Fisheye Camera Calibration for Simulated Bird's-Eye-View Imaging
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Solution Overview
Problem
Current methods lack the capability to calibrate fisheye cameras in simulation environments to generate undistorted and bird's-eye-view images, hindering efficient camera testing and validation, which are typically manual and time-consuming in real-world settings.
Innovation Solution
The system and method for fisheye camera calibration in a simulation environment allow for the computation of extrinsic and intrinsic parameters, enabling the generation of undistorted and bird's-eye-view images by using a simulated camera system with AI-driven iterative calibration, allowing for automated image processing and manipulation of virtual environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual calibration process is used in real world, then camera testing and validation can be performed, but the process is time-consuming and labor-intensive
Solution Approach 1:
The patent creates a virtual copy of the fisheye camera and calibration target within a simulation environment. This virtual replica allows calibration procedures to be performed digitally, eliminating the need for physical manual calibration while preserving the essential calibration relationships and geometric transformations needed for valid camera testing and validation.
Solution Approach 2:
The patent replaces the mechanical manual calibration process with an automated computational system. The simulation environment uses software-based coordinate mapping and image processing algorithms to perform calibration automatically, substituting human-operated mechanical procedures with automated digital processes that are both faster and more consistent.
2Loss of information
If virtual fisheye camera is created in simulation environment, then data availability and collection is improved, but there are no means to calibrate the camera for generating undistorted and BEV images
Solution Approach 1:
The patent performs preliminary calibration actions within the simulation environment by establishing the relationship between virtual world coordinates and simulated camera image coordinates before actual testing begins. This pre-calibration process creates the necessary transformation matrices and distortion parameters that enable subsequent generation of undistorted images and bird's-eye-view images without requiring real-world calibration equipment.
Solution Approach 2:
The patent creates a universal calibration framework that works within the simulation environment using the same fundamental calibration principles as real-world cameras. The simulated camera system can generate undistorted images, bird's-eye-view images, and perform testing and validation, making the simulation environment multi-functional and eliminating the need for separate real-world calibration procedures.
3Measurement precision
If manual calibration process is used, then camera parameters can be obtained, but the process requires manual movement and imaging of target objects
Solution Approach 1:
The patent implements self-service calibration where the simulation environment automatically performs all calibration operations without human intervention. The system autonomously captures virtual images of calibration targets at multiple positions, computes coordinate transformations, and determines camera parameters through automated image processing and mathematical calculations, making the entire calibration process self-sufficient and fully automated.
Solution Approach 2:
The patent incorporates feedback mechanisms where the simulation system continuously monitors and adjusts calibration parameters based on computed results. The automated process uses feedback from coordinate mapping errors and image distortion measurements to refine calibration parameters iteratively, ensuring measurement precision while maintaining full automation throughout the calibration procedure.
Data Source
AI summary
Systems and methods for fisheye camera calibration and BEV image generation in a simulation environment. This fisheye camera calibration enables the extrinsic and intrinsic parameters of the fisheye camera to be computed in the simulation environment, where data is readily available, collectible, and manipulatable. Given a surround vision system, with multiple fisheye cameras disposed around a vehicle, and these extrinsic and intrinsic parameters, undistorted and BEV images of the surroundings of the vehicle can be generated in the simulated environment, for simulated fisheye camera testing and validation, which may then be extrapolated to real-world fisheye camera testing and validation, as appropriate. Because the simulation tool can be used to create and readily manipulate the simulated fisheye camera, the vehicle, its surroundings, obstacles, targets, markers, and the like, the entire calibration and image generation process is streamlined and may be automated.