The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Estimation of Detection Thresholds for Redirected Walking Techniques
Abstract
In immersive virtual environments (IVEs), users can control their virtual viewpoint by moving their tracked head and walking through the real world. Usually, movements in the real world are mapped one-to-one to virtual camera motions. With redirection techniques, the virtual camera is manipulated by applying gains to user motion so that the virtual world moves differently than the real world. Thus, users can walk through large-scale IVEs while physically remaining in a reasonably small workspace. In psychophysical experiments with a two-alternative forced-choice task, we have quantified how much humans can unknowingly be redirected on physical paths that are different from the visually perceived paths. We tested 12 subjects in three different experiments: (E1) discrimination between virtual and physical rotations, (E2) discrimination between virtual and physical straightforward movements, and (E3) discrimination of path curvature. In experiment E1, subjects performed rotations with different gains, and then had to choose whether the visually perceived rotation was smaller or greater than the physical rotation. In experiment E2, subjects chose whether the physical walk was shorter or longer than the visually perceived scaled travel distance. In experiment E3, subjects estimate the path curvature when walking a curved path in the real world while the visual display shows a straight path in the virtual world. Our results show that users can be turned physically about 49 percent more or 20 percent less than the perceived virtual rotation, distances can be downscaled by 14 percent and upscaled by 26 percent, and users can be redirected on a circular arc with a radius greater than 22 m while they believe that they are walking straight.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Berthoz, A., Pavard, B., & Young, L. R. (1975) · Experimental Brain Research · doi:10.1007/bf00234916 · Cited by 456
Perception of self-motion from visual flow
Lappe, M., Bremmer, F., & van den Berg, A. V. (1999) · Trends in Cognitive Sciences · doi:10.1016/s1364-6613(99)01364-9 · Cited by 430
Self-citation
Cited by
Haptic Retargeting: Dynamic Repurposing of Passive Haptics for Enhanced Virtual Reality Experiences
Azmandian, M., Hancock, M., Benko, H., Ofek, E., & Wilson, A. D. (2016) · Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems · doi:10.1145/2858036.2858226 · Cited by 499
Langbehn, E., Lubos, P., & Steinicke, F. (2018) · Proceedings of the Virtual Reality International Conference - Laval Virtual · doi:10.1145/3234253.3234291 · Cited by 253
Self-citationRagan, E. D., Scerbo, S., Bacim, F., & Bowman, D. A. (2017) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2016.2601607 · Cited by 90
Memory Manipulations in Extended Reality
Bonnail, E., Tseng, W.-J., Mcgill, M., Lecolinet, E., Huron, S., & Gugenheimer, J. (2023) · Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3580988 · Cited by 51
Scene-motion thresholds during head yaw for immersive virtual environments
Jerald, J., Whitton, M., & Brooks, F. P. (2012) · ACM Transactions on Applied Perception · doi:10.1145/2134203.2134207 · Cited by 15
Self-citation
Metadata
- Authors
- Steinicke, F., Bruder, G., Jerald, J., Frenz, H., & Lappe, M.
- Venue
- IEEE Transactions on Visualization and Computer Graphics
- Published
- 2010-01
- Volume
- 16
- Issue
- 1
- Pages
- 17-27
- ISSN
- 1077-2626 (ISSN-L)
- OpenAlex
- W2110738137
- Cited by
- 635
- References
- 2
- FWCI
- 15.80
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Estimation of Detection Thresholds for Redirected Walking Techniques. https://app.cochat.ai/papers/10.1109/tvcg.2009.62
- The paper
- Steinicke, F., Bruder, G., Jerald, J., Frenz, H., & Lappe, M. (2010). Estimation of Detection Thresholds for Redirected Walking Techniques. IEEE Transactions on Visualization and Computer Graphics. https://doi.org/10.1109/tvcg.2009.62
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.