Adaptive Streaming Geometry-Based Point Clouds
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Solution Overview
Problem
Current video coding systems face challenges in efficiently compressing and streaming geometry-based volumetric or point cloud video content, particularly in adapting to varying bandwidth conditions and ensuring optimal quality levels.
Innovation Solution
The implementation of adaptive streaming techniques that allow clients to selectively access or download geometry-based point cloud compression (G-PCC) media content based on temporal levels, using media presentation description (MPD) files to identify and select appropriate point cloud streams and component sub-streams, and scheduling downloads based on G-PCC descriptors, enabling efficient storage and transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If all point cloud data is transmitted to ensure complete geometry information, then manufacturing precision is improved, but loss of substance increases due to excessive bandwidth consumption
Solution Approach 1:
The point cloud data is segmented into multiple temporal levels (e.g., coarse geometry at lower levels, fine geometry at higher levels). Clients can selectively download only the necessary temporal levels based on their specific needs and bandwidth conditions, rather than receiving all data uniformly. This segmentation allows precise control over the amount of geometry information transmitted.
Solution Approach 2:
Different regions or components of the point cloud data are assigned different quality levels based on their importance. Critical geometry components are transmitted with higher precision, while less critical areas use lower precision representations. This ensures manufacturing precision is maintained for essential features while reducing overall bandwidth consumption.
2Manufacturing precision
If complete point cloud streams are downloaded to ensure quality, then manufacturing precision is improved, but loss of time increases due to longer download durations
Solution Approach 1:
The system performs preliminary analysis of the client's requirements and available bandwidth before initiating the full download. Based on this preliminary assessment, the system pre-selects the appropriate temporal levels and data components that will satisfy the client's needs, avoiding unnecessary downloads and reducing overall download time while maintaining required quality.
Solution Approach 2:
Instead of always downloading the complete point cloud stream, the system downloads only the partial set of temporal levels and data components that are necessary to achieve the required manufacturing precision. This partial action approach reduces download time while ensuring sufficient quality for the specific application.
3Loss of substance
If adaptive streaming with temporal levels is implemented to reduce bandwidth usage, then loss of substance decreases, but device complexity increases due to MPD file processing and temporal level management
Solution Approach 1:
The MPD (Media Presentation Description) file serves multiple functions simultaneously: it describes the available temporal levels, indicates their respective qualities, provides download scheduling information, and enables client-side selection logic. This multi-functionality reduces the need for separate control mechanisms and simplifies the overall system architecture despite the added adaptability.
Data Source
AI summary
Media content may be adaptively (for example, selectively or partially) streamed based on temporal levels. The temporal levels may be indicated in a media content manifest (for example, a media presentation description (MPD)). For example, media samples for geometry-based point cloud compression (G-PCC) media content may be divided into temporal levels associated with temporal level identifiers. An MPD may indicate one or more adaptation sets associated with G-PCC media content. An adaptation set may be selected from multiple adaptation sets, A representation set may be determined from the selected adaptation set. An indication of a G-PCC descriptor associated with a representation of the representation set may be obtained from the MPD. Temporal Levels present in the representation may be identified using the G-PCC descriptor, which may include a set of temporal level identifiers, The representation may be selected based on the G-PCC descriptor.