Line Parametric Object Estimation in 3D Point Clouds
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Solution Overview
Problem
Existing methods fail to accurately differentiate and extract line parametric objects (LPOs) from 3D data, such as those collected by laser scanning, due to the lack of effective techniques for identifying and modeling these objects within dense point clouds.
Innovation Solution
A method involving the generation of projection volumes along dominant axes of LPOs, projecting points onto these volumes, matching them with cross-section templates to determine element points, and generating parameter functions to express LPO parameters as functions of position, allowing for the extraction and modeling of LPOs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional point cloud processing methods are used, then the processing is simple, but the accuracy of differentiating and extracting LPOs is insufficient
Solution Approach 1:
The method segments the point cloud data by creating projection volumes at different positions along the dominant axis of LPOs. Each projection volume captures points from a specific segment of the LPO, allowing systematic extraction of geometric parameters along the object's length. This segmentation enables accurate differentiation of LPOs from other objects while maintaining manageable processing complexity.
Solution Approach 2:
The invention transforms the 3D point cloud data into 2D projections by projecting points onto projection planes perpendicular to the dominant axis. This dimensionality reduction simplifies the extraction process while preserving essential geometric information. The projection approach converts complex 3D pattern recognition into more manageable 2D template matching problems.
2Manufacturing precision
If projection volumes are generated at multiple positions along the dominant axis, then the precision of LPO parameter extraction is improved, but the computational complexity increases
Solution Approach 1:
The method performs preliminary actions by pre-defining projection volumes at multiple predetermined positions along the dominant axis before actual parameter extraction. This preparation allows the system to systematically capture geometric information at key locations, improving measurement precision while organizing the computational workload in a structured manner that manages complexity.
Solution Approach 2:
The invention uses template matching where a reference cross-sectional template is copied and applied at each projection position. Instead of developing complex extraction algorithms for each position, the same template is reused across multiple projection volumes, reducing computational complexity while maintaining high precision through consistent measurement methodology.
3Measurement precision
If template matching is performed for each projection volume, then the accuracy of identifying LPO element points is improved, but the processing time increases
Solution Approach 1:
The method applies periodic template matching at discrete projection positions along the dominant axis rather than continuously. By selecting key positions where projection volumes are created and performing template matching only at these periodic intervals, the system achieves accurate element point identification while significantly reducing the total number of matching operations required, thus lowering processing time.
Data Source
AI summary
A method may include projecting, onto a first projection plane of a first projection volume, first points from a point cloud of a setting that are within the first projection volume. Further, the method may include matching a plurality of the projected first points with a cross-section template that corresponds to a line parametric object (LPO) of the setting to determine a plurality of first element points of a first primary projected element. Additionally, the method may include projecting, onto a second projection plane of a second projection volume, second points from the point cloud that are within the second projection volume and matching a plurality of the projected second points with the cross-section template to determine a plurality of second element points of a second primary projected element. Moreover, the method may include generating a parameter function based on the first element points and the second element points.