Multi-View 3D Damage Detection for Consistent Vehicle Inspection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional vehicle inspection for damage is a manual, time-intensive process prone to variability and financial losses due to human subjectivity, lacking consistency and trust in damage evaluation.
Innovation Solution
An automated system using multi-view data analysis with neural networks to construct a 3D object model, detect damage components, and provide consistent damage estimates through multi-view representations, heatmaps, and 3D models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual inspection is used, then flexibility and adaptability are maintained, but time consumption and cost increase significantly
Solution Approach 1:
The patent replaces manual mechanical inspection with an automated computer-based system that captures images and automatically processes them through algorithms to detect damage, eliminating the need for manual visual inspection and significantly reducing time consumption
Solution Approach 2:
The system enables self-service inspection where the computer automatically performs damage detection without requiring human operators to physically inspect each vehicle, allowing the system to serve itself in identifying and reporting damage
2Reliability
If manual inspection is used, then human judgment and experience can be applied, but consistency and reliability of results deteriorate due to human subjectivity
Solution Approach 1:
The patent replaces human judgment with automated image processing algorithms and machine learning models that objectively analyze captured images, eliminating human subjectivity and ensuring consistent, reliable damage evaluation across all inspections
Solution Approach 2:
The system transforms the inspection process from subjective human evaluation to objective parameter-based analysis by measuring specific features in images such as pixel intensity, edge detection, and geometric properties to determine damage characteristics
3Measurement precision
If comprehensive multi-view data analysis is implemented, then measurement precision and detection accuracy improve, but device complexity and processing requirements increase
Solution Approach 1:
The patent divides the inspection process into distinct stages: image capture from multiple views, pre-processing of individual images, feature extraction, damage detection, and result aggregation. This segmentation allows each component to be optimized independently while maintaining overall system accuracy
Solution Approach 2:
The system transitions from single-view to multi-view analysis by capturing images from multiple angles and perspectives, adding spatial dimensions to the inspection process. This enables more comprehensive damage detection by examining objects from different viewpoints and combining the information
Data Source
AI summary
A plurality of images may be analyzed to determine an object model. The object model may have a plurality of components, and each of the images may correspond with one or more of the components. Component condition information may be determined for one or more of the components based on the images. The component condition information may indicate damage incurred by the object portion corresponding with the component.