Automatic Camera Calibration With Staged Lens Distortion Estimation
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Solution Overview
Problem
Current camera calibration methods in robotic systems often rely on manual operations and fail to accurately estimate lens distortion parameters, leading to reduced accuracy in camera calibration, especially when dealing with complex nonlinearity and stereo camera calibration.
Innovation Solution
A method involving multiple stages for estimating lens distortion parameters, where each stage focuses on a subset of parameters, using initial estimates from previous stages to refine subsequent calculations, and applying simplifications to lens distortion models to improve accuracy, along with determining error parameters for stereo calibration to enhance spatial relationship estimation between cameras.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual camera calibration operations are used, then the calibration process can be performed with simple equipment, but the calibration accuracy deteriorates due to human error and inefficiency
Solution Approach 1:
The system performs automatic camera calibration without manual intervention. The control circuit automatically captures calibration images, detects pattern elements, calculates distortion parameters, and generates calibration information, eliminating the need for manual operations while improving accuracy
Solution Approach 2:
The patent replaces manual mechanical calibration operations with an automated computational system. The control circuit uses image processing algorithms and mathematical models to automatically determine camera parameters, substituting human operators with electronic automation
2Measurement precision
If all lens distortion parameters are estimated simultaneously in a single stage, then the calibration process is simpler and faster, but the estimation accuracy deteriorates due to parameter coupling and nonlinearity
Solution Approach 1:
The calibration process is divided into multiple stages, with each stage estimating a subset of lens distortion parameters. The first stage estimates certain parameters while fixing others, and subsequent stages refine the estimates by estimating different parameter subsets, reducing parameter coupling and improving accuracy
Solution Approach 2:
The system performs preliminary estimation of lens distortion parameters in the first stage before refining them in subsequent stages. Initial estimates are obtained by estimating a subset of parameters, which are then used as starting points for more accurate refined estimation in later stages
3Measurement precision
If complex lens distortion models are used to accurately represent all distortion effects, then the calibration accuracy improves, but the computational complexity and processing time deteriorate
Solution Approach 1:
The system estimates a subset of lens distortion parameters in each stage rather than all parameters simultaneously. By focusing on estimating specific parameter subsets in different stages, the system achieves accurate calibration without the computational burden of estimating all parameters in a single complex operation
Data Source
AI summary
A system and method for performing automatic camera calibration is provided. The system receives a calibration image, and determines a plurality of image coordinates for representing respective locations at which a plurality of pattern elements of a calibration pattern appear in a calibration image. The system determines, based on the plurality of image coordinates and defined pattern element coordinates, an estimate for a first lens distortion parameter of a set of lens distortion parameters, wherein the estimate for the first lens distortion parameter is determined while estimating a second lens distortion parameter of the set of lens distortion parameters to be zero, or is determined without estimating the second lens distortion parameter. The system determines, after the estimate of the first lens distortion parameter is determined, an estimate for the second lens distortion parameter based on the estimate for the first lens distortion parameter.