Congdon, Ben J;
Steed, Anthony;
(2023)
Monte-Carlo Redirected Walking: Gain Selection Through Simulated Walks.
IEEE Transactions on Visualization and Computer Graphics
pp. 1-10.
10.1109/tvcg.2023.3247093.
(In press).
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Abstract
We present Monte-Carlo Redirected Walking (MCRDW), a gain selection algorithm for redirected walking. MCRDW applies the Monte-Carlo method to redirected walking by simulating a large number of simple virtual walks, then inversely applying redirection to the virtual paths. Different gain levels and directions are applied, producing differing physical paths. Each physical path is scored and the results used to select the best gain level and direction. We provide a simple example implementation and a simulation-based study for validation. In our study, when compared with the next best technique, MCRDW reduced incidence of boundary collisions by over 50% while reducing total rotation and position gain.
| Type: | Article |
|---|---|
| Title: | Monte-Carlo Redirected Walking: Gain Selection Through Simulated Walks |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/tvcg.2023.3247093 |
| Publisher version: | https://doi.org/10.1109/TVCG.2023.3247093 |
| Language: | English |
| Additional information: | © 2023 IEEE. This work is licensed under a Creative Commons “Attribution 4.0 International” license (https://creativecommons.org/licenses/by/4.0/deed.en). |
| Keywords: | Virtual reality, human computer interaction, redirected walking |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10165842 |
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