Camera External Parameter Calibration via 3D Point Cloud Back-Projection
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Solution Overview
Problem
Conventional camera external parameter calibration methods require calibration reference objects of known sizes, which limits efficiency and accuracy, and necessitate the calibration reference object to remain in the calibration scenario until data is acquired.
Innovation Solution
A method involving the acquisition of three-dimensional point clouds and synchronized two-dimensional images, establishing a transformation relationship between point cloud and image coordinate systems, back-projecting point clouds onto the image plane, and adjusting transformation parameters to map projection points onto the image, allowing for external parameter calibration without needing to determine the size of the calibration reference object.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If calibration reference objects of known sizes are used in conventional calibration methods, then the external parameters can be determined through established corresponding relationships, but the calibration process becomes complex and time-consuming, and the reference object must remain in the calibration scenario until data acquisition is complete
Solution Approach 1:
The patent uses three-dimensional point cloud data as a digital copy of the calibration reference object, replacing the need for physical reference objects with known dimensions. The point cloud coordinate system serves as a virtual model that can be transformed and projected, eliminating the requirement for physical measurement tools and reducing calibration time while maintaining accuracy
Solution Approach 2:
The patent transforms the calibration approach by changing from using fixed physical dimensions to using coordinate system transformations. By establishing transformation relationships between point cloud coordinates and image coordinates, and adjusting transformation parameters during projection, the method achieves calibration without relying on pre-known physical sizes, thereby reducing calibration time and complexity
2Measurement precision
If calibration reference objects of known sizes are used, then corresponding relationships can be established, but the device complexity and calibration costs increase
Solution Approach 1:
The patent replaces complex physical calibration reference objects with three-dimensional point cloud data, which can be obtained through laser scanning or other 3D sensing technologies. This digital copy eliminates the need for specialized calibration artifacts, reducing device complexity and costs while maintaining the ability to establish accurate corresponding relationships through coordinate transformations
Solution Approach 2:
The patent substitutes mechanical measurement systems (physical reference objects with known dimensions) with computational methods (coordinate system transformations and projections). By using mathematical transformations between point cloud coordinates and image coordinates, the method eliminates the need for physical measurement tools and complex calibration hardware, thereby reducing device complexity
3Measurement precision
If the calibration reference object remains in the calibration scenario during data acquisition, then accurate calibration can be achieved, but the calibration process cannot be completed and the object cannot be removed
Solution Approach 1:
The patent performs preliminary data acquisition by capturing both the three-dimensional point cloud data and two-dimensional image data of the calibration reference object before removal. By completing data collection in advance while the object is still in position, the method enables subsequent calibration computations to be performed offline, allowing the object to be removed from the scenario without compromising calibration accuracy
Data Source
AI summary
A method and an apparatus for calibrating an external parameter of a camera are provided. The method may include: acquiring a time-synchronized data set of three-dimensional point clouds and two-dimensional image of a calibration reference object, the two-dimensional image being acquired by a camera with a to-be-calibrated external parameter; establishing a transformation relationship between a point cloud coordinate system and an image coordinate system, the transformation relationship including a transformation parameter; back-projecting the data set of the three-dimensional point clouds onto a plane where the two-dimensional image is located through the transformation relationship to obtain a set of projection points of the three-dimensional point clouds; adjusting the transformation parameter to map the set of the projection points onto the two-dimensional image; and obtaining an external parameter of the camera based on the adjusted transformation parameter and the data set of the three-dimensional point clouds.