Camera Calibration via Single Quadrangle Diagonal Analysis
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Solution Overview
Problem
Current camera calibration methods are cumbersome, requiring either complex 3D objects or multiple images of checkerboards, making them impractical for real-time applications, especially with inexpensive cameras like smartphone cameras.
Innovation Solution
A method and apparatus for camera calibration using a singular image of a quadrangle, which estimates intrinsic and extrinsic parameters by extracting diagonal parameters, calculating the projection center line, and applying homography to recover the environment quadrangle, facilitating robust and efficient camera calibration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional camera calibration methods using complex 3D objects or multiple checkerboard images are employed, then measurement precision can be achieved, but device complexity and time consumption increase significantly
Solution Approach 1:
The patent replaces expensive, complex, and durable calibration objects (like precision 3D objects or multiple checkerboards) with a simple, inexpensive quadrangle that can be easily created and discarded. This single quadrangle image suffices for calibration, eliminating the need for multiple images or complex objects while maintaining calibration accuracy.
Solution Approach 2:
The patent extracts only the essential geometric features (diagonals and their intersection) from complex calibration objects. By focusing solely on the quadrangle's diagonal properties rather than using entire complex 3D objects or multiple checkerboard patterns, the method simplifies the calibration process while preserving measurement precision.
2Measurement precision
If multiple images of checkerboards are used for calibration, then intrinsic and extrinsic parameters can be estimated, but calibration time increases making it unsuitable for real-time applications
Solution Approach 1:
The patent performs preliminary geometric analysis on the quadrangle image by pre-calculating diagonal parameters, intersection points, and segment ratios before actual calibration computation. This preliminary extraction of geometric features accelerates the overall calibration process while maintaining accuracy in parameter estimation.
Solution Approach 2:
The patent segments the calibration problem into distinct geometric components: diagonal detection, intersection point calculation, segment ratio computation, and parameter estimation. This segmentation allows each component to be processed independently and efficiently, reducing overall calibration time while preserving measurement precision.
3Ease of operation
If simple calibration objects are used, then ease of operation improves, but measurement precision deteriorates
Solution Approach 1:
The patent changes the parameter representation from complex object geometries to fundamental quadrangle diagonal parameters. By transforming the calibration problem into one based on diagonal lengths, intersection points, and segment ratios, the method achieves both operational simplicity and measurement precision through parameter transformation.
Solution Approach 2:
The patent transitions from using multiple 2D images or 3D objects to a single 2D quadrangle image with enhanced geometric analysis. By leveraging the diagonal dimension and intersection properties of the quadrangle, the method achieves accurate calibration from a simpler single-image input, effectively adding geometric dimensions to the analysis.
Data Source
AI summary
An apparatus for calibrating a camera comprises a camera; an input unit configured to receive a segmentation diagonal ratio of the environment quadrangle; a memory configured to store a program; and a processor configured to perform camera calibration based on the program, wherein the program is configured to: extract diagonal parameters of a centered quadrangle from the image; estimate length of a projection center line; estimate a projection angle; estimate an angle between diagonals of a projection quadrangle; estimate a projection center point; and estimate extrinsic and intrinsic parameters of the camera.