3D Planarity Detection Using Adaptive Search Radius
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Solution Overview
Problem
Existing methods for determining planarity in 3D data sets are prone to inaccuracies due to either large search areas including non-planar objects or small search areas being dominated by noise, necessitating a technique that balances these factors without relying on analyst expertise.
Innovation Solution
A method involving dividing 3D data into contiguous regions, calculating measures of variation in z-location, identifying a search radius based on a histogram of these variations, and segregating the data into regions of this radius to determine planarity, using standard deviation and covariance matrices for analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a large search area is selected for planarity determination, then the chance of including non-planar objects increases, but the calculation becomes more reliable due to sufficient data points
Solution Approach 1:
The patent divides the 3D data set into multiple overlapping candidate regions, each with a specified size. By segmenting the overall search space into smaller manageable regions, the system can evaluate planarity locally while maintaining sufficient data points in each region through the overlapping design, thus resolving the contradiction between region size and measurement accuracy.
Solution Approach 2:
The patent dynamically determines the optimal search radius by evaluating measures of variation in z-location across different candidate regions. The system adaptively selects regions that balance the inclusion of enough data points for reliable calculation while minimizing the inclusion of non-planar objects, making the search area dynamic rather than fixed.
2Measurement precision
If a small search area is selected for planarity determination, then noise dominates the calculation, but the calculation becomes faster and more focused
Solution Approach 1:
By segmenting the data into multiple overlapping candidate regions, the system ensures that each small region still contains sufficient data points for reliable noise-resistant calculation. The overlapping design allows the system to maintain small, focused search areas while collectively covering enough ground to achieve statistical reliability.
Solution Approach 2:
The patent combines multiple overlapping candidate regions in the evaluation process. By merging the results from multiple small regions, the system achieves the reliability of large sample sizes while maintaining the precision and focus of small, targeted search areas in each individual region.
3Ease of manufacture
If fixed search areas are used for planarity determination, then the process is simpler, but the results may be inaccurate for varying surface characteristics
Solution Approach 1:
The patent implements dynamic region evaluation by calculating measures of variation in z-location for each candidate region and using these measures to identify optimal search radii. This dynamic approach adapts to varying surface characteristics in different regions, improving measurement precision while maintaining a systematic process through automated evaluation criteria.
Solution Approach 2:
The system changes the parameter of search radius based on the measured variation in z-location for different candidate regions. By adjusting the search radius parameter dynamically according to local surface characteristics, the system achieves accurate planarity measurements for varying surfaces while keeping the overall process systematic through automated parameter adaptation.
Data Source
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AI summary
Systems, devices, methods, and computer-readable media for determining planarity in a 3D data set are provided. A method can include receiving or retrieving three-dimensional (3D) data of a geographical region, dividing the 3D data into first contiguous regions of specified first geographical dimensions, determining, for each first contiguous region of the first contiguous regions, respective measures of variation, identifying, based on the respective measures of variation, a search radius, dividing the 3D data into respective second contiguous or overlapping regions with dimensions the size of the identified search radius, and determining, based on the identified search radius, a planarity of each of the respective second contiguous or overlapping regions.