Multi-Camera Vehicle Calibration Through Pixel Coordinate Warping
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Solution Overview
Problem
Existing autonomous vehicles face challenges in calibrating images from multiple cameras located at different positions on the vehicle to align them in the same real-world coordinates due to varying perspectives and obstacles, making it difficult to estimate the relationship between these cameras effectively.
Innovation Solution
A device and method that utilize a processor to extract specific regions of interest from multiple camera images, project pixel coordinates using a warping function, and adjust camera parameters to minimize differences between these coordinates, ensuring alignment in real-world coordinates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If images are acquired from multiple cameras at different positions, then the coverage area increases, but the coordinate alignment difficulty increases
Solution Approach 1:
The patent introduces a processor as an intermediary that performs coordinate transformation and calibration operations. The processor converts pixel coordinates from different camera perspectives into a unified real-world coordinate system, mediating between the multiple camera inputs and the final aligned output, thereby resolving the coordinate alignment difficulty while maintaining multi-camera coverage
Solution Approach 2:
The patent changes the parameter representation by transforming pixel coordinates into real-world coordinates through calibration parameters. By adjusting and optimizing calibration parameters (such as camera intrinsic parameters, extrinsic parameters, and transformation matrices), the system achieves coordinate alignment across multiple cameras, converting the alignment problem into a parameter optimization problem
2Area of stationary object
If cameras are positioned at different locations, then the field of view expands, but the image calibration difficulty increases
Solution Approach 1:
The patent implements a feedback mechanism where the processor continuously optimizes calibration parameters by comparing transformed coordinates from different cameras and minimizing the differences. This iterative feedback process adjusts calibration parameters until the coordinate alignment reaches optimal precision, thereby achieving accurate image calibration across the expanded field of view
3Quantity of substance
If multiple cameras are used, then the data completeness improves, but the processing complexity increases
Solution Approach 1:
The patent segments the processing task by first extracting regions of interest from each camera image independently, then performing coordinate transformation on these segmented regions. This segmentation approach breaks down the complex processing of multiple full images into manageable parts, reducing overall processing complexity while maintaining data completeness from all cameras
Data Source
AI summary
A device for calibrating a camera of a vehicle includes: a first camera for acquiring a first image, a second camera for acquiring a second image, and a processor that extracts a first class of interest from the first image, and extracts a second class of interest from the second image. The processor projects pixel coordinates of the first class of interest onto the second image to convert the pixel coordinates, and corrects parameters of the second camera such that a difference between the converted pixel coordinates of the first class of interest and pixel coordinates of the second class of interest is minimized.