Point Cloud Inter-Prediction With Single-Stage Reference Frame Update
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Solution Overview
Problem
Existing point cloud compression techniques require multiple stages for generating an updated reference frame, leading to increased memory utilization and processing time.
Innovation Solution
Applying a scale and offset to a reference frame in a single stage to generate an updated reference frame, reducing the need for intermediate value storage and processing time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple stages are used to generate an updated reference frame, then processing accuracy is improved, but memory utilization increases and processing time increases
Solution Approach 1:
The patent combines multiple stages of reference frame generation into a single stage by integrating the operations of generating a first updated reference frame and a second updated reference frame into one unified process. This merging reduces the need to store intermediate values from multiple stages, thereby decreasing memory utilization while maintaining processing accuracy through the combined transformation.
Solution Approach 2:
The patent applies preliminary action by pre-computing and storing transformation parameters (scaling factors and offsets) before the actual reference frame generation. These pre-computed parameters are then applied in a single stage to generate the updated reference frame, eliminating the need for multiple sequential stages and reducing memory requirements for intermediate data.
2Measurement precision
If multiple stages are used to generate an updated reference frame, then processing accuracy is improved, but processing time increases
Solution Approach 1:
The patent merges multiple sequential stages of reference frame generation into a single integrated stage. By combining the operations of generating first and second updated reference frames into one process, the patent reduces the total processing time while maintaining accuracy through the combined transformation logic.
Solution Approach 2:
The patent performs preliminary computation of transformation parameters (scaling factors and offsets) before the main processing stage. This pre-computation allows the actual reference frame generation to proceed in a single stage without time-consuming iterative calculations, thereby reducing processing time while preserving accuracy.
3Quantity of substance
If a single stage process is used, then memory utilization is reduced, but processing accuracy may be compromised
Solution Approach 1:
The patent changes the parameters of the transformation process by using adaptive scaling factors and offsets that are computed based on the statistical properties of the point cloud data. This parameter adaptation allows the single stage process to achieve accuracy comparable to multi-stage processes, as the transformed reference frame accurately represents the spatial relationships in the original data.
Solution Approach 2:
The patent creates a transformed copy of the reference frame through a single stage process that applies scaling and offset transformations. This copied updated reference frame maintains the essential spatial information and relationships from the original frame, enabling accurate processing without requiring multiple stages or extensive memory for intermediate representations.
Data Source
AI summary
A method of decoding point cloud data includes applying a scale and offset to a reference frame in a single stage to generate an updated reference frame; and decoding the point cloud data of a current frame based on the updated reference frame.