Geolocation Estimation via Ground-to-Overhead Image Transformation
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Solution Overview
Problem
Existing methods for determining the geographic location of image data rely heavily on image matching databases, which are limited and computationally expensive, especially for infrequently photographed locations, and struggle with comparing ground-level images to overhead images due to their orthogonal perspectives.
Innovation Solution
The system estimates the geographic location by transforming ground-level image data into a reconstructed scene using feature point matching and Euclidean reconstruction, correlating the ground-level viewpoint with overhead images through spatial information, and utilizing occupancy grid maps for efficient matching.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional image matching algorithms are used to determine location, then locations that are frequently photographed (such as tourist destinations) can be easily identified, but image data captured at other locations cannot be effectively matched
Solution Approach 1:
Instead of matching ground-level images to ground-level database images (conventional approach), the patent inverts the approach by transforming ground-level images into overhead views and matching them against overhead satellite/aerial images in the database. This inversion of perspective allows the system to effectively match locations that are not frequently photographed from ground level, thereby improving both location identification accuracy and adaptability to different locations.
Solution Approach 2:
The patent changes the dimensional perspective by transforming images from ground-level (horizontal) view to overhead (vertical) view. This dimensional transformation allows the system to access a different viewing dimension that is not limited by the constraints of ground-level photography, enabling effective matching at locations regardless of how frequently they appear in conventional ground-level image databases.
2Measurement precision
If image matching databases are used to determine geographic location, then location can be determined when matching images are available, but the method is limited by database content and computationally expensive
Solution Approach 1:
By transforming ground-level images into overhead views, the patent enables matching against a different type of database content (aerial/satellite imagery) that covers broader geographic areas including locations not frequently photographed from ground level. This dimensional change expands the effective database coverage while the hierarchical searching methodology improves search efficiency.
Solution Approach 2:
The patent replaces the conventional mechanical image-matching process with a transformed approach using overhead view transformation and hierarchical searching. This substitution of the matching mechanism with a different methodology (overhead transformation + hierarchical search) improves both the coverage of matchable locations and the computational efficiency of the search process.
3Adaptability or versatility
If ground-level images are compared directly to overhead images, then perspective differences make matching difficult, but transformation to reconstructed scene enables correlation
Solution Approach 1:
The patent transforms ground-level images into overhead views to match the perspective of satellite/aerial images in the database. This dimensional transformation resolves the perspective mismatch problem, enabling effective cross-perspective matching. The transformation complexity is managed through automated processing pipelines that convert ground-level coordinates to overhead coordinates using geometric transformation algorithms.
Data Source
AI summary
In some embodiments, a system and method for estimating the geographical location at which image data was captured with a camera identifies matching feature points between the captured images, estimates a pose of the camera during the image capture from the feature points, performs geometric reconstruction of a scene in the images using the estimated pose of the camera to obtain a reconstructed scene, and compares the reconstructed scene to overhead images of known geographical origin to identify potential matches.