Surround View Camera Calibration with Platform-Specific Chart Alignment
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Solution Overview
Problem
Automotive surround view camera systems require accurate calibration to integrate images from multiple cameras effectively, without which the integrated images may be inaccurate, posing challenges in autonomous driving and parking applications.
Innovation Solution
An automatic calibration method for surround view camera systems that captures video streams from multiple cameras, overlays bounding boxes on calibration charts, detects feature points, computes calibration parameters based on these points and platform-dependent parameters, and stores them for precise geometric alignment and distortion correction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual calibration methods are used for surround view camera systems, then calibration accuracy can be achieved, but the process requires specialized skills and is time-consuming
Solution Approach 1:
The system performs automatic calibration by capturing images of calibration charts, detecting feature points, and computing calibration parameters without requiring technician intervention or specialized skills. The calibration process serves itself by using the camera system's own imaging capabilities to determine its geometric parameters.
Solution Approach 2:
The patent replaces manual mechanical adjustment and visual inspection methods with automated image processing and computer vision algorithms. The system uses software-based feature point detection and parameter computation to substitute for manual calibration procedures.
2Reliability
If manual calibration methods are used for surround view camera systems, then calibration can be performed, but the process is time-consuming
Solution Approach 1:
The system uses pre-designed calibration charts with known geometric patterns and pre-defined feature points to streamline the calibration process. The bounding boxes are pre-positioned based on platform-dependent parameters, allowing the system to quickly locate and process calibration features without manual searching or adjustment.
Solution Approach 2:
The patent automatically computes calibration parameters (geometric transformation matrices, distortion coefficients) based on detected feature points and platform-dependent parameters. The system changes from fixed manual parameter setting to dynamic parameter computation based on actual camera observations.
3Adaptability or versatility
If generic calibration software is used across multiple platforms, then software versatility is improved, but platform-specific calibration requirements may not be met
Solution Approach 1:
The patent implements a universal calibration software platform that can be used across multiple vehicle platforms. The system achieves this by separating platform-specific parameters (bounding box positions, calibration chart dimensions) from the core calibration algorithm, allowing the same software to adapt to different platforms through parameter configuration rather than code modification.
Solution Approach 2:
The system maintains versatility across platforms by changing only the platform-dependent parameters (bounding box coordinates, calibration chart size and position) while keeping the core calibration processing logic identical. This allows generic software to meet platform-specific requirements through parameter adaptation.
Data Source
AI summary
A method for automatic generation of calibration parameters for a surround view (SV) camera system is provided that includes capturing a video stream from each camera comprised in the SV camera system, wherein each video stream captures two calibration charts in a field of view of the camera generating the video stream; displaying the video streams in a calibration screen on a display device coupled to the SV camera system, wherein a bounding box is overlaid on each calibration chart, detecting feature points of the calibration charts, displaying the video streams in the calibration screen with the bounding box overlaid on each calibration chart and detected features points overlaid on respective calibration charts, computing calibration parameters based on the feature points and platform dependent parameters comprising data regarding size and placement of the calibration charts, and storing the calibration parameters in the SV camera system.