamson
University of Glasgow
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Corina Sas
Lancaster University
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Max L. Wilson
University of Nottingham
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Phoebe Toups Dugas
Monash University/New Mexico State University
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Irina Shklovski
University of Copenhagen

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Cited By

Yaseen Kwon OKim JJamil SLee JUllah F(2024)Next-Gen Dynamic Hand Gesture Recognition: MediaPipe, Inception-v3 and LSTM-Based Enhanced Deep Learning ModelElectronics10.3390/electronics1316323313:16(3233)Online publication date: 15-Aug-2024
https://doi.org/10.3390/electronics13163233

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