Onboard Camera Automatic Calibration for Mounting Angle Drift
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Solution Overview
Problem
Existing onboard camera calibration methods using pre-installed calibration targets on the road surface are insufficient as they do not account for changes in the vehicle's mounting angle due to factors like passenger load or aging, leading to inaccurate calibration during vehicle operation.
Innovation Solution
An onboard camera automatic calibration apparatus that includes a camera, motion vector calculation unit, road surface point selection unit, and coordinate rotation correction unit, which determines and corrects the camera's mounting angle relative to the road surface in real-time using images captured by the camera, performing rotation corrections around the X, Y, and Z axes to ensure accurate alignment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If calibration is performed using a calibration target installed on the road surface in advance, then the calibration process is simple and quick, but the calibration accuracy deteriorates because the vehicle state at calibration time does not correspond to the actual state during vehicle operation
Solution Approach 1:
The system uses the vehicle's own camera and existing sensors (accelerometer, gyroscope) to perform self-calibration without requiring external calibration targets or manual intervention. The camera captures images of the road surface while the vehicle is in its actual operating state, and the system automatically calculates and corrects the mounting angle based on the captured image data and vehicle state information.
Solution Approach 2:
The system dynamically adjusts the calibration parameters based on real-time vehicle state changes. Instead of using fixed calibration targets, the system continuously monitors and adapts to changes in vehicle acceleration, orientation, and camera position, updating the mounting angle parameters to reflect the actual vehicle state during operation.
2Ease of manufacture
If calibration is performed using a calibration target, then the calibration process is straightforward, but the calibration becomes insufficient for mounting angle changes due to passenger load fluctuations and vehicle aging
Solution Approach 1:
The system continuously monitors the vehicle's actual state using sensors and camera feedback, comparing the current state with the calibrated state. When deviations are detected due to passenger load changes or aging, the system automatically adjusts the mounting angle parameters to maintain accurate calibration, ensuring the system adapts to changing vehicle conditions over time.
Solution Approach 2:
The calibration system transitions from a static, one-time calibration process to a dynamic, continuous calibration process. The system continuously updates the mounting angle parameters based on real-time vehicle state data, allowing the calibration to adapt to dynamic changes in vehicle conditions such as passenger load and aging effects.
3Measurement precision
If manual recalibration is performed to account for vehicle state changes, then the calibration accuracy can be maintained, but the operational complexity and time consumption increase
Solution Approach 1:
The system automatically performs calibration without requiring manual intervention. The camera captures images of the road surface, the processor analyzes the image data combined with sensor information, and the system self-corrects the mounting angle parameters, eliminating the need for manual recalibration operations while maintaining high calibration accuracy.
Solution Approach 2:
The system replaces manual mechanical calibration procedures with automated computational processing. Instead of physically adjusting the camera or using manual measurement tools, the system uses image processing algorithms and sensor data fusion to automatically calculate and correct mounting angle parameters, reducing operational complexity and time consumption.
Data Source
AI summary
According to one embodiment, an onboard camera automatic calibration apparatus includes at least a road surface point selection unit, an amount-of-rotation-around-Z-axis calculation unit and a coordinate rotation correction unit. The road surface point selection unit selects multiple points not less than three on a road surface in a predetermined image among the multiple images obtained by an onboard camera and selects multiple combinations of two points from among the multiple points. The amount-of-rotation-around-Z-axis calculation unit determines, in a camera coordinate system with an optical axis as a Z axis, an amount of rotation around the Z axis such that the road surface is parallel to an X axis, based on the multiple combinations and motion vectors. The coordinate rotation correction unit performs rotation correction around the Z axis for the images obtained by the onboard camera based on the determined amount of rotation around the Z axis.