Point Cloud Coding Prediction and Temporal Order Signaling
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Solution Overview
Problem
Current Point Cloud Coding (PCC) lacks definition for prediction types and temporal orders, leading to inefficiencies in data compression and transmission, as it relies on spatial and temporal redundancy reduction methods without standardized signaling for prediction types and order.
Innovation Solution
The implementation of prediction type signaling and temporal order signaling in PCC through specific fields in bitstreams, such as frame type fields, FOC fields, POC lookup encoder fields, and reference index fields, to define whether intra-prediction, unidirectional, or bidirectional prediction is used and to specify the temporal order of point clouds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If point clouds are compressed during encoding to reduce data amount, then bandwidth consumption is reduced, but point cloud quality deteriorates
Solution Approach 1:
The patent applies parameter changes by introducing multiple prediction types (intra-prediction, unidirectional inter-prediction, bidirectional inter-prediction) and temporal ordering mechanisms that transform how point cloud data is processed and compressed, enabling better quality at reduced bitrates through standardized signaling fields
2Manufacturing precision
If more data is used to improve point cloud quality, then point cloud quality is improved, but bandwidth consumption increases
Solution Approach 1:
The patent transforms the data efficiency through parameter changes by implementing standardized prediction type signaling and temporal order signaling, which enable more effective compression algorithms that achieve higher quality at lower data rates
3Productivity
If prediction type signaling and temporal order signaling are implemented to improve compression efficiency, then data compression efficiency is improved, but device complexity increases
Solution Approach 1:
The patent resolves the complexity-efficiency tradeoff by parameter changes through standardized signaling fields that encode prediction types and temporal orders in a systematic manner, improving compression efficiency while maintaining manageable encoder and decoder complexity through consistent formatting
Solution Approach 2:
The patent applies universality by creating a multi-functional signaling framework where the same standardized fields serve multiple purposes: indicating prediction types, specifying temporal orders, and enabling various decoding strategies, thereby improving compression efficiency without proportionally increasing complexity
Data Source
AI summary
An apparatus comprises an encoder configured to obtain point clouds, generate a first field that implements prediction type signaling of the point clouds, generate a second field that implements temporal order signaling of the point clouds, and encode the first field and the second field into an encoded bitstream; and an output interface coupled to the encoder and configured to transmit the encoded bitstream. An apparatus comprises a receiver configured to receive an encoded bitstream; and a processor coupled to the encoded bitstream and configured to decode the encoded bitstream to obtain a first field and second field, wherein the first field implements prediction type signaling of point clouds, and wherein the second field implements temporal order signaling of the point clouds, and generate the point clouds based on the first field and the second field.