TriSoup Triangle Reconstruction for Accurate 3D Ridge Lines
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Solution Overview
Problem
Existing methods for encoding and decoding three-dimensional data, such as point cloud data, face challenges in accurately reproducing the shape of three-dimensional structures, particularly at boundaries and ridge lines, leading to inaccuracies in reconstructed models.
Innovation Solution
The proposed method employs a TriSoup scheme that derives sorted edge and face vertices to generate triangles, incorporating face vertices to improve accuracy by reconstructing ridge lines and ensuring connectivity between nodes, using a decoding and encoding process that includes entropy encoding and decoding of vertex information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional point cloud compression methods are used, then data transmission and storage are enabled, but the accuracy of restored three-dimensional data deteriorates
Solution Approach 1:
The method segments the point cloud data into multiple nodes, where each node is independently processed to generate TriSoup triangles. This segmentation allows for localized optimization of reconstruction accuracy while managing data complexity, directly addressing the contradiction by enabling accurate restoration through structured division of the data into manageable segments that can be efficiently compressed and transmitted
Solution Approach 2:
The invention transitions from representing three-dimensional data as discrete points to representing it as two-dimensional triangular surfaces (TriSoup) that approximate the three-dimensional shape. This dimensionality change enables more efficient compression while maintaining or improving restoration accuracy, as the triangular surface representation captures geometric information more effectively than point cloud alone
2Manufacturing precision
If TriSoup scheme is applied to generate triangles, then shape representation improves, but complexity of the encoding and decoding process increases
Solution Approach 1:
The method performs preliminary sorting of edge vertices and pre-establishes the triangular surface structure during the encoding phase. By organizing the data in advance according to the TriSoup scheme, the decoding process becomes simpler and more efficient, resolving the contradiction by shifting computational complexity to the encoding stage while simplifying the decoding stage
Solution Approach 2:
The invention changes the fundamental representation parameters from point cloud coordinates to triangular surface definitions with sorted edge vertices. This parameter transformation enables more accurate shape reconstruction while providing a structured framework that simplifies the overall processing complexity through consistent mathematical relationships
Data Source
AI summary
A decoding method includes: deriving sorted edge vertices of a node according to a TriSoup scheme; deriving a face vertex provided on a surface of the node except for edges of the node; selecting two adjacent edge vertices that are adjacent to each other in sort order and closest to the face vertex among the sorted edge vertices; and generating a TriSoup triangle by using the face vertex and one of the two adjacent edge vertices.