Immersive Media Asset Prioritization for Reuse-Aware Streaming
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Solution Overview
Problem
The distribution of immersive media over commercial networks is hindered by the diversity of client devices, which require significant adaptation processes to translate media formats suitable for each target display, leading to inefficient use of network and compute resources.
Innovation Solution
A network architecture that employs caching mechanisms and media reuse logic to adapt immersive media for heterogeneous client devices, optimizing the transformation and streaming process by reusing assets across similar displays and leveraging client capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If traditional immersive media streaming systems render and stream all assets equally, then visual quality is maintained, but bandwidth consumption increases and asset reuse efficiency decreases
Solution Approach 1:
The system applies different quality levels to different assets based on their importance and reuse frequency. High-priority assets (those with high reuse frequency) are rendered at full quality, while low-priority assets are rendered at reduced quality or skipped entirely. This localized quality adjustment maintains overall visual experience while reducing total bandwidth consumption.
Solution Approach 2:
The system dynamically changes rendering parameters (quality level, resolution, detail level) based on asset priority metrics. Assets are classified into priority levels, and rendering parameters are adjusted accordingly - high-priority assets receive full rendering resources while low-priority assets receive reduced resources, optimizing the trade-off between visual quality and bandwidth usage.
2Manufacturing precision
If the system renders all assets at full quality, then visual fidelity is maintained, but rendering time and computational resources increase
Solution Approach 1:
The system applies different rendering quality levels to different assets based on their priority classification. High-priority assets that are likely to be reused receive full-quality rendering, while low-priority assets receive reduced-quality rendering or are skipped. This selective approach maintains visual fidelity for important assets while reducing total rendering time and computational resource consumption.
Solution Approach 2:
The system performs rendering actions selectively rather than universally. Instead of rendering all assets at full quality, it performs partial rendering on low-priority assets and full rendering only on high-priority assets. This partial action approach reduces overall rendering time while maintaining adequate quality for assets that matter most.
3Device complexity
If the system streams all assets with equal priority, then simplicity is maintained, but streaming efficiency and user experience decrease
Solution Approach 1:
The system changes the priority parameter assigned to different assets based on their reuse frequency and importance. Assets are classified into priority levels (e.g., high, medium, low), and streaming parameters such as bandwidth allocation, pre-rendering decisions, and quality levels are adjusted according to these priority classifications. This parameter-based differentiation improves streaming efficiency without requiring complex system architecture changes.
4Reliability
If the system pre-renders all possible assets, then asset availability is ensured, but storage requirements and rendering overhead increase
Solution Approach 1:
The system applies different pre-rendering strategies to different assets based on their priority classification. High-priority assets with high reuse frequency are pre-rendered and stored in advance to ensure immediate availability. Low-priority assets are either pre-rendered at reduced quality or rendered on-demand when needed. This selective pre-rendering approach ensures asset availability for important content while reducing total storage requirements and rendering overhead.
Data Source
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AI summary
Packaging media for optimizing immersive media distribution of a media steam performed by at least one processor, is provided, including: receiving immersive media data for an immersive presentation; acquiring asset information associated with media assets corresponding to a set of scenes included in the immersive media data for the immersive presentation; analyzing characteristics of the media assets based on the asset information, the characteristics comprising an asset type associated with a respective media asset and a frequency that indicates a number of times the respective media asset is used among the set of scenes included in the immersive presentation; ordering the media assets in a sequence based on the asset type and the frequency associated with each of the media assets; and streaming the immersive media data for the immersive presentation based on the ordered sequence of the media assets.