Geolocated Image Establishment Anchoring
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Solution Overview
Problem
Existing directories face delays and inaccuracies in updating establishment locations due to the need for manual input, leading to potential failures in maintaining accurate location data as businesses open, close, or move.
Innovation Solution
A method and system that utilize image processing to determine and update an establishment's presence at a geographic location by comparing captured images with a set of logo-labeled images containing geographic location information and identification marks, associating the establishment with a location in a database based on proximity and confidence levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual input is used to update establishment locations in directories, then accuracy of location data can be maintained, but time consumption and delays increase
Solution Approach 1:
The patent replaces manual mechanical input methods with automated image recognition and processing systems. Cameras capture images of establishments, and computer vision algorithms automatically identify and extract location information, substituting human manual entry with automated optical and computational systems.
Solution Approach 2:
The system enables self-service by allowing the directory update process to occur automatically without human intervention. The image recognition system autonomously captures, processes, and updates establishment location data, making the system self-sufficient in maintaining directory accuracy.
2Reliability
If manual updating of establishment locations is performed, then control over data accuracy is maintained, but productivity and update frequency decrease
Solution Approach 1:
The patent implements continuous automatic updating through persistent image capture and processing operations. The system continuously monitors for changes in establishment locations by repeatedly capturing and analyzing images, ensuring uninterrupted updates without the gaps inherent in manual processes.
Solution Approach 2:
Manual updating operations are replaced with automated image capture devices and computer vision processing systems that operate continuously at high speed, dramatically increasing update frequency while maintaining or improving accuracy through algorithmic verification.
3Productivity
If automated image recognition is used to update establishment locations, then update speed and productivity increase, but system complexity increases
Solution Approach 1:
The patent employs universal image recognition algorithms that can identify multiple types of establishments and location markers across diverse scenarios. The same core image processing system handles various establishment types, signage formats, and environmental conditions, reducing the need for separate specialized systems.
4Reliability
If frequent automatic updates are implemented, then location data currentness is improved, but resource consumption increases
Solution Approach 1:
The system implements periodic image capture and processing cycles rather than continuous operation. Updates occur at optimized intervals based on establishment activity patterns, reducing unnecessary computational resource consumption while maintaining location data currentness through strategically timed monitoring.
Data Source
AI summary
The technology relates to determining an establishment's presence at a geolocation. A computing device may receive a first image including location data associated with the first image's capture. A set of images, which include location information and one or more identification marks associated with one or more establishments may also be received. The computing device may compare the first image to the set of images to determine whether the first image contains one of the one or more identification marks, and determine that one of the one or more establishments, associated with the one of the one or more identification marks contained in the first image, is currently located within a set proximity of the first image location. The computing device may also update a location database by associating the one of the one or more establishments with a location within a set proximity of the first image location.