Vehicle Hinge Point Calibration via Image Stitching
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Solution Overview
Problem
Existing methods for obtaining a panoramic view of a vehicle's motion state, particularly for vehicles with articulated parts, suffer from low accuracy, complex operations, and poor adaptability.
Innovation Solution
A method for vehicle hinge point calibration that involves acquiring raw images of a vehicle's external environment, adjusting and stitching these images to obtain independent surround-view images, and calculating the rotation angle and translation vector between vehicle parts to determine the coordinates of their hinge points.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If physical measurement methods are used to obtain panoramic view of vehicle motion state, then the measurement can be obtained, but the accuracy is low, operations are complicated and adaptability is poor
Solution Approach 1:
The patent replaces physical measurement methods (mechanical systems) with image processing and computer vision algorithms. By using images captured by vehicle-mounted cameras and processing them through feature point detection, rotation angle calculation, and coordinate transformation, the system obtains hinge point calibration data without requiring physical measurement equipment, thereby improving accuracy while reducing operational complexity
Solution Approach 2:
The patent creates a virtual model of the vehicle's spatial configuration by copying and processing image data. Instead of directly measuring physical dimensions, the system captures images of the vehicle and surrounding environment, extracts feature points, and reconstructs the hinge point coordinates through computational geometry, replacing physical measurement with a digital copy-based approach
2Adaptability or versatility
If physical measurement methods are used to obtain panoramic view of vehicle motion state, then the measurement can be obtained, but the adaptability is poor
Solution Approach 1:
The patent develops a universal image processing method that can be applied to various vehicle types with different hinged structures. The system uses general-purpose feature point detection and coordinate transformation algorithms that work across different vehicle configurations, making the method highly adaptable while maintaining accuracy through consistent mathematical principles
Solution Approach 2:
The patent employs dynamic image processing that adapts to different vehicle motion states. By capturing images at various angles and positions and processing them through flexible coordinate transformation, the system maintains high accuracy across different operational conditions and vehicle configurations, demonstrating dynamic adaptability
3Measurement precision
If feature points are detected and matched in multiple pairs of images to calculate rotation angles, then the calibration accuracy is improved, but the calculation complexity increases
Solution Approach 1:
The patent segments the image processing task into distinct stages: feature point detection, feature point matching, rotation angle calculation, and coordinate transformation. By dividing the complex calculation process into manageable segments, the system improves accuracy through systematic processing while reducing overall complexity through modular computation
Solution Approach 2:
The patent performs preliminary feature point detection and matching before calculating rotation angles. By pre-processing the images to identify and match feature points, the system prepares the necessary data for accurate rotation angle calculation, improving precision while organizing the computational workload in advance to manage complexity
Data Source
AI summary
The present application relates to a method for vehicle hinge point calibration, comprising: acquiring a raw image of a first portion and a second portion hinged to one another of a vehicle; adjusting, stitching and cropping the raw image to obtain respective independent surround-view images of the first portion and the second portion; and at least on the basis of the independent surround-view images of the first portion and the second portion, calculating the angle of rotation and the corresponding translation vector between the first and second portions, and thus calculating the coordinates of the respective hinge points of the first and second portions. Further comprised in the present application are an apparatus for vehicle hinge point calibration, a computer device, and a computer-readable storage medium.