Geometric Optimization for Environment Modeling
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Solution Overview
Problem
Current methods for generating environment models from satellite and aerial imagery require large amounts of data and result in slow processing times, failing to differentiate between various objects in the environment effectively.
Innovation Solution
A system and method for creating geometrically optimized low-data environment models by obtaining images, recognizing objects, determining shapes based on fitting quality, and generating models using stereo pairs, panchromatic images, and material classifications to produce accurate and complete models with reduced data requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution images are used to create high-density mesh models, then model accuracy is improved, but data requirements and processing time increase significantly
Solution Approach 1:
The patent segments the environment into distinct geometric primitives (buildings, trees, roads, water bodies) and models each separately using simplified geometries. This segmentation allows accurate representation of key features without requiring high-density meshes across the entire scene, thus reducing overall data requirements while maintaining model accuracy for important objects.
Solution Approach 2:
The patent uses satellite and aerial imagery as reference copies to extract geometric information, then creates simplified 3D models that capture essential features. Rather than directly converting high-resolution images into high-density meshes, the system uses the images as templates to guide the creation of optimized geometric representations, reducing data needs while preserving accuracy.
2Measurement precision
If high-resolution images are used to create high-density mesh models, then model accuracy is improved, but processing time increases significantly
Solution Approach 1:
The patent extracts only the essential geometric information needed for accurate modeling from the imagery, rather than processing the entire high-resolution image data. By extracting key features (building footprints, road centers, water body boundaries) and representing them with simplified geometries, the system achieves accurate models with significantly reduced processing time.
Solution Approach 2:
The patent changes the parameter representation from high-density vertex meshes to low-parameter geometric primitives (planes, cylinders, cones, polylines). This parameter transformation maintains visual and functional accuracy while dramatically reducing computational complexity and processing time.
3Productivity
If simple mesh representation is used, then processing time is reduced, but ability to differentiate objects is lost
Solution Approach 1:
The patent applies different geometric representations to different object types based on their specific characteristics. Buildings use extruded polygons with roof geometries, trees use cylinders with conical tops, roads use flattened cylinders, and water bodies use planes. This local quality approach maintains processing efficiency while preserving object differentiation through geometry-type associations.
4Productivity
If geometric optimization is applied to reduce data, then processing efficiency is improved, but model completeness may be compromised
Solution Approach 1:
The patent creates composite environment models by combining multiple geometric primitive types (planes, cylinders, cones, extruded polygons) to represent different environmental features. This composite approach maintains model completeness by appropriately representing each feature type with its suitable geometry while keeping overall data requirements low through the use of simplified primitives.
Data Source
AI summary
Embodiments of the invention provide systems and methods of generating a complete and accurate geometrically optimized environment. Stereo pair images depicting an environment are selected from a plurality of images to generate a Digital Surface Model (DSM). Characteristics of objects in the environment are determined and identified. The geometry of the objects may be determined and fit with polygons and textured facades. By determining the objects, the geometry, and the material from original satellite imagery and from a DSM created from the matching stereo pair point clouds, a complete and accurate geometrically optimized environment is created.