Surround View Camera Calibration Using Chart Feature Detection
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Solution Overview
Problem
Automotive surround view camera systems require accurate calibration to integrate images from multiple cameras correctly, without which the integrated images may be inaccurate.
Innovation Solution
An automatic method for generating calibration parameters involves capturing video streams from each camera, displaying them with overlaid bounding boxes and detected feature points, and computing calibration parameters based on these features and platform-dependent parameters.
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 calibration process is time-consuming and complex
Solution Approach 1:
The system performs automatic self-calibration by capturing images of calibration charts, detecting feature points automatically, and computing calibration parameters without requiring manual intervention. The camera system calibrates itself through the processor analyzing the captured images and generating calibration data autonomously.
Solution Approach 2:
The patent replaces manual mechanical calibration procedures with an automated computer vision-based system. Instead of manual adjustment and measurement, the system uses image capture, feature point detection algorithms, and automated computation to determine calibration parameters, substituting mechanical/manual processes with electronic and software-based solutions.
2Productivity
If automatic calibration is implemented, then calibration time is reduced, but the complexity of the calibration system increases
Solution Approach 1:
The processor performs multiple functions including image capture coordination, feature point detection, calibration parameter computation, and validation. The calibration chart serves multiple purposes as both a reference object and a source of feature points. This multi-functionality reduces the need for separate dedicated components, managing system complexity while maintaining automation.
Solution Approach 2:
The calibration chart acts as an intermediary object that facilitates the automatic calibration process. It provides known geometric features that the system can detect and use to compute calibration parameters, serving as a mediator between the camera system and the calibration algorithm without requiring complex direct measurement mechanisms.
3Measurement precision
If calibration charts are used for automatic calibration, then calibration accuracy is improved, but the calibration process requires additional setup and equipment
Solution Approach 1:
The system uses a calibration chart with known geometric patterns that can be captured as an image copy. The feature points on the chart represent known reference positions that are copied into the digital image domain, where they can be detected and used for calibration without requiring physical measurement tools or complex setup procedures.
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.