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license: cc |
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# BOXRR-23: Berkeley Open Extended Reality Recording Dataset 2023 |
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This is a copy of the official Berkeley Open Extended Reality Recording Dataset 2023 (BOXRR-23). Please visit the [project website](https://rdi.berkeley.edu/metaverse/boxrr-23/) for more information. |
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In `users/` you find one tarball for each user (which you can untar with `tar xvf <path/to/user.tar>`), which includes all replays of that user. Each replay is stored in a dedicated file in the [XROR](https://github.com/MetaGuard/xror) format. |
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## Metadata |
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The entire dataset is around 5 TB large, which can be inconvenient and you might want to only download users you are interested in. |
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For this we have collected the metadata from each recording and dumped it into a BSON file which you find in `metadata/`. You can import this as collection into mongodb to quickly select users and replays to compile a list of the specific files you want to download (the field `user_id` matches the filename in `users/`). |
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## Notes |
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- there are BeatSaber and TiltBrush users, which is noted in the field `info.software.app` in the metadata |
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- BeatSaber uses Unity's coordinate system. For more details (and why these details matter) [have a look at this](https://cschell.github.io/kinematic-maze/) |
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## Tools |
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- you'll need [XROR](https://github.com/MetaGuard/xror) to open the individual replays |
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- for an example script that imports and converts the motion data, you might find the ["XR Motion Dataset Conversion Scrips"](https://cschell.github.io/kinematic-maze/) useful, which include a conversion script for BOXRR-23 (you need to unpack each user first). |
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- also, there is the [Motion Learning Toolbox](https://github.com/cschell/Motion-Learning-Toolbox) for further preprocessing of motion data |
