TEXR: The University of Texas Extended Reality Headset Tracking Dataset

Robert M. Tenny, Nicholas Christner, Raymond Jiang, and Todd E. Humphreys

Peer Reviewed

Abstract:	The next generation of XR devices will require seamless functionality in any environment and require globally referenced poses. This paper introduces a public benchmark dataset for extended reality (XR) headset tracking in a variety of outdoor environments. The dataset includes raw GNSS intermediate frequency samples, timestamped measurements from three inertial measurement units, and globally shuttered stereoscopic cameras, all collected on a head-mounted sensor platform. Our benchmark dataset recordings include data collected in urban, light-urban, and open field environments. The dataset includes differing levels of user dynamics corresponding to pedestrian and gaming use cases. Similar datasets exist for ground and aerial vehicle-mounted sensor platforms. However, no dataset currently exists for head-mounted XR platforms with this combination of sensors. This dataset enables the evaluation of computer vision and sensor fusion algorithms for headset tracking on real-world data.
Published in:	2025 IEEE/ION Position, Location and Navigation Symposium (PLANS) April 28 - 1, 2025 Salt Lake Marriott Downtown at City Creek Salt Lake City, UT
Pages:	917 - 923
Cite this article:	Tenny, Robert M., Christner, Nicholas, Jiang, Raymond, Humphreys, Todd E., "TEXR: The University of Texas Extended Reality Headset Tracking Dataset," 2025 IEEE/ION Position, Location and Navigation Symposium (PLANS), Salt Lake City, UT, April 2025, pp. 917-923.
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