Auxiliary Camera Self-Calibration for Ultrawide 3D Laser Scanners
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Solution Overview
Problem
Existing 3D scanners face challenges in efficiently acquiring and colorizing 3D scans due to the time-consuming nature of high dynamic range imaging techniques and systematic errors in mapping 3D points to camera image space, particularly when using ultrawide-angle lenses.
Innovation Solution
A method involving a 3D scanner with an integrated ultrawide-angle camera and a dynamic calibration process using feature extraction and matching algorithms to generate a control image, allowing for rapid acquisition and accurate colorization of 3D scans.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high dynamic range imaging techniques are used to acquire multiple images at each location with different exposure settings, then color image quality is improved, but acquisition time increases significantly
Solution Approach 1:
The patent performs camera calibration before the actual scanning process. By pre-determining the mapping relationship between camera image space and 3D scanner coordinate space through calibration targets and feature point extraction, the system eliminates the need for multiple exposure shots during actual operation. This preliminary calibration action enables single-shot color image acquisition while maintaining high quality.
2Productivity
If ultrawide-angle lenses are used to reduce the number of images required for colorization, then productivity is improved, but systematic errors in mapping 3D points to image space increase
Solution Approach 1:
The patent transforms the coordinate system parameters by establishing a mapping relationship between camera image space and 3D scanner coordinate space. Through calibration, the system determines transformation parameters that account for the ultrawide-angle lens distortion, enabling accurate mapping despite the wide field of view. This parameter transformation resolves the distortion issues while maintaining high productivity.
3Measurement precision
If multiple images are stitched to form a control image for calibration, then calibration accuracy is improved, but processing complexity increases
Solution Approach 1:
The patent extracts key feature points from calibration target images and uses only these extracted features for establishing the mapping relationship. By taking out only the essential feature points rather than processing entire images, the system achieves accurate calibration while significantly reducing processing complexity. This extraction approach simplifies the calibration process while maintaining precision.
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
The method reduces the number of images required for colorization and addresses systematic errors, enabling faster and more precise 3D scanning with accurate color information.
Implementation Method 1
transmitting a beam of light onto the objects and collecting the reflected or scattered light to determine the distance, two-angles (i.e., azimuth and a zenith angle), and optionally a gray-scale value
Implementation Method 2
transmitting a beam of light onto the objects and collecting the reflected or scattered light to determine the distance, two-angles (i.e., azimuth and a zenith angle), and optionally a gray-scale value
Implementation Method 3
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 4
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 another 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 another angle transducer)
Data Source
AI summary
A method includes capturing, by a three-dimensional (3D) scanner, a 3D point cloud, and capturing, by a camera, a control image by capturing and stitching multiple images of the surrounding environment. The method further includes capturing, by an auxiliary camera, an ultrawide-angle calibration image. The method further includes dynamically calibrating the auxiliary camera using the 3D point cloud, the control image, and the calibration image. The calibrating includes extracting a first plurality of features from the control image and extracting a second plurality of features from the calibration image. Further, a set of matching features are determined from the first and second sets of features. A set of control points is generated using the set of matching features by determining points in the 3D point cloud that correspond to the set of matching features. Further, a self-calibration of the auxiliary camera is performed using the set of control points.