Around View Monitoring System Road Gradient Compensation
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Solution Overview
Problem
Existing around view monitoring systems (AVMS) face reliability and stability issues due to changes in camera tolerances caused by environmental factors like vehicle vibration and mirror adjustments, leading to distorted images and decreased accuracy in camera attitude estimation, especially when road gradients are present.
Innovation Solution
An AVMS that includes an image capture unit, a feature point extraction unit, a camera attitude estimation unit, and an around view generation unit, which extracts ground feature points, estimates rotation angles, and generates a rotation matrix to account for road gradients, allowing for the removal of gradient components and the creation of a synthesis lookup table (LUT) to correct image matching.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If camera tolerances are corrected during vehicle assembly, then image matching accuracy is improved, but the corrected tolerances change due to environmental factors such as vibration, mirror folding, and door opening/closing
Solution Approach 1:
The system performs preliminary detection of road gradients and pre-calculates compensation values before image synthesis. By detecting the gradient in advance and preparing correction data, the system can quickly compensate for tolerance changes without requiring real-time complex calculations, thus maintaining image matching accuracy despite environmental variations.
Solution Approach 2:
The system dynamically changes the rotation matrix parameters based on detected road gradients. Instead of using fixed tolerance corrections, the system adjusts rotation angles and transformation parameters in real-time according to the actual road conditions, allowing the image processing to adapt to environmental changes and maintain accuracy.
2Device complexity
If standard camera attitude estimation is used, then processing simplicity is maintained, but accuracy of camera attitude estimation decreases when road gradients are present
Solution Approach 1:
The attitude estimation process is segmented into two independent parts: road gradient detection and camera attitude estimation. The gradient detection module first identifies road inclination, and then this information is used to correct the attitude estimation. This segmentation allows each module to focus on its specific task, improving overall accuracy without significantly increasing complexity.
Solution Approach 2:
The road gradient detection result serves as an intermediary variable that mediates between the raw image data and the final attitude estimation. By introducing this intermediate step, the system can account for road gradients without completely redesigning the attitude estimation algorithm, thus improving accuracy while maintaining reasonable complexity.
3Measurement precision
If tolerance correction is performed at service centers, then image matching is improved, but the process becomes cumbersome and time-consuming
Solution Approach 1:
The system enables self-service tolerance correction by automatically detecting road gradients and calculating compensation values during normal operation. Instead of requiring visits to service centers, the vehicle's AVMS performs self-diagnosis and self-correction, eliminating the need for professional intervention and significantly reducing the time and effort required for maintenance.
Solution Approach 2:
The system implements continuous feedback by monitoring image matching quality and automatically adjusting tolerance parameters based on detected deviations. This closed-loop control allows the system to maintain accurate image matching over time without external intervention, effectively replacing periodic service center visits with continuous automatic correction.
Data Source
AI summary
The present invention is directed to providing an around view monitoring system (AVMS) that may enhance accuracy of an estimation of a camera attitude while a road gradient is present, and an operating method thereof. According to an embodiment of the present invention, the AVMS may calculate a rotation matrix for removing a road gradient component using a camera that has not changed position and generate an estimated rotation matrix from which the road gradient is removed by applying the rotation matrix to an estimated rotation matrix for a camera that has changed position.