Multi-Camera Housing Calibration Using a Reference Vehicle Camera
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Calibration of multiple vehicle cameras in a housing is time-consuming and costly, leading to inaccurate or misleading image information, which compromises vehicle safety.
Innovation Solution
A vehicle imaging system uses first calibration information from a calibrated camera to generate second calibration information for an uncalibrated camera, combining this with translation information to adjust the position and orientation differences between the cameras, thereby improving image accuracy without additional calibration processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional calibration processes are performed on each camera individually, then calibration accuracy is ensured, but calibration time and cost increase significantly
Solution Approach 1:
The calibration process is segmented into two parts: (1) perform full calibration on a reference camera, and (2) use the reference calibration data combined with relative position information to compute calibration parameters for other cameras. This segmentation allows one camera to be fully calibrated while others use relative calibration, reducing overall calibration time and cost while maintaining sufficient accuracy.
Solution Approach 2:
The calibration parameters obtained from the reference camera are copied and adapted for other cameras in the housing. By using the reference camera's calibration data as a base and adjusting it according to relative position and orientation information, the system avoids performing identical calibration procedures on each camera, thereby reducing time and expense.
2Measurement precision
If traditional calibration processes are performed on each camera individually, then calibration accuracy is ensured, but manufacturing cost increases
Solution Approach 1:
The calibration workload is segmented so that only one reference camera requires full calibration procedures. Other cameras use a simplified calibration approach based on the reference camera's data and relative positioning information, reducing the overall manufacturing cost while maintaining acceptable calibration accuracy.
Solution Approach 2:
The reference camera's calibration data serves a universal purpose for all cameras in the housing. By using the same reference calibration data combined with relative position information to calibrate multiple cameras, the system reduces the number of separate calibration processes needed, thereby lowering manufacturing costs.
3Productivity
If cameras are mounted in a common housing, then installation efficiency is improved, but manufacturing non-uniformities cause image information inaccuracy
Solution Approach 1:
The system replaces mechanical precision requirements with computational correction. Instead of requiring mechanically precise mounting of each camera in the housing, the system uses computational methods to calculate and apply calibration parameters that compensate for manufacturing non-uniformities and positioning variations, thereby maintaining image accuracy despite variability in physical mounting.
Solution Approach 2:
The system changes from fixed mechanical positioning parameters to adjustable calibration parameters. By allowing calibration parameters to be computed and adjusted based on actual camera positions and the reference camera's data, the system compensates for manufacturing non-uniformities and mounting variations, maintaining image information accuracy despite physical imperfections.
Data Source
AI summary
A vehicle includes an imaging system including a first camera and a second camera in a housing mounted to the vehicle, and a processing circuit that uses a first calibration information obtained from a calibration of the first camera to generate a second calibration information to calibrate the second camera. The first calibration information identifies a first position difference between a position of the first camera and a reference position, and also identifies a first orientation difference between an orientation of the first camera and a reference orientation. The second calibration information includes a second position difference between the second camera and the reference position, and a second orientation difference between the second camera and the reference orientation. Generating the second calibration information includes combining the first calibration information with translation information providing a position difference and an orientation difference between the first camera and the second camera.


