Automatic Vehicle Image Labeling System
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Solution Overview
Problem
The manual process of labeling and documenting vehicle images for repair estimates and insurance claims is time-consuming and prone to inconsistencies, leading to confusion and delays in the processing of these claims.
Innovation Solution
A system and method for automatically capturing and labeling vehicle images with identity information and pose data, using a computing device with a digital camera, where the user can select predefined icons or use voice activation to associate images with pre-assigned identifiers, reducing the need for manual input and ensuring consistent labeling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If manual labeling of photographs is performed, then image documentation is completed, but time consumption increases significantly
Solution Approach 1:
The system enables self-service automation where the computing device automatically performs image capture, labeling, and documentation without requiring manual human intervention. The device captures images via its camera, automatically labels them with relevant data, and stores them in the database, allowing the system to serve itself rather than requiring continuous human operation.
Solution Approach 2:
The patent replaces the mechanical manual process of labeling photographs with an automated electronic system. The computing device uses its camera to capture images and automatically generates and applies labels through software processing, substituting the manual mechanical action of writing or typing labels with automated digital processes.
2Productivity
If multiple photographs are taken without immediate downloading, then photography efficiency is improved, but tracking and associating images with vehicles becomes difficult
Solution Approach 1:
The system implements feedback mechanisms where the computing device automatically tracks and associates captured images with specific vehicles in real-time. The automatic labeling system provides continuous feedback about which images are linked to which vehicles, ensuring that even when multiple photographs are taken and stored locally, the association information is maintained and updated automatically.
Solution Approach 2:
The patent introduces an intermediary automatic labeling system that acts as a mediator between the image capture process and the final documentation storage. This intermediary system automatically manages the association between photographs and vehicles, serving as a bridge that maintains the relationship information without requiring direct manual intervention at each step.
3Reliability
If consistent labeling is implemented across different adjustors, then documentation quality improves, but standardization complexity increases
Solution Approach 1:
The patent implements a universal labeling system where the computing device applies standardized labels across all image documentation tasks regardless of which adjustor is performing the work. The system uses a unified set of labeling criteria and data structures that work universally for all vehicles and all adjustors, ensuring consistent documentation quality throughout the organization.
Data Source
AI summary
A vehicle image capture and labeling system operates to enable a user to capture vehicle photos, pictures, and/or images that are automatically labeled, i.e., annotated. In particular, the captured vehicle photos, pictures, or images are automatically labeled with certain vehicle identifier information, like a vehicle identification number (VIN), and pose information, that identifies a portion or view of the vehicle depicted within the image of the vehicle. The vehicle images may also be automatically labeled with one or more other image attributes or indicia, such as geospatial information corresponding to a location at which the photo or image was captured (e.g., global positioning system (GPS) data), time and date of image capture data, etc. The captured vehicle image and its label(s) may then be stored and used by other applications such as vehicle insurance claim applications, automobile repair estimate applications, etc.