Point Cloud Filtering via Grid-Based Redundant Point Removal
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Solution Overview
Problem
Current point cloud processing systems are hindered by the presence of redundant points, which slow down processing speed and reduce accuracy, as existing technologies do not provide an automated method for filtering these points, relying instead on manual intervention.
Innovation Solution
A computing system and method that includes an acquiring module for obtaining a point cloud, a filtering module with a calculating sub-module to determine a cubical figure, a mapping sub-module to create a grid on the point cloud, and a redundant point deleting sub-module to retain the closest point to the grid center and remove redundant points, resulting in a filtered point cloud.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual filtering of redundant points is performed, then filtering can be done with simple methods, but processing speed decreases and productivity is reduced
Solution Approach 1:
The patent divides the point cloud into multiple grid cells based on spatial coordinates, processing each cell independently. This segmentation allows parallel processing of different regions, significantly improving processing speed while keeping each individual cell's processing simple and efficient.
Solution Approach 2:
The patent introduces a grid structure as an intermediary between the raw point cloud and the filtering operation. This grid mediates the processing by organizing points into manageable cells, enabling automated filtering algorithms to work efficiently on structured data rather than unstructured point clouds.
2Productivity
If automated filtering algorithms are implemented, then processing speed and productivity improve, but the system complexity increases
Solution Approach 1:
By dividing the point cloud into grid cells, the complex global filtering problem is broken down into multiple simple local filtering tasks. Each cell can be processed independently using straightforward algorithms, reducing overall system complexity while maintaining high productivity through parallel processing.
Solution Approach 2:
The patent applies different processing strategies to different regions by treating each grid cell independently. This allows locally optimized simple algorithms to be applied throughout the entire point cloud, achieving high overall efficiency without requiring a single complex global algorithm.
3Measurement precision
If redundant points are not filtered, then the point cloud retains complete information, but processing accuracy decreases due to redundant data
Solution Approach 1:
The patent extracts and removes redundant points from the point cloud while preserving essential geometric information. By identifying and eliminating duplicate or unnecessary points within each grid cell, the system achieves higher verification accuracy with a reduced point cloud, improving the signal-to-noise ratio in subsequent analysis.
Solution Approach 2:
The filtering process discards redundant points that do not contribute to geometric accuracy while recovering and preserving representative points that maintain the essential features of the scanned object. This selective discarding and recovery improves measurement precision without losing critical information.
Data Source
AI summary
An exemplary method for filtering a point cloud is disclosed. The method includes the steps of: acquiring a point cloud from a point cloud obtaining device; identifying an outmost point on each of surface edges of the point cloud in a coordinate system; determining a cubical figure that confines the point cloud and intersects at surface points of the point cloud; deriving the length, the width and the height of the cubical figure; mapping a grid on the cubical figure of the point cloud and obtaining a plurality of grid squares; and processing points in each of the grid squares to retain a selected point having a smallest distance from a center of the grid square and delete redundant points in the grid square, thereby yielding a filtered point cloud. A related system is also disclosed.