Trailer Camera Self-Calibration for Targetless Misalignment Detection
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Solution Overview
Problem
Existing vehicle trailering systems lack an efficient method for calibrating cameras on a trailer without the use of targets, which affects the accuracy of image processing and object detection during maneuvers.
Innovation Solution
A vehicle trailering assist system that utilizes one or more CMOS cameras and an electronic control unit (ECU) to capture and process image data, estimating camera orientation and location parameters based on ground feature coordinates and intrinsic camera parameters, allowing for targetless calibration and accurate image processing during vehicle and trailer maneuvers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If targetless calibration method is used, then calibration complexity is reduced, but measurement precision may be affected
Solution Approach 1:
The system performs self-calibration by automatically detecting ground features and computing camera parameters without requiring external targets or manual intervention. The ECU autonomously processes image data from multiple frames to determine image coordinates of ground features and estimates camera orientation parameters, enabling the system to calibrate itself during normal operation.
Solution Approach 2:
The calibration method changes from target-based fixed parameters to targetless dynamic parameters by using ground features that can be detected in the environment. The system computes camera location and orientation parameters by analyzing the geometric relationships between detected ground features across multiple image frames, adapting to varying environmental conditions.
2Measurement precision
If multiple frames of image data are processed, then measurement precision improves, but loss of time increases
Solution Approach 1:
The system performs preliminary calibration during the first stage of a calibration maneuver by processing multiple frames to establish initial camera orientation parameters. These pre-computed parameters are then used during the second stage to quickly determine camera location, reducing the time required for full calibration while maintaining precision through the initial multi-frame analysis.
Solution Approach 2:
The calibration process is divided into two distinct stages: the first stage processes multiple frames to determine image coordinates and estimate orientation parameters, while the second stage uses these pre-computed parameters to determine camera location. This segmentation allows the computationally intensive multi-frame processing to be performed once, with faster subsequent calibration operations.
3Adaptability or versatility
If camera orientation parameters are estimated during maneuver, then adaptability improves, but reliability may be affected by motion
Solution Approach 1:
The calibration system is designed to operate dynamically during vehicle and trailer maneuvers rather than requiring static conditions. The ECU processes image data while the vehicle is in motion, estimating camera orientation parameters based on ground features detected during the calibration maneuver, enabling calibration under real operating conditions.
Solution Approach 2:
The system uses feedback from multiple image frames captured during the maneuver to continuously refine the estimation of ground feature coordinates and camera parameters. By analyzing the consistency of ground feature detection across multiple frames and using the computed parameters to verify camera location, the system ensures reliable calibration despite motion-induced variations.
Data Source
AI summary
A vehicular trailering assist system includes at least one camera disposed at a trailer hitched to a hitch of a vehicle, and an electronic control unit (ECU). The ECU determines, during a first stage of a calibration maneuver of the vehicle and trailer, image coordinates of at least one ground feature point. The ECU, responsive to determining image coordinates of the at least one ground feature point, estimates orientation parameters of the camera based at least on the determined image coordinates and intrinsic camera parameters. As the vehicle and trailer travel further along the ground surface during a second stage of the calibration maneuver of the vehicle and trailer, and based on the estimated orientation parameters of the at least one camera, the vehicular trailering assist system determines misalignment of the at least one camera at the trailer.