Trailer Camera Extrinsic Calibration Using 3D Feature Mapping
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Solution Overview
Problem
Existing vehicle-trailer systems lack an efficient method for automatically calibrating aftermarket trailer cameras, which is essential for vehicle-trailer applications that rely on accurate camera calibration parameters.
Innovation Solution
A method and system for automatically calibrating extrinsic parameters of a trailer camera by determining a three-dimensional feature map from vehicle images, identifying reference points, detecting these points in trailer images, and calculating the trailer camera's location and extrinsic parameters relative to a trailer reference point.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual calibration methods are used for trailer cameras, then calibration accuracy can be achieved, but the complexity of operation and time consumption increase significantly
Solution Approach 1:
The system performs automatic self-calibration by capturing images from multiple cameras, extracting features automatically, and computing extrinsic parameters without human intervention. The calibration process serves itself by using the camera system to calibrate itself through automated feature detection and geometric computation.
Solution Approach 2:
The system performs preliminary actions by capturing a series of images during a calibration drive before the actual calibration computation. These pre-captured images contain the necessary feature points that will be used for subsequent automatic calibration, preparing the data in advance for processing.
2Ease of operation
If automatic calibration is implemented, then ease of operation improves, but the reliability and precision of calibration may deteriorate
Solution Approach 1:
The system uses feedback by comparing feature points detected across multiple images and iteratively refining the calibration parameters. The extrinsic parameters are computed based on feedback from the geometric relationships observed in the captured images, ensuring accurate automatic calibration.
Solution Approach 2:
The system transitions from two-dimensional image data to three-dimensional spatial understanding by computing extrinsic parameters that describe the 3D positions and orientations of cameras. This dimensional transformation enables precise automatic calibration by leveraging spatial geometric relationships.
3Measurement precision
If multiple cameras are used for calibration, then measurement precision improves, but device complexity increases
Solution Approach 1:
The calibration system is designed with multi-functionality to handle multiple cameras simultaneously using a unified calibration process. The same feature extraction and parameter computation methods are applied universally across all cameras, reducing the need for separate calibration procedures for each camera.
Data Source
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AI summary
A method for calibrating extrinsic parameters (182) of a trailer camera (132d, 132e, 132f) supported by a trailer (106) attached to a tow vehicle (102). The method includes determining a three-dimensional feature map (162) from one or more vehicle images (133) received from a camera (132a, 132b, 132c) supported by the tow vehicle and identifying reference points (163) within the three-dimensional feature map. The method includes detecting the reference points within one or more trailer images received from the trailer camera after the vehicle and the trailer moved a predefined distance in the forward direction. The method also includes determining a trailer camera location (172) of the trailer camera (132d, 132e, 132f) relative to the three-dimensional feature map (162) and determining a trailer reference point (184) based on the trailer camera location. The method also includes determining extrinsic parameters (182) of the trailer camera relative to the trailer reference point.