Single-Image 3D Urban Modeling Using Segmentation and Depth Maps
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Solution Overview
Problem
Creating up-to-date 3D models of urban areas is a complex and costly process that typically requires significant time and resources, and current methods struggle to capture detailed depth information without extensive on-site efforts.
Innovation Solution
A computer-implemented method that generates a 3D model from a single monocular optical satellite image using segmentation and depth map analysis, involving image tiling, segmentation models, and depth map processing to create a height map and 3D model, which can be updated quickly and cost-effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional methods are used to create 3D models of urban areas, then the model accuracy and detail are improved, but the time and cost increase significantly
Solution Approach 1:
The patent divides the urban area into multiple tiles or blocks, processing each segment independently using monocular images and depth estimation models. This segmentation allows parallel processing and reduces the overall time required while maintaining accuracy through consistent processing of each segment.
Solution Approach 2:
The patent uses monocular satellite images as copies or representations of the urban area, processing these 2D images through depth estimation models to generate 3D representations. This copying approach eliminates the need for expensive on-site surveys and physical measurements while achieving comparable accuracy.
2Measurement precision
If traditional methods are used to create 3D models, then the depth detail capture is improved, but the hardware and on-site team requirements increase
Solution Approach 1:
The patent replaces mechanical surveying equipment and on-site measurement teams with computational methods. Specifically, it uses monocular image processing and depth estimation algorithms to extract depth information, eliminating the need for physical total stations, laser scanners, or manual measurements.
Solution Approach 2:
The patent introduces an intermediary processing layer between the monocular images and the final 3D model. This intermediary consists of depth estimation models and image processing algorithms that transform 2D visual data into 3D geometric information, enabling accurate depth capture without specialized hardware.
3Manufacturing precision
If high-resolution images are used, then the model detail and object capture are improved, but the processing complexity and data volume increase
Solution Approach 1:
The patent segments high-resolution images into smaller tiles or patches, processing each segment independently through depth estimation models. This segmentation reduces the computational complexity of processing any single image while maintaining the detail information from the high-resolution source through consistent segmentation across the entire area.
Data Source
AI summary
A computer-implemented method for generating a 3D model from an image of an area of interest (AOI), the method comprising: analyzing an image of the AOI with a segmentation module generating a depth map by analyzing an output of the segmentation module with a depth map module; and, converting the depth map into a height map and a 3D model of the AOI. A system for generating a 3D model from an image of an area of interest (AOI) and a non-transitory computer-readable medium comprising instructions for performing the method are also disclosed.