Cross Reality System Quality Information Persistent Coordinate Frames
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Solution Overview
Problem
Cross reality (XR) systems face challenges in providing realistic and immersive experiences due to inaccuracies in positioning virtual content within a shared coordinate frame, leading to positional uncertainties and errors in rendering virtual objects relative to real-world objects.
Innovation Solution
The implementation of methods to compute and utilize quality information about persistent coordinate frames, which involves localizing devices in 3D environments, obtaining persistent coordinate frame information, and calculating positional uncertainties to adapt rendering based on quality metrics, ensuring accurate placement and rendering of virtual content relative to real-world features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If virtual content is rendered in a shared coordinate frame without quality information, then the rendering process is simple and fast, but positional accuracy and realism deteriorate due to uncertainties and errors
Solution Approach 1:
The system pre-computes and stores quality information (uncertainty metrics) for persistent coordinate frames before rendering occurs. This preliminary computation of quality metrics allows the rendering system to later use this pre-available information to adjust virtual content placement without adding computational complexity during the rendering process itself.
Solution Approach 2:
The system incorporates quality information about persistent coordinate frames as feedback into the rendering process. By using uncertainty metrics to adjust the placement and rendering of virtual content, the system creates a feedback loop that improves positional accuracy based on measured quality parameters, resolving the contradiction between simplicity and precision.
2Measurement precision
If quality information about persistent coordinate frames is computed and used, then rendering accuracy improves, but computational time and processing requirements increase
Solution Approach 1:
Quality information is pre-computed and stored with persistent coordinate frames during system initialization or when coordinate frames are established. This preliminary action eliminates the need to compute quality metrics in real-time during rendering, reducing processing time while maintaining high positioning precision through the use of pre-available quality data.
3Reliability
If virtual objects are placed without accounting for coordinate frame quality, then the rendering process is efficient, but realism and immersion deteriorate due to positional errors
Solution Approach 1:
The system applies different rendering strategies based on the quality information of specific persistent coordinate frames. Instead of uniformly treating all coordinate frames equally, the system adjusts rendering parameters locally for each coordinate frame based on its quality metrics, improving reliability where needed while maintaining efficiency in high-quality regions.
Data Source
AI summary
A cross reality system that provides an immersive user experience shared by multiple user devices by providing quality information about a shared map. The quality information may be specific to individual user devices rendering virtual content specified with respect to the shared map. The quality information may be provided for persistent coordinate frames (PCFs) in the map. The quality information about a PCF may indicate positional uncertainty of virtual content, specified with respect to the PCF, when rendered on the user device. The quality information may be computed as upper bounding errors by determining error statistics for one or more steps in a process of specifying position with respect to the PCF or transforming that positional expression to a coordinate frame local to the device for rendering the virtual content. Applications running on individual user devices may adjust the rendering of virtual content based on the quality information about the shared map.