3D Point Cloud Mirror Surface Position Measurement
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing 3D laser scanners struggle to accurately measure and remove artifacts caused by reflective surfaces like mirrors and windows, which lead to virtual points in the point cloud, disturbing registration and visual quality.
Innovation Solution
A computer-implemented method that divides the point cloud into parts based on an initial guess of a reflective surface's location, registers the virtual points after a mirror operation, and determines the accurate position and orientation of the reflective surface by transformation, allowing for the approximation of the surface's extent and shape.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If laser scanners measure points on reflecting surfaces, then measurement coverage is improved, but virtual points are created that disturb registration and visual quality
Solution Approach 1:
The point cloud is segmented into two parts: points in front of the reflective surface and points behind the reflective surface. This segmentation allows the algorithm to identify and separate virtual points from real points, enabling removal of artifacts while preserving legitimate measurements.
Solution Approach 2:
The patent converts the harmful virtual points into a useful diagnostic tool. By detecting the geometric pattern of virtual points behind reflective surfaces, the algorithm identifies the location and orientation of reflective surfaces, which then enables targeted removal of artifacts while preserving legitimate data.
2Object-generated harmful factors
If manual removal of artifacts is performed, then visual quality is improved, but processing time increases
Solution Approach 1:
The system performs automatic artifact removal without manual intervention. The algorithm autonomously identifies reflective surfaces, separates virtual points from real points, and removes artifacts, eliminating the need for tedious manual correction while maintaining high visual quality.
Solution Approach 2:
The patent introduces an automatic processing intermediary (the artifact removal algorithm) that mediates between the raw point cloud data and the final visual output. This intermediary automatically handles artifact removal, saving time compared to manual processing.
3Area of stationary object
If beam steering mechanism scans reflecting surfaces, then scan coverage is improved, but light deflection causes measurement errors
Solution Approach 1:
The patent extracts and removes the harmful component (virtual points) from the point cloud while preserving the legitimate measurements. By taking out the artifact points that cause measurement errors, the system maintains scan coverage while improving measurement accuracy.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This method effectively removes reflection artifacts from 3D point clouds, improves registration accuracy, and increases point density by adding mirrored points back into the cloud, resulting in a more accurate and visually clear representation of the scanned environment.
Implementation Method 1
A time-of-flight (TOF) laser scanner is a scanner in which the distance to a target point is determined based on the speed of light in air between the scanner and a target point
Implementation Method 2
The beam steering mechanism includes a first motor that steers the beam of light about a first axis by a first angle that is measured by a first angular encoder (or other angle transducer). The beam steering mechanism also includes a second motor that steers the beam of light about a second axis by a second angle that is measured by a second angular encoder (or other angle transducer)
Implementation Method 3
Laser scanners are typically used for scanning closed or open spaces such as interior areas of buildings, industrial installations and tunnels. They are used, for example, in industrial applications and accident reconstruction applications. A laser scanner optically scans and measures objects in a volume around the scanner through the acquisition of data points representing object surfaces within the volume. Such data points are obtained by transmitting a beam of light onto the objects and collecting the reflected or scattered light to determine the distance, two-angles (i.e., an azimuth and a zenith angle), and optionally a gray-scale value
Data Source
AI summary
Embodiments for measuring/determining the position and shape of a mirror surface in 3D point clouds are provided given the knowledge of the position from where the points of the point cloud were captured. Starting from an initial rough estimation of a modelled mirror surface, the point cloud is divided into two parts: the presumable virtual points that are behind the modelled mirror with respect to the scanner position and the rest or remainder of the points in the point cloud. The presumable virtual points are mirrored back at the modelled mirror surface and then registered against the rest of the point cloud. The registered points cleaned from outliers together with the associated virtual points define the actual position and shape of the mirror surface.