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Berkeley Open Extended Reality Recordings 2023 (BOXRR-23): 4.7 Million Motion Capture Recordings from 105,000 XR
IEEE Transactions on Visualization and Computer Graphics
|March 4, 2024
Summary
The BOXRR-23 dataset offers a massive collection of extended reality (XR) motion data, enabling crucial research into XR security and privacy. This large-scale dataset is vital for understanding the implications of motion tracking in immersive technologies.
Area of Science:
- Computer Science
- Human-Computer Interaction
- Data Science
Background:
- Extended reality (XR) devices are rapidly gaining popularity, with motion tracking data central to their functionality.
- Current research into XR data implications (security, privacy, usability) is limited by the lack of large-scale human motion datasets.
Purpose of the Study:
- To introduce the BOXRR-23 dataset, a novel, large-scale collection of human motion capture recordings from XR users.
- To provide a resource for researchers investigating the security, privacy, and usability of XR and metaverse technologies.
Main Methods:
- Collected 4,717,215 motion capture recordings from 105,852 XR device users across over 50 countries.
- Developed and utilized a new, efficient XR Open Recording (XROR) file format for data storage.
Main Results:
- Created BOXRR-23, a dataset over 200 times larger than existing motion capture research datasets.
- Established a comprehensive dataset enabling in-depth analysis of XR user motion data.
Conclusions:
- BOXRR-23 is a foundational resource for advancing research in XR and metaverse technologies.
- The dataset facilitates critical studies on the security, privacy, and user experience of immersive systems.
