3D Mesh Decoding with Layered Vertices for Flexible Resolution
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Solution Overview
Problem
Existing technologies struggle to efficiently output three-dimensional data at different resolutions, necessitating improved methods for encoding and decoding to accommodate varying data requirements.
Innovation Solution
A decoding device and encoding device that generate and output low-resolution and high-resolution three-dimensional data by connecting vertices and faces in two steps, allowing for flexible resolution adjustment based on encoded data formats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If point cloud data is compressed for accumulation and transmission, then data amount is reduced, but resolution and detail are lost
Solution Approach 1:
The patent segments the three-dimensional data into multiple levels of detail (LOD - Level of Detail). The encoded data structure includes base layer information (coarse resolution) and enhancement layers (fine resolution). This allows the system to transmit and store data in segmented portions, reducing overall data quantity while preserving the ability to reconstruct high-resolution data when needed.
Solution Approach 2:
The patent implements a nested data structure where enhancement information is embedded within the base encoded data. The enhancement layers are nested inside the base layer, allowing incremental decoding. When only base layer data is decoded, low-resolution data is obtained; when enhancement layers are also decoded, high-resolution data is reconstructed. This nesting enables flexible resolution adjustment without requiring separate data streams.
2Manufacturing precision
If high-resolution three-dimensional data is transmitted, then detail and quality are improved, but data traffic increases
Solution Approach 1:
The patent applies partial decoding by transmitting and processing only the necessary portions of the encoded data. The base layer provides essential low-resolution data that can be decoded independently, while enhancement layers containing additional detail are transmitted selectively. This partial action approach allows the system to reduce data traffic when high resolution is not required, while maintaining the capability to achieve high resolution when needed.
Solution Approach 2:
The patent implements dynamic resolution adjustment based on transmission conditions and processing requirements. The system can adaptively select which layers to transmit and decode based on available bandwidth, storage capacity, and performance requirements. This dynamic approach allows the system to optimize the balance between data traffic and resolution in real-time.
3Adaptability or versatility
If multiple resolution levels are supported, then versatility is improved, but device complexity increases
Solution Approach 1:
The patent creates a universal encoded data structure that serves multiple functions: it can be decoded to produce low-resolution data, high-resolution data, or intermediate resolutions depending on which layers are processed. The same encoded bitstream supports multiple resolution requirements, eliminating the need for separate encoding processes for different resolutions. This multi-functionality reduces overall system complexity despite supporting multiple resolution levels.
Solution Approach 2:
The patent performs preliminary encoding that establishes a hierarchical structure during the encoding phase. The base layer and enhancement layers are prepared in advance with their dependency relationships defined. This preliminary structuring simplifies the decoding process, as the decoder only needs to follow the predefined layer structure rather than performing complex real-time decisions. The encoding complexity is front-loaded, while decoding remains relatively simple.
Data Source
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AI summary
A decoding device (1320) includes circuitry (1321) and memory (1322) coupled to the circuitry (1321). In operation, the circuitry (1321): restores first vertices based on encoded data (S1311); generates first face information including a first face by connecting the first vertices restored (S1313); restores second vertices based on the encoded data and the first face (S1314); generates second face information including a second face by connecting a point cloud including the first vertices restored and the second vertices restored (S1315); and outputs the first vertices, the second vertices, the first face information, and the second face information (S1316).