Exploring Gesture Interaction in Underwater Virtual Reality

An underwater virtual reality (UVR) system with gesture-based controls was developed to facilitate navigation and interaction while submerged. The system uses a waterproof head-mounted display and camera-based gesture recognition, originally trained for above-water conditions, employing three gestures: grab for navigation, pinch for single interactions, and point for continuous interactions. In an experimental study, we tested gesture recognition both above and underwater, and evaluated participant interaction within an immersive underwater scene. Results showed that underwater conditions slightly affected gesture accuracy, but the system maintained high performance. Participants reported a strong sense of presence and found the gestures intuitive while highlighting the need for further refinement to address usability challenges.

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Published
2024-09-13
DOI
https://doi.org/10.1145/3677386.3688890
Primary Topic
Hand Gesture Recognition Systems
Type
article
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article

Exploring Gesture Interaction in Underwater Virtual Reality

Kiyoshi Kiyokawa, Alexander Marquardt, Ernst Kruijff, Felix Dollack et al.
Hand Gesture Recognition Systems
article

Exploring Gesture Interaction in Underwater Virtual Reality

Kiyoshi Kiyokawa, Alexander Marquardt, Ernst Kruijff, Felix Dollack, Hideaki Uchiyama, Monica Perusquía-Hernández, Melissa Steininger, Marvin Lehnort, Hiromu Otsubo
article en

Abstract

An underwater virtual reality (UVR) system with gesture-based controls was developed to facilitate navigation and interaction while submerged. The system uses a waterproof head-mounted display and camera-based gesture recognition, originally trained for above-water conditions, employing three gestures: grab for navigation, pinch for single interactions, and point for continuous interactions. In an experimental study, we tested gesture recognition both above and underwater, and evaluated participant interaction within an immersive underwater scene. Results showed that underwater conditions slightly affected gesture accuracy, but the system maintained high performance. Participants reported a strong sense of presence and found the gestures intuitive while highlighting the need for further refinement to address usability challenges.

Hochschule Bonn-Rhein-Sieg (DE), Simon Fraser University (CA), Nara Institute of Science and Technology (JP)
Openalex Percentile: Top 85%
Hand Gesture Recognition Systems
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