Crowdsourced Image Analysis Platform Using Configurable Tag Radius
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Solution Overview
Problem
Current crowdsourcing platforms are inadequate for accurately locating targets of interest in image analysis tasks, as they either fail to provide precise location information or are inefficient in handling continuous variations in input data, particularly in search and locate problems where multiple participants may tag the same target with varying locations.
Innovation Solution
A crowdsourced search and locate platform that includes an application server and client interface, allowing participants to navigate to specific geospatial locations, tag objects, and display icons corresponding to objects, with a configurable radius to define agreement among users, thereby improving the accuracy of target location and classification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If crowdsourcing platforms use multiple participants to tag targets, then the quantity of analysis increases, but the precision of location estimation deteriorates due to varying user interpretations
Solution Approach 1:
The system implements feedback loops where location estimates from multiple users are aggregated and refined iteratively. The platform provides feedback to users about consensus locations and allows for correction of erroneous tags, continuously improving location precision while maintaining high productivity through parallel processing of multiple user inputs
Solution Approach 2:
The patent merges location estimates from multiple independent users into a single consensus location. By combining multiple measurements and using aggregation algorithms, the system achieves higher precision than individual users could attain alone, while preserving the productivity benefits of having many participants analyze images simultaneously
2Adaptability or versatility
If the platform processes continuous variations in input data from multiple users, then the adaptability increases, but the device complexity increases due to handling varying locations and agreements
Solution Approach 1:
The platform employs dynamic algorithms that adapt to continuous variations in user input data. The system adjusts its processing based on the distribution and agreement of user tags, dynamically modifying aggregation parameters and consensus thresholds to handle different scenarios without requiring complex static structures
Solution Approach 2:
The system changes processing parameters based on input characteristics, such as adjusting agreement thresholds and weighting factors according to the variability and distribution of user tags. This allows the platform to handle continuous variations adaptively while maintaining manageable complexity through parameter adjustment rather than structural complexity
3Measurement precision
If the platform requires highly-trained specialized image analysts, then the measurement precision improves, but the loss of time and cost increases
Solution Approach 1:
The patent segments the analysis task into multiple independent subtasks that can be performed simultaneously by multiple users. This parallel processing approach maintains precision through specialized analysis while dramatically reducing total completion time by distributing work across many analysts working concurrently rather than sequentially
Solution Approach 2:
The platform introduces an intermediary aggregation system that combines results from multiple analysts. This intermediary layer coordinates the work of many analysts, reconciles their findings, and produces a unified high-precision result, enabling both speed through parallel processing and accuracy through coordinated expertise
Data Source
AI summary
A crowdsourced search and locate platform, comprising an application server and a client interface application. The application server: receives connections from crowdsourcing participants; navigates a first crowdsourcing participant to a specific geospatial location; sends an image corresponding to the geospatial location to the first crowdsourcing participant; receives tagging data from the first crowdsourcing participant, the tagging data corresponding to a plurality of objects and locations identified by the first crowdsourcing participant. The client interface application: displays an image of a location; displays icons corresponding to objects that may be tagged; displays a navigation minimap adapted to allow a user to navigate; and upon the user's selecting a cursor location at which to place a new tag corresponding to a specific object type, displays a shape surrounding the cursor location, the effective radius of which is configurable and is adapted to define a region about the cursor location within which other tags by other users are considered to be in agreement with the new tag.