Vehicle Camera Calibration Using Rigid Mounting and Motion Cues
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Solution Overview
Problem
Existing camera calibration methods for vehicles are complex and difficult to implement in the field due to equipment and computing complexity, requiring controlled environments and multiple calibration techniques that are hard to combine effectively.
Innovation Solution
A hybrid approach using a mounting device to provide a rigid geometric calibration, combined with simplified software calibration based on vehicle motion and environmental assumptions, reduces complexity by fixing the camera's orientation relative to the vehicle and using transformations to adjust camera parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional camera calibration methods are used, then calibration accuracy can be achieved, but the process becomes complex and difficult to implement in the field
Solution Approach 1:
The calibration process is segmented into two distinct phases: (1) geometric calibration using a rigid mounting device to establish fixed transformation parameters between camera and vehicle coordinate systems, and (2) simplified software-based calibration using environmental features and vehicle motion data. This segmentation reduces overall complexity by separating hardware setup from software processing.
Solution Approach 2:
The rigid mounting device performs preliminary geometric calibration before the vehicle operates, pre-establishing transformation parameters (rotation and translation) between camera and vehicle coordinate systems. This preliminary action eliminates the need for complex real-time calibration during field operations, reducing on-site complexity while maintaining accuracy.
2Measurement precision
If multiple calibration techniques are combined, then calibration accuracy improves, but implementation difficulty increases
Solution Approach 1:
The patent merges geometric calibration (through rigid mounting) with feature-based calibration (using environmental features like lane markings) into a unified approach. The rigid mounting provides transformation parameters that are then refined using visual features captured by the camera, combining both methods seamlessly without requiring separate complex procedures.
Solution Approach 2:
The calibration system uses the vehicle's own motion data (from IMU and GPS) and captured images to automatically perform calibration adjustments. The system self-calibrates by detecting environmental features and comparing them with expected positions based on vehicle motion, eliminating the need for external calibration equipment or complex manual procedures.
3Measurement precision
If controlled environment calibration is used, then calibration accuracy is maintained, but field deployment flexibility is reduced
Solution Approach 1:
The patent replaces mechanical/physical calibration equipment (such as calibration targets and controlled environment setups) with a software-based system that uses environmental features and vehicle motion data. This substitution allows calibration to be performed in any field condition without requiring controlled environments or specialized hardware.
Solution Approach 2:
The calibration approach changes from fixed parameter calibration (performed in controlled environments) to dynamic parameter adjustment (performed in the field using vehicle motion and environmental features). The system adapts calibration parameters based on real-time conditions, maintaining accuracy while enabling flexible field deployment.
Data Source
AI summary
System and techniques for determining calibration parameters for a camera mounted to a vehicle are described herein. The system obtains images at multiple points in time that contain the same feature. The feature is simulated in a second image based on a representation of the feature in a first image. The difference between the simulated feature and a representation of the feature in the second image is iteratively minimized by adjusting the available calibration parameters.