3D Roof Reconstruction from 2D Spatial Graphs
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Solution Overview
Problem
Current methods for estimating three-dimensional building structures from two-dimensional spatial graphs, such as satellite imagery, fail to accurately represent the three-dimensional structure of buildings, limiting their application in remote analysis and design, particularly in shading analysis for solar installations.
Innovation Solution
The method involves processing a two-dimensional spatial graph, which is a projection of a three-dimensional building structure onto the ground, by classifying edges and calculating node heights to reconstruct a three-dimensional model, using user-defined or algorithm-generated graphs, and incorporating edge types like eave, rake, ridge, and hip to accurately represent roof structures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current methods are used to estimate three-dimensional building structures from two-dimensional spatial graphs, then the process is simple and quick, but the accuracy and completeness of the three-dimensional representation is insufficient
Solution Approach 1:
The method segments the roof structure into discrete graph elements (nodes representing vertices and edges representing roof sections). By classifying edges into different types (ridge, eave, hip, valley) based on their spatial relationships, the system can process complex roofs through systematic segmentation of their structural components, improving accuracy while maintaining manageable complexity
Solution Approach 2:
The invention transitions from two-dimensional spatial graphs to three-dimensional models by inferring vertical dimensions (heights) from edge classifications. By identifying edge types and their geometric relationships, the system reconstructs the third dimension (elevation) from planar representations, enabling accurate 3D representation without requiring direct 3D measurement data
2Reliability
If detailed three-dimensional models are created to improve shading analysis, then the analysis accuracy improves, but the data processing complexity and time increase
Solution Approach 1:
The method performs preliminary classification of edge types and identification of roof faces before conducting shading analysis. By pre-processing the spatial graph to establish the three-dimensional structure, node heights, and face orientations in advance, the system prepares accurate geometric data that can be directly used for shading calculations, reducing the time required during actual analysis while maintaining reliability
3Adaptability or versatility
If complete three-dimensional structures are reconstructed, then the scope of application expands, but the computational requirements and processing complexity increase
Solution Approach 1:
The system applies different processing rules and classification criteria to different parts of the roof structure based on their local characteristics. By identifying specific edge types (ridge, eave, hip, valley) and applying appropriate geometric relationships locally, the method reconstructs the overall three-dimensional structure through localized processing of individual roof sections, expanding applicability while managing computational complexity
Data Source
AI summary
The present invention overcomes the limitations of the prior art by exploiting properties of the projection of a three-dimensional building structure (such as a roof) onto the ground. This projection is a two-dimensional spatial graph, which can be constructed for example by a user or by an image recognition algorithm. The spatial graph is processed to recreate a three-dimensional model of the building structure.