3D Image Inspection With Contextual Model Alignment
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Solution Overview
Problem
Existing image inspection methods lack context and location data, making it difficult to accurately identify and analyze structures and objects in digital images, particularly in applications like construction and insurance, where precise information about structures is crucial for planning and cost estimation.
Innovation Solution
A system that captures contextual metadata from images, aligns them with 3D models, and generates an interactive environment for 2D and 3D viewing with annotation capabilities, allowing users to inspect and annotate structures and objects with precise location data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If images are taken very close to a roof surface to provide sufficient resolution, then image resolution is improved, but context and location information are lost
Solution Approach 1:
The patent transitions from 2D image inspection to 3D model-based inspection. By creating three-dimensional models of structures and overlaying images onto these models, the system preserves both high-resolution image details and contextual spatial information. The 3D model provides the missing dimension of spatial context, allowing users to understand the location and orientation of each image fragment within the overall structure.
Solution Approach 2:
The patent introduces a 3D model as an intermediary between the close-up images and the final inspection result. This intermediary structure serves as a framework that organizes and contextualizes multiple high-resolution images, maintaining their detailed information while adding spatial relationships and location data that would be lost in individual images alone.
2Reliability
If multiple images are captured to provide complete coverage, then inspection completeness is improved, but data processing complexity increases
Solution Approach 1:
The patent merges multiple individual images into a unified 3D model representation. By combining multiple image datasets into a single integrated three-dimensional model, the system achieves complete structural coverage while simplifying the processing workflow. The 3D model serves as a consolidated data structure that inherently organizes spatial relationships, reducing the complexity of managing multiple separate image files.
Solution Approach 2:
The patent segments the inspection process into distinct phases: image capture, 3D model generation, image-to-model alignment, and annotation. This segmentation allows each component to be processed independently and efficiently, with the 3D model acting as an intermediate representation that simplifies subsequent analysis tasks compared to processing raw image sequences directly.
3Measurement precision
If manual inspection methods are used to ensure accurate identification, then inspection accuracy is improved, but inspection time increases
Solution Approach 1:
The patent implements automated alignment and identification features where the system performs self-alignment of images to 3D models using feature recognition and coordinate matching. The automated annotation tools allow the system to pre-identify structures and objects, reducing the manual effort required while maintaining high accuracy. Users can review and verify results rather than performing complete manual inspection.
Solution Approach 2:
The patent replaces manual mechanical inspection processes with computer vision and automated image processing algorithms. The system automatically aligns images, identifies structures, and generates annotations through computational methods, substituting human manual analysis with automated digital processing that maintains accuracy while significantly reducing inspection time.
Data Source
AI summary
A system and method for generating models from digital images in an interactive environment comprising a memory and a processor in communication with the memory. The processor captures or derives metadata for one or more digital images. The processor derives transforms from the metadata to align the digital images with one or more three-dimensional (“3D”) models of objects/structures represented in the digital image. The processor generates an interactive environment which allows a user to view a contextual model of each of the objects/structures in two dimensional (“2D”) and 3D views.