PatternTrack: Multi-Device Tracking Using Infrared, Structured-Light Projections from Built-in LiDAR

要旨

As augmented reality devices (e.g., smartphones and headsets) proliferate in the market, multi-user AR scenarios are set to become more common. Co-located users will want to share coherent and synchronized AR experiences, but this is surprisingly cumbersome with current methods. In response, we developed PatternTrack, a novel tracking approach that repurposes the structured infrared light patterns emitted by VCSEL-driven depth sensors, like those found in the Apple Vision Pro, iPhone, iPad, and Meta Quest 3. Our approach is infrastructure-free, requires no pre-registration, works on featureless surfaces, and provides the real-time 3D position and orientation of other users' devices. In our evaluation --- tested on six different surfaces and with inter-device distances of up to 260 cm --- we found a mean 3D positional tracking error of 11.02 cm and a mean angular error of 6.81°.

著者
Daehwa Kim
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
Robert Xiao
University of British Columbia, Vancouver, British Columbia, Canada
Chris Harrison
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
DOI

10.1145/3706598.3713388

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713388

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Immersive Touch and Gesture Interaction

G303
7 件の発表
2025-04-30 20:10:00
2025-04-30 21:40:00
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