xR Content Encoding via ROI Priority Bandwidth Allocation
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Solution Overview
Problem
Virtual, augmented, and mixed reality applications in connectivity-constrained environments face challenges in efficiently transmitting high-quality visual and audio content due to limited bandwidth, where existing systems struggle to prioritize and adapt transmission based on user interaction and environment mapping.
Innovation Solution
An Information Handling System (IHS) that receives sensor information from Head-Mounted Devices (HMDs), calculates priorities for Regions-of-Interest (ROIs) using SLAM landmarks and gaze vectors, and adjusts video and audio encoders to allocate bandwidth accordingly, ensuring visual and audio fidelity while maintaining resilience in transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If high-quality visual and audio content is transmitted in xR applications, then user experience quality is improved, but bandwidth consumption increases beyond available capacity in connectivity-constrained environments
Solution Approach 1:
The patent applies local quality by differentiating transmission quality across different regions of the visual field. High-fidelity encoding is applied to foveal regions where users focus attention, while peripheral regions receive lower-fidelity encoding. This resolves the contradiction by maintaining perceived visual quality in important areas while reducing overall bandwidth consumption through selective quality degradation in less critical regions.
Solution Approach 2:
The patent segments the visual field into multiple regions of interest (ROIs) based on user gaze and environmental importance. Each ROI is independently encoded with appropriate quality levels, allowing the system to prioritize bandwidth allocation to significant regions while reducing transmission load from less important areas, thus balancing fidelity and bandwidth consumption.
2Adaptability or versatility
If comprehensive sensor data and environmental mapping are processed to enhance xR experience, then adaptability and user experience are improved, but processing complexity and computational requirements increase
Solution Approach 1:
The system performs preliminary processing of sensor data to identify and prioritize regions of interest before full encoding and transmission. By pre-processing sensor information to determine which areas require high-fidelity rendering, the system reduces subsequent processing complexity while maintaining adaptability to user needs and environmental context.
Solution Approach 2:
The patent extracts only the most relevant features from comprehensive sensor data and environmental maps for the purpose of ROI determination. Instead of processing all sensor information at full detail, the system extracts key spatial and contextual features needed for region prioritization, reducing computational complexity while preserving adaptability.
Data Source
AI summary
Embodiments of systems and methods for encoding content for virtual, augmented, or mixed reality (xR) applications in connectivity-constrained environments are described. In some embodiments, an Information Handling System (IHS) may be configured to: receive sensor information from a Head-Mounted Device (HMD) worn by a user during execution of an xR application; calculate, based on the sensor information, a priority of each of a plurality of Regions-of-Interest (ROIs) within one or more images produced by a rendering engine; and indicate the priorities to a video encoder, where the video encoder is configured to use each priority to control at least one of: (a) visual fidelity, or (b) resilience of a corresponding ROI transmitted by the IHS to the HMD in a video signal during execution of the xR application.