Vehicular Vision System Camera Calibration via Euler Angle Estimation
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Solution Overview
Problem
Existing vehicle vision systems face limitations in accurately aligning optical overlays with real-world views captured by cameras, particularly rear cameras, due to dynamic steering wheel parameters, which affect the accuracy and resolution of output images.
Innovation Solution
A vehicle vision system that uses one or more CMOS cameras to capture exterior images, with a companion chip processing image data to estimate camera Euler angles (pitch, yaw, roll) on-the-fly, allowing for calibration of graphic overlays to match the real viewing angle without pre-rendered data sets or specially designed visual patterns, ensuring accurate alignment and matching of overlays with real-world views.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If dynamic steering wheel parameters are used for overlay generation, then the system can adapt to different steering positions, but the accuracy and resolution of output images deteriorate
Solution Approach 1:
The system performs preliminary calibration by capturing images at multiple known steering wheel positions and pre-calculating the transformation parameters (rotation angles, translation vectors) for each position. This pre-computation stores the relationship between steering positions and required overlay transformations, allowing the system to quickly retrieve and apply the correct transformation without real-time dynamic calculation, thus maintaining both adaptability and precision.
2Speed
If pre-rendered graphics are recalled for overlays, then real-time processing is enabled, but the data set expands when overlays need to be adapted to calibration parameters
Solution Approach 1:
The system generates a single universal set of overlay graphics that can be applied to any steering wheel position. Instead of creating separate pre-rendered datasets for each calibration parameter configuration, the system uses transformation matrices (rotation and translation) to adapt one universal overlay set to match any camera orientation. This mathematical transformation approach allows the same overlay data to serve multiple purposes across different mounting situations, reducing the overall data set size while maintaining real-time adaptability.
3Manufacturing precision
If overlays are calculated for different mounting situations, then alignment accuracy is improved, but the complexity of the system increases
Solution Approach 1:
The system handles different mounting situations by changing transformation parameters (rotation angles, translation offsets, scaling factors) rather than creating fundamentally different overlay sets. The calibration process determines the specific parameter values for each camera mounting position, and these parameters are stored in a lookup table or configuration file. This approach allows the system to adapt to various mounting situations using a unified mathematical framework, avoiding the complexity of multiple specialized overlay generation algorithms while maintaining high alignment accuracy.
Data Source
AI summary
A method for calibrating a vehicular vision system includes disposing a camera at a vehicle, disposing a processor at the vehicle, and disposing a video display screen in the vehicle so as to be viewable by the vehicle driver. The video display screen is operable to display video images derived from image data captured by the imager of the camera. Image data is captured by the imager of the camera and provided to the processor. The video display screen displays video images derived from image data captured by the imager of the camera. The processor generates a graphic overlay for display with the video images at the video display screen. Responsive to processing captured image data, the vehicular vision system is calibrated by adapting an orientation and position of the image data relative to the generated graphic overlay to a corrected orientation and position relative to the generated graphic overlay.