XR training and gameplay 6DoF mobility dataset ...
User mobility in extended reality (XR) can have a major impact on millimeter-wave (mmWave) links and may require dedicated mitigation strategies to ensure reliable connections and avoid service outages. The available prior art has predominantly focused on XR applications with constrained user mobili...
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Online Access: | https://dx.doi.org/10.5281/zenodo.10210058 https://zenodo.org/doi/10.5281/zenodo.10210058 |
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ftdatacite:10.5281/zenodo.10210058 2024-04-28T08:40:53+00:00 XR training and gameplay 6DoF mobility dataset ... De Kunst, Sam Marinšek Alexander Callebaut, Gilles De Strycker, Lieven Van der Perre, Liesbet 2023 https://dx.doi.org/10.5281/zenodo.10210058 https://zenodo.org/doi/10.5281/zenodo.10210058 unknown Zenodo https://dx.doi.org/10.5281/zenodo.8224632 Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 virtual reality extended reality vive tundra body tracking steamvr openvr vr xr mobility tracking data head-mounted display dataset Dataset 2023 ftdatacite https://doi.org/10.5281/zenodo.1021005810.5281/zenodo.8224632 2024-04-02T11:43:35Z User mobility in extended reality (XR) can have a major impact on millimeter-wave (mmWave) links and may require dedicated mitigation strategies to ensure reliable connections and avoid service outages. The available prior art has predominantly focused on XR applications with constrained user mobility and limited impact on mmWave channels. We have performed dedicated experiments to extend the characterisation of relevant future XR use cases featuring a high degree of user mobility. To this end, we have carried out a tailor-made measurement campaign. For a description, for analysis results, and for citing the dataset, view [coming soon] ... : Compiled tracking data into a single dataset. We recommend using Xarray and Dask for opening the tracking and controller input data, stored in `cacerumd.h5` and `cacerumdcontroller.h5`, respectively. Dask allows for lazy loading (without occupying memory), while Xarray is handy in manipulating the multi-dimensional data. The file `cacerumd_continuous_intervals.csv` describes the intervals on which data is continuously sampled at 250 Hz. The supplied photo, `cacerumd.png` shows a user conducting the T-pose in the measurement environment. ... Dataset Tundra DataCite Metadata Store (German National Library of Science and Technology) |
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Open Polar |
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DataCite Metadata Store (German National Library of Science and Technology) |
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unknown |
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virtual reality extended reality vive tundra body tracking steamvr openvr vr xr mobility tracking data head-mounted display |
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virtual reality extended reality vive tundra body tracking steamvr openvr vr xr mobility tracking data head-mounted display De Kunst, Sam Marinšek Alexander Callebaut, Gilles De Strycker, Lieven Van der Perre, Liesbet XR training and gameplay 6DoF mobility dataset ... |
topic_facet |
virtual reality extended reality vive tundra body tracking steamvr openvr vr xr mobility tracking data head-mounted display |
description |
User mobility in extended reality (XR) can have a major impact on millimeter-wave (mmWave) links and may require dedicated mitigation strategies to ensure reliable connections and avoid service outages. The available prior art has predominantly focused on XR applications with constrained user mobility and limited impact on mmWave channels. We have performed dedicated experiments to extend the characterisation of relevant future XR use cases featuring a high degree of user mobility. To this end, we have carried out a tailor-made measurement campaign. For a description, for analysis results, and for citing the dataset, view [coming soon] ... : Compiled tracking data into a single dataset. We recommend using Xarray and Dask for opening the tracking and controller input data, stored in `cacerumd.h5` and `cacerumdcontroller.h5`, respectively. Dask allows for lazy loading (without occupying memory), while Xarray is handy in manipulating the multi-dimensional data. The file `cacerumd_continuous_intervals.csv` describes the intervals on which data is continuously sampled at 250 Hz. The supplied photo, `cacerumd.png` shows a user conducting the T-pose in the measurement environment. ... |
format |
Dataset |
author |
De Kunst, Sam Marinšek Alexander Callebaut, Gilles De Strycker, Lieven Van der Perre, Liesbet |
author_facet |
De Kunst, Sam Marinšek Alexander Callebaut, Gilles De Strycker, Lieven Van der Perre, Liesbet |
author_sort |
De Kunst, Sam |
title |
XR training and gameplay 6DoF mobility dataset ... |
title_short |
XR training and gameplay 6DoF mobility dataset ... |
title_full |
XR training and gameplay 6DoF mobility dataset ... |
title_fullStr |
XR training and gameplay 6DoF mobility dataset ... |
title_full_unstemmed |
XR training and gameplay 6DoF mobility dataset ... |
title_sort |
xr training and gameplay 6dof mobility dataset ... |
publisher |
Zenodo |
publishDate |
2023 |
url |
https://dx.doi.org/10.5281/zenodo.10210058 https://zenodo.org/doi/10.5281/zenodo.10210058 |
genre |
Tundra |
genre_facet |
Tundra |
op_relation |
https://dx.doi.org/10.5281/zenodo.8224632 |
op_rights |
Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 |
op_doi |
https://doi.org/10.5281/zenodo.1021005810.5281/zenodo.8224632 |
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1797571368332558336 |