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Cited by 411

The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.

Does the Quality of the Computer Graphics Matter when Judging Distances in Visually Immersive Environments?

Thompson, William B., Willemsen, Peter, Gooch, Amy A., Creem-Regehr, Sarah H., Loomis, Jack M., Beall, Andrew C.·2004·Presence: Teleoperators and Virtual Environments

Abstract

In the real world, people are quite accurate in judging distances to locations in the environment, at least for targets resting on the ground plane and distances out to about 20 m. Distance judgments in visually immersive environments are much less accurate. Several studies have now shown that in visually immersive environments, the world appears significantly smaller than intended. This study investigates whether or not the compression in apparent distances is the result of the low-quality computer graphics utilized in previous investigations. Visually directed triangulated walking was used to assess distance judgments in the real world and in three virtual environments with graphical renderings of varying quality.

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Metadata

Authors
Thompson, W. B., Willemsen, P., Gooch, A. A., Creem-Regehr, S. H., Loomis, J. M., & Beall, A. C.
Venue
Presence: Teleoperators and Virtual Environments
Published
2004-10
Volume
13
Issue
5
Pages
560-571
ISSN
1054-7460 (ISSN-L)
OpenAlex
W1973401283
Cited by
411
References
26
FWCI
29.94
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Does the Quality of the Computer Graphics Matter when Judging Distances in Visually Immersive Environments? https://app.cochat.ai/papers/10.1162/1054746042545292
The paper
Thompson, W. B., Willemsen, P., Gooch, A. A., Creem-Regehr, S. H., Loomis, J. M., & Beall, A. C. (2004). Does the Quality of the Computer Graphics Matter when Judging Distances in Visually Immersive Environments? Presence: Teleoperators and Virtual Environments. https://doi.org/10.1162/1054746042545292

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