Utility Pole Geotagging via Street View Triangulation
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Solution Overview
Problem
Current methods for determining the geographic location of specific objects, such as utility poles or fire hydrants, are inefficient and inaccurate, relying on manual inspection or reviewing aerial or satellite imagery, which can be time-consuming and prone to errors due to incomplete documentation or poor image resolution.
Innovation Solution
A system and method that analyzes a plurality of street view images to identify objects, generates vectors based on detected objects, and triangulates their geographic location by combining these vectors, with additional filtering to confirm accuracy using clustering algorithms and reference to aerial or satellite imagery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual inspection is used to determine geographic location of objects, then measurement precision can be achieved, but loss of time increases and productivity decreases
Solution Approach 1:
The patent replaces manual mechanical inspection with an automated image processing system that uses computer vision algorithms to detect objects and determine their geographic locations automatically, eliminating the need for human inspectors to physically visit and record locations while maintaining measurement precision
Solution Approach 2:
The patent uses copies of aerial or satellite images as substitutes for direct manual inspection of the physical area. By analyzing image copies rather than physically visiting the location, the system achieves both speed and accuracy without requiring human presence at each inspection point
2Productivity
If aerial or satellite imagery is reviewed to identify object locations, then productivity increases, but measurement precision deteriorates due to poor image resolution
Solution Approach 1:
The patent segments the image analysis process into multiple stages: initial automated detection using computer vision algorithms, verification against reference data, and refinement through clustering algorithms. This segmentation allows the system to maintain high productivity while improving precision by processing images in manageable, verifiable steps
Solution Approach 2:
The patent implements feedback mechanisms where detected object locations are verified against reference data (such as existing utility pole locations or aerial imagery) and refined through iterative clustering algorithms. This feedback loop corrects errors and improves measurement precision while maintaining the speed benefits of automated processing
3Productivity
If automated image analysis is used to detect objects, then productivity increases, but device complexity increases
Solution Approach 1:
The patent employs a multi-functional vision system that performs multiple tasks using the same infrastructure: detecting objects, determining their geographic locations, verifying against reference data, and refining results through clustering. By making the system multi-functional, the patent avoids the need for separate specialized systems for each task, thereby managing complexity while maintaining high productivity
Data Source
AI summary
According to one aspect, embodiments of the invention provide a method for determining the geographic location of an object, the method comprising retrieving at a vision system a plurality of images from a database, each image related to a respective vantage point, detecting, with the vision system, the object in at least two of the plurality of images, generating a vector in relation to the respective vantage point for each image in which the object was detected, and triangulating, based on the intersection of at least two vectors, the geographic location of the object.