3D Building Models from Ground-Level Imagery and Point Clouds

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Solution Overview

Problem

Existing 3D map technologies for urban cities have limited texture resolution and geometry quality, are expensive, time-consuming, and lack robust real-time image data analytics, making them unsuitable for consumer and commercial use cases.

Innovation Solution

A system and method for generating 3D building models using ground-level and orthogonal imagery, involving image processing and texturing techniques to create accurate 3D building models by correlating ground-level images with orthogonal images to establish scale, rotation, and location, utilizing capture devices and a networked image processing system.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If aerial imagery or specialized camera-equipped vehicles are used to generate 3D maps, then 3D building models can be created, but the texture resolution and geometry quality are limited, and the process becomes expensive and time-consuming

Engineering Contradiction:
Improvetexture resolution and geometry qualityVSAvoidtime-consuming
Core Design Contradiction:
Measurement precisionVSLoss of time

Solution Approach 1:

Instead of using aerial imagery to create 3D models (top-down approach), the patent inverts the approach by using ground-level imagery captured from street view to generate 3D building models (bottom-up approach). This inversion enables higher texture resolution since ground-level cameras can capture detailed building facades up close, and the process becomes more efficient by leveraging existing street view image data that can be automatically processed.

Inventive Principle:
Principle #13The other way round (Inversion)

2Measurement precision

If aerial imagery or specialized camera-equipped vehicles are used to generate 3D maps, then 3D building models can be created, but the process becomes expensive

Engineering Contradiction:
Improvetexture resolution and geometry qualityVSAvoidcost
Core Design Contradiction:
Measurement precisionVSQuantity of substance

Solution Approach 1:

The patent uses ground-level street view images as copies or representations of building facades to construct 3D models. Instead of deploying expensive specialized camera-equipped vehicles, the system copies and processes readily available street view imagery data, significantly reducing costs while maintaining high texture resolution through careful image processing and photogrammetry techniques.

Inventive Principle:
Principle #26Copying

3Reliability

If existing 3D map technologies are used, then 3D building models can be generated, but they lack robust real-time image data analytics

Engineering Contradiction:
Improvereal-time image data analyticsVSAvoidsystem complexity
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The patent creates a multi-functional system that not only generates 3D building models from ground-level imagery but also performs real-time image data analytics on these models. The system can analyze building characteristics, detect changes over time, and provide various commercial and consumer applications from a single unified platform, making the complexity worthwhile by delivering multiple valuable functions simultaneously.

Inventive Principle:
Principle #6Universality (Multi-functionality)

Data Source

PatentUS12450832B2Systems and methods for generating three dimensional geometry
Publication Date: 2025.10.21 HOVER INC
  • US12450832B2 patent drawing
  • US12450832B2 patent drawing
  • US12450832B2 patent drawing

AI summary

Systems and methods are described for creating three dimensional models of building objects by creating a point cloud from a plurality of input images, defining edges of the building object's surfaces represented by the point cloud, creating simplified geometries of the building object's surfaces and constructing a building model based on the simplified geometries. Input images may include ground, orthographic, or oblique images. The resultant model may be scaled according to correlation with select image types and textured.