Onboard Camera Extrinsic Parameter Correction via Lane Line Analysis
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Solution Overview
Problem
Common onboard cameras for Advanced Driver Assistance Systems (ADAS) fail to provide valid lane images for analysis and recognition due to displacement or environmental changes, leading to system failures.
Innovation Solution
An automatic correction method for onboard cameras that adjusts the extrinsic parameter matrix by identifying lane lines, converting images to top-view, and calculating correction matrices to correct the camera's parameters, ensuring accurate lane image analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If static adjustment method is used for onboard camera, then device complexity is reduced, but reliability deteriorates because the camera cannot adapt to displacement or environmental changes
Solution Approach 1:
The patent implements dynamic correction of the extrinsic parameter matrix by continuously detecting lane lines and calculating correction values based on current road conditions. The system transitions from static calibration to dynamic adaptation, allowing the camera to automatically adjust to displacement and environmental changes during vehicle operation.
Solution Approach 2:
The system performs self-correction by automatically detecting lane lines in captured images, calculating deviations from expected lane line positions, and adjusting the extrinsic parameter matrix without external intervention. This self-service mechanism enables the camera to autonomously maintain accurate lane detection despite environmental variations.
2Adaptability or versatility
If automatic correction is implemented, then adaptability is improved, but device complexity increases due to additional processing modules
Solution Approach 1:
The correction algorithm leverages the existing lane detection functionality to simultaneously perform both lane identification and camera calibration. The same image processing pipeline that detects lane lines for navigation also calculates correction parameters for the extrinsic matrix, making the system multi-functional without requiring separate dedicated hardware modules.
Solution Approach 2:
The system adapts to environmental changes by dynamically adjusting the extrinsic parameter matrix based on detected lane line positions. By changing the camera parameters in real-time according to actual road conditions, the system achieves high adaptability while using computational rather than hardware modifications.
3Measurement precision
If static calibration is used, then manufacturing precision is maintained, but measurement precision deteriorates under varying environmental conditions
Solution Approach 1:
The system performs preliminary correction by calculating the extrinsic parameter matrix adjustment based on detected lane lines before using the camera for navigation tasks. This preliminary calibration step ensures that measurements are performed with corrected parameters that account for current environmental conditions, thereby maintaining high measurement precision.
Data Source
AI summary
There is provided an automatic correction method for an onboard camera and an onboard camera device. The automatic correction method includes the following steps: obtaining a lane image with the onboard camera and a current extrinsic parameter matrix, and identifying two lane lines in the lane image; converting the lane image into a top-view lane image, and obtaining two projected lane lines in the top-view lane image for the two lane lines; calculating a plurality of correction parameter matrices corresponding to the current extrinsic parameter matrix according to the two projected lane lines; and correcting the current extrinsic parameter matrix according to the plurality of correction parameter matrices. This can be applied in situations where the vehicle is stationary or travelling for automatic correction on the extrinsic parameter matrix of the onboard camera.