XR Overlay Placement Using Edge AI Motion Probability Fields
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Solution Overview
Problem
Existing XR devices face challenges in efficiently placing visual overlays due to high latency and processing demands, particularly in dynamic environments with moving objects, and lack effective methods for precise overlay placement using 4G LTE networks.
Innovation Solution
An architecture utilizing 5G NR's low latency and high-speed capabilities to process semantic data in the edge cloud, integrating static and dynamic motion probability fields (S-MPF and D-MPF) for accurate overlay placement, leveraging computer vision and AI to predict object movement and streamline processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If overlay placement processing is performed on XR devices using 4G LTE networks, then device functionality is maintained, but latency is high and processing efficiency is poor
Solution Approach 1:
The patent introduces an edge cloud server as an intermediary between XR devices and the core network. This edge server performs overlay placement processing locally at the network edge, reducing the distance data must travel and thereby lowering latency while improving processing efficiency compared to cloud-based processing over 4G LTE networks.
Solution Approach 2:
The patent transitions from traditional horizontal network architecture to a vertical edge computing dimension. By placing processing capabilities at the network edge (spatial dimension change), the system achieves lower latency and higher processing efficiency without sacrificing device functionality.
2Manufacturing precision
If more processing power is allocated to XR devices for overlay placement, then overlay precision improves, but device complexity and power consumption increase
Solution Approach 1:
The patent extracts complex overlay placement processing functions from XR devices and relocates them to edge cloud servers. This extraction maintains high overlay precision while reducing device complexity, as the heavy computational tasks are performed externally rather than on the limited device hardware.
Solution Approach 2:
The edge cloud server provides universal processing capabilities that can serve multiple XR devices simultaneously. This multi-functionality approach achieves high overlay precision without requiring each individual device to have complex processing power, as the edge server handles processing for multiple devices.
3Measurement precision
If real-time motion tracking is implemented for moving objects, then overlay placement accuracy improves, but processing demands and latency increase
Solution Approach 1:
The patent implements preliminary action by pre-processing and caching motion probability fields (S-MPF and D-MPF) at the edge cloud server before they are needed for overlay placement. This advance preparation reduces real-time processing demands and latency when actual overlay placement requires motion tracking data for moving objects.
Solution Approach 2:
The patent uses dynamic motion probability fields that are updated continuously at the edge server based on object movement patterns. This dynamic approach maintains high overlay placement accuracy for moving objects while reducing processing time compared to static real-time tracking, as the system adapts to motion patterns proactively rather than reactively.
Data Source
AI summary
A method of an electronic device in an edge cloud of a mobile network supports extended reality overlay placement for an object having a location in the real world. The method includes receiving a request from an application of a user equipment, the request including an object identifier for an object that is a target of an extended reality overlay, and determining a static motion probability field (S-MPF) for the object identifier.