Automated 3D Model Generation from Aerial Elevation Data
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Solution Overview
Problem
Manually creating 3D models of structures in metropolitan areas is labor-intensive due to the large number of structures and complexity of geographic areas, which existing methods fail to address efficiently.
Innovation Solution
A method that projects elevation values from a 3D surface into a 2D plane, segments the intensity image to detect the geographic footprint of structures, and constructs a 3D model by assigning heights based on elevation values, allowing for automated generation of 3D models of structures within geographic areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual methods are used to create 3D models of structures in metropolitan areas, then model accuracy can be maintained, but the process becomes extremely labor-intensive and time-consuming
Solution Approach 1:
The patent uses 2D aerial images as copies or representations of the actual geographic area, extracting structural information from these images to build 3D models. This copying approach allows automated processing while maintaining accuracy by using real-world visual data as the source.
Solution Approach 2:
The patent replaces manual mechanical modeling processes with automated image processing and computer vision algorithms. The system automatically detects building footprints, extracts walls, and generates 3D models from 2D images, substituting human labor with computational methods.
2Productivity
If automated methods are used to create 3D models from aerial images, then productivity increases, but the complexity of the system increases
Solution Approach 1:
The patent segments the complex task of 3D model creation into distinct modules: 2D image acquisition, footprint detection, wall extraction, and 3D model generation. This segmentation reduces system complexity by breaking down the overall process into manageable, independent components that can be processed separately.
Solution Approach 2:
The patent transitions from 2D aerial images to 3D models by adding the vertical dimension. The system detects 2D footprints and walls, then extrudes them into 3D structures with height information, effectively using dimensionality change to simplify the modeling process while maintaining geometric accuracy.
3Manufacturing precision
If detailed 3D models are created for every structure in a metropolitan area, then model detail and accuracy improve, but the resources required for processing and storage increase
Solution Approach 1:
The patent applies local quality by creating detailed 3D models only for specific structures (buildings) rather than uniformly processing the entire metropolitan area with the same level of detail. The system identifies building footprints and applies 3D modeling specifically to these regions, leaving other areas with less detailed representation.
Solution Approach 2:
The patent uses partial action by focusing computational resources on detecting and modeling only the building structures within the aerial image, rather than processing every feature in the geographic area. This selective approach reduces overall data volume while maintaining detailed models where needed.
Data Source
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AI summary
Constructing a three dimensional (3D) model of a structure may involve receiving a 3D surface representing a geographic area, the surface having elevation values associated with points of the surface and the geographic area comprises a structure having a geographic footprint smaller than the geographic area. Constructing a 3D model may also involve projecting the elevation values into a two dimensional (2D) plane. Further, a 3D model may be constructed of the structure by assigning model heights based on the elevation values projected into points of the 2D plane.