Layered Point Cloud Attribute Encoding for Faster 3D Decoding
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Solution Overview
Problem
Existing three-dimensional data decoding devices face significant processing time challenges due to the massive amount of data in point cloud representations, necessitating more efficient encoding and decoding methods.
Innovation Solution
A method of assigning three-dimensional points to layers and encoding attribute information using these layers, along with encoding the total number of points per layer, allows the decoding device to determine layer membership without geometry calculations, enabling parallel processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If point cloud data is used to represent three-dimensional structures, then the data can comprehensively capture geometric and attribute information, but the massive amount of data necessitates compression and increases processing time
Solution Approach 1:
The patent segments the point cloud data into multiple layers based on depth information, where each layer contains points within a specific depth range. This segmentation allows the decoding device to process and reconstruct layers sequentially rather than handling all points simultaneously, significantly reducing processing time while preserving complete geometric and attribute information.
Solution Approach 2:
The patent performs preliminary encoding of layer structure information and point-to-layer mapping during the encoding phase. The bitstream includes pre-encoded data about the number of points in each layer and their assignments, allowing the decoding device to reconstruct the three-dimensional structure without performing complex geometry calculations during decoding, thereby reducing processing time.
2Device complexity
If layer assignment is performed without pre-encoded mapping information, then the decoding can be simpler, but geometry calculations are required which increase processing time
Solution Approach 1:
The encoding device performs the complex task of assigning points to layers and encoding this mapping information in advance. The bitstream contains pre-encoded layer structure data including the number of points per layer and their assignments. During decoding, the device simply reads this pre-encoded information without performing geometry calculations, thus reducing processing time while maintaining decoding simplicity.
3Ease of operation
If all three-dimensional points are processed simultaneously, then the decoding is straightforward, but the massive amount of data increases processing time significantly
Solution Approach 1:
The patent divides the point cloud into multiple layers based on depth ranges, allowing the decoding device to process each layer sequentially rather than handling all points simultaneously. This segmentation maintains decoding simplicity for each individual layer while significantly improving overall processing efficiency by breaking down the massive data set into manageable chunks.
Data Source
AI summary
A three-dimensional data encoding method is a method of encoding three-dimensional points each having an attribute information item. The three-dimensional data encoding method includes: assigning each of the three-dimensional points to any one of layers; encoding the attribute information item of each three-dimensional point using the layers; and encoding information indicating a total number of three-dimensional points belonging to each of the layers.