3D Data Encoding via Random Access Units
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Solution Overview
Problem
Current methods for representing and transmitting three-dimensional data, such as point clouds, lack efficient compression and random access capabilities, leading to high data volumes and limited functionality for applications like autonomous vehicles and map information systems.
Innovation Solution
A three-dimensional data encoding method that divides data into random access units, allowing for efficient encoding and decoding by referencing other units, enabling selective transmission and improved accessibility while optimizing data size and transmission efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If three-dimensional data is transmitted in its original form, then data completeness is maintained, but data transmission volume becomes excessively large
Solution Approach 1:
The three-dimensional data is divided into random access units (RAUs) that can be independently encoded and transmitted. This segmentation allows selective transmission of only necessary data portions, reducing overall transmission volume while maintaining access to complete data when needed by decoding all RAUs.
Solution Approach 2:
The patent extracts and encodes only the necessary three-dimensional data into RAUs based on specific encoding conditions. By selectively extracting and encoding data portions that meet certain criteria, the system reduces transmission volume while preserving essential information for autonomous vehicle operations.
2Productivity
If all three-dimensional data is transmitted, then data availability is maximized, but transmission efficiency decreases
Solution Approach 1:
The encoding system dynamically adjusts which data portions are encoded into RAUs based on varying conditions such as vehicle speed, distance to other vehicles, and environmental factors. This dynamic adaptation allows the system to optimize transmission efficiency for different operational scenarios while maintaining data availability when needed.
Solution Approach 2:
The patent changes encoding parameters such as RAU size, encoding density, and selection criteria based on operational conditions. By adjusting these parameters dynamically, the system achieves high transmission efficiency in normal conditions while preserving data availability for complete three-dimensional reconstruction when required.
3Ease of operation
If random access units are implemented, then data accessibility is improved, but encoding complexity increases
Solution Approach 1:
By segmenting three-dimensional data into standardized RAUs with defined structures, the patent simplifies random access operations. Each RAU contains necessary information for independent decoding, improving data accessibility without requiring complex coordination between data portions.
Solution Approach 2:
The RAU structure is designed to be universal and multi-functional, serving both as a transmission unit and a random access unit. This standardized structure enables simple access operations while the encoding complexity is managed through systematic application of the segmentation principle across all data portions.
Data Source
AI summary
A three-dimensional data encoding method includes: extracting, from first three-dimensional data, second three-dimensional data having an amount of a feature greater than or equal to a threshold; and encoding the second three-dimensional data to generate first encoded three-dimensional data. For example, the three-dimensional data encoding method may further include encoding the first three-dimensional data to generate the second encoded three-dimensional data.