G-PCC Point Cloud Tracks for Temporal Scalability Playback
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Solution Overview
Problem
Existing technologies face challenges in efficiently processing large volumes of point cloud data, managing latency and encoding/decoding complexity, and supporting temporal scalability in geometry-based point cloud compressed (G-PCC) data, as well as efficient storage and access to G-PCC bitstreams.
Innovation Solution
A method and device for processing point cloud data that includes reconstructing point clouds based on temporal scalability information, generating G-PCC files with specified constraints, and dividing bitstreams into multiple tracks for efficient storage and access, supporting temporal scalability and reducing playback complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If point cloud data is processed using traditional methods, then the processing can be performed, but the processing efficiency is low and latency is high due to the vast amount of point data
Solution Approach 1:
The patent segments the G-PCC bitstream into multiple tracks based on temporal levels, where each track contains point cloud data for a specific temporal level. This segmentation allows parallel processing of different temporal levels, improving processing efficiency and reducing latency by avoiding sequential processing of all point data.
Solution Approach 2:
The patent performs preliminary organization of point cloud data into temporal levels during encoding, creating a structured G-PCC bitstream with temporal scalability information. This preliminary action enables the reception device to quickly access and process only the required temporal level data without examining the entire point cloud dataset, thereby reducing processing time and latency.
2Adaptability or versatility
If temporal scalability is supported in G-PCC data, then service quality is improved, but encoding and decoding complexity increases
Solution Approach 1:
The patent divides the G-PCC bitstream into multiple tracks, with each track corresponding to a specific temporal level. This segmentation allows the encoding and decoding processes to be performed independently for each temporal level, reducing the overall complexity by avoiding the need to process all temporal levels simultaneously while still supporting temporal scalability.
Solution Approach 2:
The patent implements dynamic temporal level selection where the reception device can adaptively choose which temporal level tracks to process based on available bandwidth, processing capabilities, and service requirements. This dynamic approach enables temporal scalability while managing encoding and decoding complexity by processing only the necessary temporal levels.
3Ease of manufacture
If G-PCC bitstream is stored in a single track, then storage is simple, but access efficiency is low
Solution Approach 1:
The patent segments the G-PCC bitstream into multiple tracks organized by temporal levels, maintaining storage simplicity through a structured format while enabling efficient access to specific temporal levels. Each track is independently accessible, allowing the reception device to quickly locate and process only the required temporal level data without scanning the entire bitstream.
Solution Approach 2:
The patent introduces a temporal level dimension to the storage structure, organizing data not just sequentially but also hierarchically by temporal levels. This multi-dimensional organization allows efficient access to specific temporal levels while maintaining overall storage simplicity through standardized track structures.
4Ease of operation
If all samples are processed together, then processing is straightforward, but playback complexity increases and smooth playback is difficult to achieve
Solution Approach 1:
The patent segments the point cloud samples into different temporal level tracks, allowing the reception device to process and playback samples from a single temporal level independently. This segmentation simplifies playback operations by enabling focused processing of manageable data subsets while achieving smooth playback through incremental rendering of temporal levels.
Data Source
AI summary
Transmission device of point cloud data, method performed by transmission device, reception device of point cloud data and method performed by reception device are provided. According to an embodiment of the present disclosure, a method performed by a reception device of point cloud data comprises obtaining a geometry-based point cloud compression (G-PCC) file including the point cloud data and reconstructing the point cloud based on temporal scalability information, wherein the temporal scalability information may comprise first information on a temporal level track of the G-PCC file, and the first information may specify a constraint on the temporal level track based on a sample entry type.