Vehicle Camera Self-Calibration Using Lane Line Geometry
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Calibration of vehicle-mounted cameras for vehicle event recorders is difficult, error-prone, and cumbersome, leading to inaccurate sensor location measurements and subsequent errors in advanced driver assistance systems (ADAS) determinations.
Innovation Solution
A system that automatically calculates the height and offset of vehicle-mounted cameras using image analysis and machine learning to identify lane lines, eliminating the need for manual calibration and improving installation efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual calibration is used to determine camera location, then measurement precision can be achieved, but device complexity and ease of operation deteriorate due to the difficult and error-prone calibration process
Solution Approach 1:
The system performs self-calibration by automatically determining camera height and offset using image processing of lane markings. The calibration process serves itself by utilizing the camera's own captured images to compute its location parameters, eliminating the need for external calibration equipment or manual procedures.
Solution Approach 2:
The patent replaces manual mechanical calibration procedures with an automated computational system. Instead of physically measuring and adjusting camera positions, the system uses image processing algorithms to automatically calculate camera location parameters from captured lane marking patterns.
2Measurement precision
If manual calibration is used to determine camera location, then measurement precision can be achieved, but productivity deteriorates due to the time-consuming calibration process
Solution Approach 1:
The system performs calibration automatically as part of the normal operation process rather than as a separate preliminary step. By continuously capturing images and computing camera parameters during regular vehicle operation, the system eliminates the need for dedicated calibration time during installation and deployment.
Solution Approach 2:
The calibration process is made continuous and ongoing rather than a one-time manual procedure. The system continuously captures images, processes lane markings, and refines camera location parameters throughout vehicle operation, ensuring accurate measurements without interrupting productivity.
3Ease of operation
If automated calculation is used to determine camera height and offset, then ease of operation and productivity improve, but measurement precision may deteriorate without proper calibration
Solution Approach 1:
The system uses feedback from captured images to continuously refine camera location measurements. By processing lane marking patterns from the camera's own views and comparing against known road geometry, the system achieves high measurement precision through iterative automated calculation rather than manual calibration.
Solution Approach 2:
The automated calculation system serves multiple functions: it determines camera height, offset, and orientation simultaneously while also providing lane detection and road geometry information. This multi-functionality maintains measurement precision across various operating conditions without requiring separate calibration procedures.
Data Source
AI summary
A system for calculating height and offset of a vehicle-mounted camera includes an interface and a processor. The interface is configured to receive image data from a camera mounted on a vehicle. The processor is configured to determine a set of lane lines using the image, determine points for calculating height and offset of the camera using a pair of lane lines, and calculate the height and the offset of the camera using the points.