Camera Calibration Using Non-Point Landmark Alignment
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Solution Overview
Problem
Existing camera calibration techniques are impractical for outdoor environments, such as sporting events, due to the difficulty in using point-based targets like checkerboards, especially when dealing with non-planar surfaces and dynamic camera movements.
Innovation Solution
A method using image-based alignment that aligns non-point landmarks in a reference image with counterparts in the camera image, employing gradient-based image alignment optimization to estimate intrinsic, extrinsic, and lens distortion parameters, allowing for calibration of cameras capturing dynamic and non-planar scenes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If point-based targets like checkerboards are used for camera calibration, then calibration accuracy can be achieved, but the method becomes impractical for outdoor environments and non-planar surfaces
Solution Approach 1:
The patent uses a pre-rendered template image of the playing field as a virtual copy of the real scene, eliminating the need for physical calibration targets. This template is synthesized from 3D field geometry and markings, allowing calibration in outdoor environments without physical checkerboards or point targets.
Solution Approach 2:
Instead of projecting 3D world points to 2D image points (traditional calibration), the patent inverts the approach by rendering a 2D template image from 3D field geometry and comparing it with the actual camera image. This inversion allows using non-planar field surfaces as calibration references.
2Measurement precision
If feature-based alignment is used to initialize image-based alignment, then coarse alignment can be achieved, but the process becomes complex and time-consuming
Solution Approach 1:
The patent extracts and removes the feature-based alignment initialization step from the calibration process, using only gradient-based optimization with the rendered template image. This extraction simplifies the overall process while maintaining alignment accuracy through direct gradient descent on the error image.
3Measurement precision
If standard camera calibration algorithms are used, then calibration can be performed, but the process requires exhaustive feature extraction and corresponding point matching
Solution Approach 1:
The patent replaces exhaustive feature extraction and point matching with a rendered template image comparison approach. By using a pre-synthesized template from 3D field geometry, the system avoids time-consuming feature detection and correspondence establishment, directly computing camera parameters through gradient-based optimization of the rendered template against the captured image.
Data Source
AI summary
A system and method improves a camera calibration. The method includes receiving a camera image, a planar template pattern, a 3D geometry of a surface on which the planar template pattern is embedded, and a set of parameter values. The method includes rendering the planar template pattern into a camera perspective based on the parameter values to generate a warped template image. The method includes generating an error image including at least one non-zero difference between the camera image and the warped template image. The method includes adjusting the parameter values to reduce an error between the camera image and the warped template image.