3D Evaluation Point Extraction Using Image Conjugate Matching
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Solution Overview
Problem
Current methods for ground truth assessment of 3D data sets require manual selection of three-dimensional evaluation points, which is inefficient and labor-intensive, limiting the number of samples that can be assessed over areas of interest.
Innovation Solution
An automated method for identifying corresponding point cloud locations of three-dimensional evaluation points using image registration techniques, including coarse and fine registration processes, to align synthetic image data with real image data, allowing for efficient regression testing of true and predicted errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual selection of three-dimensional evaluation points is used, then measurement precision can be ensured, but productivity is reduced and labor intensity increases
Solution Approach 1:
The patent uses image conjugates (2D projections) as copies of the 3D points to automatically identify corresponding points in the point cloud. By projecting 3D points to 2D image space and matching with conjugate points, the system replicates the manual selection process automatically, maintaining accuracy while increasing productivity
Solution Approach 2:
The patent replaces the manual mechanical selection process with an automated computational system. Image registration algorithms and point cloud matching techniques substitute human operators, enabling high-throughput assessment of 3DEPs without sacrificing measurement precision
2Productivity
If automated identification method is used, then productivity is improved, but device complexity increases
Solution Approach 1:
The patent divides the complex automated identification process into distinct segments: image registration phase, conjugate point matching phase, and 3DEP identification phase. This segmentation allows each component to be independently optimized and managed, reducing overall system complexity while maintaining high productivity
Solution Approach 2:
The image registration system performs multiple functions: aligning synthetic imagery with real imagery, establishing geometric transformations, and enabling automatic conjugate point matching. This multi-functionality reduces the need for separate specialized systems, managing complexity while enhancing productivity
Data Source
AI summary
Devices, systems, and methods for three-dimensional (3D) evaluation point (3DEP) identification; wherein a method can include receiving a first conjugate point of a first real two-dimensional (2D) image, receiving a second conjugate point of a second real 2D image, the first and second conjugate points corresponding to a same geographical location, determining a first set of points of a 3D point set that project to within a specified distance of the first conjugate point in the first real 2D image, determining a second set of points of the 3D point set that project to within the specified distance of the second conjugate point in the second real 2D image, identifying a common point in both the first set of points and the second set of points that satisfies a specified heuristic relative to all other points in both the first set of points and the second set of points, and using the point as the 3DEP.