UbiPose: Towards Ubiquitous Outdoor AR Pose Tracking using Aerial Meshes
Weiwu Pang, Chunyu Xia, Branden Leong, Fawad Ahmad, Jeongyeup Paek, Ramesh Govindan
Abstract
Tracking the position and orientation, or pose, of a viewing device enables AR applications to accurately embed virtual content in physical spaces. Mobile OSs track pose by matching device camera images against street-level imagery. Thus, pose tracking is often unavailable at off-street pedestrian locations. UbiPose enables pose tracking at such locations using aerial meshes, generated from satellite imagery, that are likely to be more widely available at these locations. However, matching a camera image against an aerial mesh can be error-prone, even with modern neural matchers. These neural components are also compute-intensive. UbiPose contains a novel pose tracking pipeline that runs entirely on a mobile device using fast-path optimizations designed to accept or reject pose estimates in many cases, without sacrificing accuracy. Experiments on real-world traces show that it achieves tracking accuracy comparable to AR pose tracking in iOS in places where that is available, and is able to track pose accurately in places where it is not.
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