Moving-Object 3D Tracking With Unified Camera Calibration
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Solution Overview
Problem
Existing camera calibration methods require decomposition into intrinsic and extrinsic camera parameters, which is prone to reprojection errors and assumptions, limiting their accuracy and applicability to cameras with lens distortions or tilts.
Innovation Solution
A camera system and method that calibrates without decomposing camera parameters, using a transformation matrix to implicitly handle both intrinsic and extrinsic parameters, allowing calibration with any lens or tilt, and adjusting these parameters through affine corrections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If camera parameters are decomposed into intrinsic and extrinsic parameters, then the calibration process becomes more structured and manageable, but reprojection errors increase and measurement precision deteriorates
Solution Approach 1:
The patent merges intrinsic and extrinsic camera parameters into a unified projection matrix that maps 3D world points directly to 2D image points without decomposition. This combined approach eliminates the reprojection errors that arise from separate parameter estimation and avoids the need for iterative optimization, thereby maintaining measurement precision while preserving calibration structure.
Solution Approach 2:
The patent extracts the essential calibration information into a simplified projection matrix that contains only the necessary parameters for accurate 3D-to-2D mapping. By removing redundant decomposition steps and assumptions about lens distortion or tilt, the method achieves higher precision with a more direct calibration approach.
2Device complexity
If assumptions are made about intrinsic or extrinsic camera parameters (e.g., no lens distortion, no tilt), then the calibration complexity is reduced, but the adaptability to different camera setups deteriorates
Solution Approach 1:
The patent creates a universal projection matrix framework that works with any camera configuration without requiring specific assumptions about lens distortion or tilt. The method is adaptable to different lenses and camera orientations by simply adjusting the transformation parameters, making it universally applicable to diverse camera setups while maintaining simplicity.
Solution Approach 2:
The patent allows the projection matrix parameters to be adjusted based on the specific camera configuration being used. By changing the transformation parameters rather than making fixed assumptions, the method maintains low complexity while achieving high adaptability to different lenses, tilts, and camera orientations.
3Ease of manufacture
If decomposition into intrinsic and extrinsic parameters is performed, then the calibration can be done in standard steps, but ambiguities and errors in parameter extraction increase
Solution Approach 1:
The patent combines the extraction of intrinsic and extrinsic parameters into a single direct estimation of the projection matrix. This unified approach eliminates the sequential decomposition process that introduces ambiguities and errors, providing a more reliable calibration procedure that maintains standardization through a single-step transformation matrix calculation.
Data Source
AI summary
An image taken of an object in motion is received. At least three markers on the object in motion in the image are detected. Image points of the three markers are determined. Based on the image points of the three markers, depths of the object in motion at the image points are determined, where the depths are determined relative to an image plane of the image. Using the image points and the depths, three-dimensional (3D) world points representing a position of the object in motion in a 3D real world coordinate are determined.