3D Point Cloud Attribute Encoding via Difference Value Segmentation
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Solution Overview
Problem
There is a demand to improve coding efficiency in three-dimensional data encoding processes, particularly in representing and transmitting point cloud data.
Innovation Solution
A three-dimensional data encoding method that calculates difference values between attribute information of three-dimensional points and predicted values, and then generates a second code sequence including information about consecutive zero difference values and non-zero difference values, to reduce code amount and enhance coding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional point cloud encoding methods are used, then the encoding process is simple, but the coding efficiency is low and the code amount is large
Solution Approach 1:
The patent segments the encoding process into multiple stages: first encoding geometric information, then encoding attribute information separately. Within attribute encoding, it further segments by processing difference values in blocks and applying different encoding strategies to zero and non-zero difference values, thereby improving coding efficiency through structured division of the encoding task
Solution Approach 2:
The patent changes parameters by using difference values instead of original attribute values for encoding. It calculates difference values between current point attributes and predicted attributes, then encodes these differences. This parameter transformation reduces the amount of information that needs to be transmitted while maintaining reconstruction accuracy
2Quantity of substance
If all difference values are encoded individually, then the decoding process is simple, but the code amount increases significantly
Solution Approach 1:
The patent merges consecutive zero difference values into a single encoded unit by recording their count as a parameter. Instead of encoding each zero difference value separately, it combines them into one entry with a counter, significantly reducing the code amount while maintaining the ability to reconstruct the original sequence
Solution Approach 2:
The patent extracts and separately handles zero difference values from non-zero difference values. It identifies consecutive zero difference values and processes them as a distinct category, applying specialized encoding (count-based representation) that is different from how non-zero values are encoded, thereby optimizing the overall code efficiency
Data Source
AI summary
A three-dimensional data encoding method includes: calculating difference values each of which is a difference between (i) a corresponding one of pieces of attribute information of three-dimensional points included in point cloud data and (ii) a predicted value corresponding to the corresponding attribute information; generating a second code sequence including first information and a second information, the first information indicating a total number of zero difference values consecutive in a first code sequence in which the difference values are arranged, the second information indicating a value of a non-zero difference value included in the difference values, the zero difference values being included in the difference values and having a value of 0; and generating a bitstream including the second code sequence.


