3D Point Attribute Prediction Modes for Compression Efficiency

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Solution Overview

Problem

Existing methods for representing and encoding three-dimensional data, such as point clouds, face challenges in achieving efficient compression and transmission due to the massive amount of data involved, necessitating improved encoding efficiency.

Innovation Solution

A three-dimensional data encoding method that selects a prediction mode from multiple modes based on attribute information of nearby points to calculate a predicted value, generating a bit stream with the prediction mode and residual, enhancing encoding efficiency.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Quantity of substance

If point cloud data is stored in its original form, then the completeness and accuracy of three-dimensional data are maintained, but the data volume becomes excessively large requiring efficient compression

Engineering Contradiction:

Improvedata volumeVSAvoiddata completeness

Core Design Contradiction:

Quantity of substanceVSLoss of information

Solution Approach 1:

The patent segments the point cloud data into multiple octants based on spatial division, processing and encoding each octant separately. This segmentation allows selective compression and transmission of only the necessary spatial regions, reducing overall data volume while preserving complete information about the three-dimensional structure through systematic partitioning.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent performs preliminary spatial division of the point cloud into octants before encoding, and pre-calculates prediction values for attribute information items based on neighboring points within each octant. This preliminary preparation enables efficient compression by establishing prediction models in advance, reducing the information that needs to be transmitted while maintaining data completeness.

Inventive Principle:

Principle #10Preliminary action

2Productivity

If prediction modes are selected based on attribute information of nearby points, then encoding efficiency is improved, but the complexity of the encoding process increases

Engineering Contradiction:

Improveencoding efficiencyVSAvoidencoding process complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent applies different prediction modes selectively based on the local characteristics of each octant and the attribute information of nearby points. Instead of using a uniform encoding approach, the system adapts the prediction method to the specific local conditions, improving encoding efficiency in regions where prediction is effective while avoiding unnecessary complexity in regions where direct encoding is simpler.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The patent dynamically selects between different prediction modes (first prediction mode using average values of neighboring points, second prediction mode using median values) based on the specific attribute information and spatial relationships in each octant. This dynamic adaptation allows the encoding process to optimize its complexity based on local data characteristics, achieving higher encoding efficiency without consistently increasing overall process complexity.

Inventive Principle:

Principle #15Dynamics

3Measurement precision

If multiple prediction modes are used to calculate predicted values, then the accuracy of attribute information reconstruction is improved, but the computational load increases

Engineering Contradiction:

Improveattribute information accuracyVSAvoidcomputational load

Core Design Contradiction:

Measurement precisionVSPower

Solution Approach 1:

The patent changes the parameters of the prediction calculation based on the local characteristics of each octant. By switching between different prediction modes (using average values versus median values of neighboring points) depending on the specific attribute information and spatial relationships, the system optimizes the balance between reconstruction accuracy and computational load for each local region.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent applies prediction modes selectively only where necessary and beneficial, rather than uniformly across all point cloud data. By using prediction only in octants where it improves accuracy significantly, and direct encoding where the gain is minimal, the system achieves improved overall accuracy without proportionally increasing total computational load.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS20250350718A1Three-dimensional data encoding method, three-dimensional data decoding method, three-dimensional data encoding device, and three-dimensional data decoding device

Publication Date: 2025.11.13 PANASONIC INTELLECTUAL PROPERTY CORP OF AMERICA

AI summary

A three-dimensional data encoding method encodes a plurality of three-dimensional points, and includes: selecting one of two or more prediction modes for calculating a predicted value of an attribute information item of the first three-dimensional point, in accordance with attribute information items of one or more second three-dimensional points in the vicinity of a first three-dimensional point; calculating the predicted value by the selected prediction mode; calculating, as a prediction residual, a difference between a value of the attribute information item of the first three-dimensional point and the calculated predicted value; and generating a bit stream that includes the one prediction mode and the prediction residual.