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Cited by 282

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Surround-Screen Projection-Based Virtual Reality: The Design and Implementation of the CAVE

Cruz-Neira, Carolina, Sandin, Daniel J., DeFanti, Thomas A.·2023·Seminal Graphics Papers: Pushing the Boundaries, Volume 2

Abstract

This paper describes the CAVE (CAVE Automatic Virtual Environment) virtual reality/scientific visualization system in detail and demonstrates that projection technology applied to virtual-reality goals achieves a system that matches the quality of workstation screens in terms of resolution, color, and flicker-free stereo. In addition, this format helps reduce the effect of common tracking and system latency errors. The off-axis perspective projection techniques we use are shown to be simple and straightforward. Our techniques for doing multi-screen stereo vision are enumerated, and design barriers, past and current, are described. Advantages and disadvantages of the projection paradigm are discussed, with an analysis of the effect of tracking noise and delay on the user. Successive refinement, a necessary tool for scientific visualization, is developed in the virtual reality context. The use of the CAVE as a one-to-many presentation device at SIGGRAPH '92 and Supercomputing '92 for computational science data is also mentioned.

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Metadata

Authors
Cruz-Neira, C., Sandin, D. J., & DeFanti, T. A.
Venue
Seminal Graphics Papers: Pushing the Boundaries, Volume 2
Publisher
ACM
Published
2023-08
Pages
51-58
OpenAlex
W4385484117
Cited by
282
References
3
FWCI
51.38
Type
book chapter
Language
en
Open access
closed

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CoChat. (2026). Citation check: Surround-Screen Projection-Based Virtual Reality: The Design and Implementation of the CAVE. https://app.cochat.ai/papers/10.1145/3596711.3596718
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Cruz-Neira, C., Sandin, D. J., & DeFanti, T. A. (2023). Surround-Screen Projection-Based Virtual Reality: The Design and Implementation of the CAVE. Seminal Graphics Papers: Pushing the Boundaries, Volume 2. https://doi.org/10.1145/3596711.3596718

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.