Shared XR Pose Tracking Beyond Camera Field of View
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Solution Overview
Problem
XR devices face challenges in tracking objects, particularly when they exit and re-enter the camera field of view, leading to inconsistencies in rendering virtual content.
Innovation Solution
XR devices share 6DOF pose data with each other to enhance tracking capabilities, using techniques like SLAM and VIO, and synchronize spatial reference systems to maintain accurate tracking even when objects are outside the camera view.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If XR devices use only camera images to track objects, then device complexity is reduced, but tracking reliability deteriorates when objects exit and re-enter the camera field of view
Solution Approach 1:
The patent combines data from multiple XR devices (pose data, image data) to perform tracking. Instead of relying on a single device's camera, the system merges information from multiple sources including pose data from other XR devices and image data from the local device, creating a more reliable tracking system that maintains tracking continuity when objects leave and re-enter the field of view.
2Measurement precision
If multiple XR devices share and process pose data and image data, then tracking precision is improved, but computational resources and processing time increase
Solution Approach 1:
The system performs preliminary actions by establishing pose sharing sessions and pre-processing data from multiple XR devices before tracking is critically needed. Pose data and image data are collected and prepared in advance, allowing the tracking algorithm to work with pre-processed information rather than raw data, reducing real-time computational burden while maintaining high precision.
3Stability of the object's composition
If XR devices continuously capture and process images to maintain tracking, then tracking consistency is improved, but energy consumption increases
Solution Approach 1:
The patent makes the tracking system multi-functional by utilizing multiple data sources (pose data from inertial sensors, image data from cameras, data from other XR devices) that can serve different purposes. When energy is conserved and continuous image capture is reduced, the system can still maintain tracking consistency by relying on pose data and data from other XR devices, making the system adaptable to different energy availability conditions.
Data Source
AI summary
Examples disclosed herein relate to the use of shared pose data in extended reality (XR) tracking. A communication link is established between a first XR device and a second XR device. The second XR device is worn by a user. The first XR device receives pose data of the second XR device via the communication link and captures an image of the user. The user is identified based on the image and the pose data.


