Stereo Calibration for Movable Vision Systems
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Solution Overview
Problem
Existing stereo calibration algorithms for movable multi-ocular vision systems fail to obtain real-time extrinsic parameters of cameras during operation, due to errors in mechanical machining and assembly, which affect the accuracy of depth information calculation.
Innovation Solution
A stereo calibration method that calculates relative positional relationships between imaging components using position recording components attached to rotation axes, allowing for real-time extrinsic parameter calculation based on sequences of captured images and movement information, incorporating a calibration template and processing algorithms to derive rotation and translation matrices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional stereo calibration algorithms are used for movable vision systems, then the system structure remains simple, but real-time extrinsic parameters cannot be obtained during camera movements
Solution Approach 1:
The patent applies preliminary action by pre-calibrating the vision system at a reference position to establish initial parameter relationships before movement occurs. The calibration template is positioned and captured in advance, creating a baseline from which all subsequent real-time calculations during movement are derived, enabling accurate extrinsic parameter computation without requiring complex real-time mechanical sensing.
Solution Approach 2:
The patent introduces a calibration template as an intermediary object that mediates between the camera system and the movement parameters. This template serves as a reference medium that can be captured by the moving camera, allowing the system to calculate extrinsic parameters through image processing rather than direct mechanical measurement, thus simplifying the overall system structure while maintaining precision.
2Manufacturing precision
If mechanical machining and assembly techniques are used to position cameras, then the system is easier to manufacture, but errors in relative positions between cameras and rotation axes occur
Solution Approach 1:
The patent replaces the mechanical positioning system with an optical-computational system. Instead of relying on precise mechanical machining to position cameras relative to rotation axes, the system uses image capture of a calibration template combined with computational algorithms to determine extrinsic parameters. This substitution eliminates the need for high-precision mechanical assembly while achieving comparable or superior positioning accuracy through software-based calibration.
Solution Approach 2:
The patent changes the approach from fixed mechanical parameters to dynamic computational parameters. Rather than attempting to maintain constant mechanical precision throughout manufacturing and assembly, the system allows parameters to be dynamically calculated and adjusted through image processing and mathematical transformations, accommodating variations in mechanical positioning while achieving accurate stereo vision.
3Adaptability or versatility
If multiple cameras move during operation, then the system gains versatility, but extrinsic parameters vary and require continuous recalibration
Solution Approach 1:
The patent applies dynamics by creating a calibration system that adapts to movement rather than resisting it. The method establishes parameter relationships at a reference position and then uses these relationships to continuously calculate updated extrinsic parameters as the camera moves. This dynamic approach allows the system to maintain measurement precision throughout the range of motion without requiring physical recalibration at each position, enabling both versatility and precision.
Data Source
AI summary
A stereo calibration method for a movable vision system. The movable vision system involved in the method comprises at least two photography components, at least one calculation component, and at least one control component. The method comprises: placing a calibration template in front of photography components; rotating the photography components by degrees of freedom of motion; obtaining one or more groups of images including calibration template features, and obtaining corresponding position information at the degrees of freedom of motion when the images are obtained; obtaining, by means of calculation, a calibration result of the photography components and the degrees of freedom of motion, i.e., a rotation matrix and a translation matrix of the rotation axis at the degrees of freedom of motion with respect to the photography components; and then obtaining in real time a stereo calibration result by combining the obtained calibration result and the position information at the degrees of freedom of motion in the vision system. The method implements stereo calibration of the photography components in a movable multiocular system in a motion state, has a good calculation real-time property, eliminates the error problem caused by machining or assembly, and has a broad application prospect.