3D Point Cloud Encoding With Duplicate-Point Signaling

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Solution Overview

Problem

There is a demand to reduce the data amount in three-dimensional data encoding processes, particularly in representing and transmitting three-dimensional data used in various applications such as autonomous vehicles and map information.

Innovation Solution

A three-dimensional data encoding method that divides a current frame of three-dimensional points into processing units, encodes these units to generate a bitstream, and includes control information indicating the presence or absence of duplicated points within each processing unit.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Quantity of substance

If three-dimensional point cloud data is stored and transmitted in its original form, then the complete geometric information is preserved, but the data amount becomes excessively large requiring compression

Engineering Contradiction:

Improvedata amountVSAvoidgeometric information

Core Design Contradiction:

Quantity of substanceVSLoss of information

Solution Approach 1:

The patent divides the point cloud data into multiple processing units (patches) that can be independently encoded and transmitted. This segmentation allows for selective compression of different regions, reducing overall data amount while preserving important geometric features in critical areas through adaptive encoding strategies.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent uses reference copying where certain point cloud data blocks are referenced from previously decoded frames or neighboring blocks. By storing references instead of complete data and using duplication detection mechanisms, the system reduces data amount while maintaining geometric information integrity through intelligent reuse of existing data.

Inventive Principle:

Principle #26Copying

2Productivity

If compression encoding is applied to reduce data amount, then the data transmission efficiency improves, but the complexity of the encoding and decoding process increases

Engineering Contradiction:

Improvedata transmission efficiencyVSAvoidencoding process complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent performs preliminary organization of point cloud data into structured processing units and pre-computes geometric features before the actual compression encoding. This preliminary processing simplifies the subsequent encoding stage by preparing data in an optimized format, reducing the computational complexity during real-time compression while maintaining transmission efficiency.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent applies different levels of compression to different processing units based on their importance and characteristics. Critical regions receive lighter compression (partial action) to preserve geometric information, while less important regions undergo more aggressive compression. This selective approach balances transmission efficiency with manageable encoding complexity.

Inventive Principle:

Principle #16Partial or excessive action

3Quantity of substance

If duplicated points are removed from processing units, then the data amount is reduced, but the detection and processing of point cloud features becomes more difficult

Engineering Contradiction:

Improvedata amountVSAvoidfeature detection difficulty

Core Design Contradiction:

Quantity of substanceVSDifficulty of detecting and measuring

Solution Approach 1:

The patent introduces an intermediary duplication detection mechanism that identifies and marks duplicated points before removal. This intermediary step maintains awareness of the original data structure and geometric relationships, allowing feature detection algorithms to compensate for removed points using surrounding context information, thus reducing data amount while preserving detectability of important features.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent implements feedback loops where the results of feature detection are used to adjust the duplication removal strategy. If feature detection becomes difficult after removing certain duplicated points, the system adjusts by retaining some duplicates in critical regions or adjusting compression parameters, thereby balancing data reduction with feature detectability through continuous feedback optimization.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS12335491B2Three-dimensional data encoding method, three-dimensional data decoding method, three-dimensional data encoding device, and three-dimensional data decoding device

Publication Date: 2025.06.17 PANASONIC INTELLECTUAL PROPERTY CORP OF AMERICA

AI summary

A three-dimensional data encoding method includes: dividing a current frame including three-dimensional points into processing units; and encoding the processing units to generate a bitstream. Control information for each frame included in the bitstream includes first information indicating whether (i) one of the processing units included in the current frame includes duplicated points that are three-dimensional points having same geometry information or (ii) none of the processing units includes the duplicated points.