3D Geometric Model Generation from Single Facade Images
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for generating 3D geometric models from single digital images of building facades lack sufficient resolution and visual quality, especially for applications requiring detailed near-ground level navigation and simulation, and are inefficient, often requiring extensive manual labor.
Innovation Solution
A computer system and method that subdivides digital images into regions and assigns corresponding 3D architectural objects from a library to generate a rules-based parametric 3D geometric model, enhancing resolution and visual quality through bottom-up detection and association of facade structures, incorporating symmetry analysis and shader information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional manual methods are used for large-scale urban reconstruction, then visual quality and geometric detail can be achieved, but the process requires several man years of labor and is highly time-consuming
Solution Approach 1:
The system performs automatic facade analysis and 3D model generation without requiring manual intervention. The computer vision algorithms automatically detect architectural elements, analyze facade structures, and generate parametric 3D models from single images, enabling the system to serve itself and eliminate the need for manual modeling operations.
Solution Approach 2:
Manual mechanical modeling operations are replaced with automated computer vision and image processing systems. The system uses algorithms to detect edges, identify architectural elements, and generate 3D geometry automatically, substituting human operators with computational processes that are both faster and more consistent.
2Productivity
If recent automatic large-scale modeling techniques are used, then processing efficiency is improved, but the models do not provide sufficient resemblance to the real life environment and lack visual quality
Solution Approach 1:
The system applies different processing strategies to different parts of the facade based on local characteristics. Architectural elements such as windows, doors, and decorative features are detected and modeled with higher detail using specialized computer vision algorithms, while uniform wall sections are processed more efficiently, achieving both speed and visual fidelity where needed.
Solution Approach 2:
The system performs preliminary analysis of the input image to identify architectural elements, facade patterns, and structural features before generating the 3D model. This preliminary detection phase allows the system to prepare appropriate modeling strategies for different facade regions, ensuring high visual quality is achieved during the subsequent model generation phase.
3Extent of automation
If computer vision methods are used during modeling to assist users, then automation is improved, but the methods rely on graphical simplifications and pre-specified facade element types that limit detection accuracy
Solution Approach 1:
The system uses dynamic and adaptive algorithms that can adjust to different facade styles and architectural elements without being constrained by pre-specified types. The computer vision algorithms dynamically identify and classify architectural elements based on their visual characteristics, allowing the system to handle diverse and unexpected facade designs with high detection accuracy.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
For generating a 3D geometric model (44) and/or a definition of the 3D geometric model from a single digital image of a building facade (4), a facade structure is detected from the digital image by dividing the facade (4) along horizontal lines into horizontal layers representative of floors (41 ), and by dividing the horizontal layers along vertical lines into tiles (42). The tiles (42) are further subdivided into a hierarchy of rectangular image regions (43), 3D architectural objects (45) corresponding to the image regions (43) are determined in an architectural element library. The 3D geometric model (44) or the definition of the 3D geometric model is generated based on the facade structure, the hierarchy and the 3D architectural objects (45). The library-based generation of the 3D geometric model makes it possible to enhance simple textured building models constructed from aerial images and/or ground-based photographs.