Point Cloud Visibility Mapping Using a Spherical Grid
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Solution Overview
Problem
The challenge of determining which points in a point cloud are visible or not visible from a given viewpoint, particularly when using lidar and camera sensors with different perspectives, leads to incorrect labeling of obscured points, as existing methods like 'Hidden Point Removal' and surface reconstruction are computationally intensive and prone to errors.
Innovation Solution
A method that transforms point cloud coordinates into spherical coordinates, uses a spherically curved grid to assign points to cells, and applies distance thresholds to identify and remove points not visible from the desired viewpoint, achieving a target set of visible points with a time complexity of O(n).
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If Hidden Point Removal method or surface reconstruction is used to determine visible points, then visibility determination accuracy is improved, but computational complexity increases significantly
Solution Approach 1:
The patent divides the point cloud into multiple point groups and processes them in batches. By segmenting the point cloud data and processing visible points for each segment separately, the computational complexity is reduced from O(n²) to O(n), while still achieving accurate visibility determination through systematic processing of each point group against the visible points of previously processed groups.
2Adaptability or versatility
If lidar and camera sensors are used with different perspectives, then environmental sensing capability is improved, but point labeling accuracy deteriorates due to visibility problems
Solution Approach 1:
The patent introduces an intermediary visibility determination process that mediates between the lidar point cloud and camera images. By first determining which lidar points are visible from the camera's viewpoint and using only those visible points for mapping and labeling, the system resolves the perspective mismatch issue and ensures accurate point labeling that reflects what the camera actually observes.
3Reliability
If all points in point cloud are processed for visibility determination, then completeness of visible point identification is improved, but processing time increases
Solution Approach 1:
The patent performs preliminary processing by sorting points based on their distance from the origin and dividing them into multiple point groups before the main visibility determination process. This preliminary organization allows the system to efficiently process points in batches, determining visibility for each group against the accumulated visible points from previous groups, thereby reducing overall processing time while maintaining complete identification of visible points.
Data Source
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AI summary
The invention relates to a method for determining a target quantity of point groups in a surrounding area (150), said point groups being visible or not visible of a specified viewing point (214) in the surrounding area (150), from a quantity of point groups, wherein a point group comprises one or more points (P, A, B). The method has the steps of: providing the quantity of point groups in the surrounding area with coordinates in an origin coordinate system (200); transforming the coordinates of the quantity of point groups into spherical coordinates in a target coordinate system, said viewing point (214) lying in the surrounding area in the origin of the target coordinate system; determining a spherically curved grid in spherical coordinates in the target coordinate system, said grid comprising grid points and/or cells; assigning each point group of at least some of the quantity of point groups to a cell or to a grid point; and for each of at least some of the cells of the grid or for each of at least some of the grid points of the grid assigned to more than one point group: determining a minimum and/or maximum spacing, a) determining a target quantity of point groups which are visible from a specified viewing point (214) in the surrounding area, and/or b) determining a target quantity of point groups which are not visible from a specified viewing point in the surrounding area; and providing the target quantity or the target quantities of point groups.