Geometry Tile Tracks for Selective Point Cloud Rendering
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Solution Overview
Problem
Existing point cloud compression standards force users to download and decode all geometry-based point cloud component information, even when they are interested in specific regions or objects, lacking efficient partial access support.
Innovation Solution
A method and apparatus that utilize timed-metadata tracks to identify point cloud tiles within a scene, allowing for the retrieval and processing of specific geometry tile tracks corresponding to those tiles, enabling efficient partial access and rendering of point cloud data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all geometry-based point cloud component information is downloaded and decoded, then complete point cloud data is available, but data transfer volume and processing time increase unnecessarily
Solution Approach 1:
The point cloud data is divided into multiple tiles, each representing a specific spatial region. The encoded bitstream includes tile indicators that identify which tiles correspond to user-selected regions of interest. This segmentation allows the system to transmit and decode only the necessary tile data rather than the entire point cloud, resolving the contradiction between data completeness and transfer volume.
2Manufacturing precision
If all geometry-based point cloud component information is decoded, then accurate 3D reconstruction is achieved, but processing time and computational resources increase
Solution Approach 1:
The system extracts and processes only the tile data corresponding to user-selected regions of interest from the encoded point cloud bitstream. The decoding device uses tile indicators to identify and decode only the necessary tile components, excluding irrelevant regions. This extraction approach maintains 3D reconstruction accuracy for the regions of interest while significantly reducing processing time and computational resource requirements.
3Productivity
If selective decoding of specific regions is implemented, then data transfer efficiency improves, but system complexity increases due to tile tracking and region management
Solution Approach 1:
The point cloud data is pre-divided into tiles with associated indicators embedded in the encoded bitstream before transmission. This preliminary organization allows the decoding device to efficiently identify and access only the necessary tile data without requiring complex runtime decisions. The tile indicators provide a straightforward mapping between user-selected regions and the corresponding encoded data, improving transfer efficiency while keeping the system manageable.
Data Source
AI summary
A method and apparatus include receiving a timed-metadata track identifying point cloud tiles corresponding to one or more spatial regions within a point cloud scene. A decoding device determines one or more point cloud tiles to be used for rendering an image. One or more geometry tile tracks are retrieved, via a communications network, corresponding to the determined one or more point cloud tiles. Each geometry tile track comprises point cloud geometry data for a respective tile. The retrieved geometry tile tracks are processed.