Mobile Camera Calibration System for UAV Imaging Accuracy
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Solution Overview
Problem
Camera systems in mobile vehicles, such as UAVs, face calibration challenges due to environmental factors like wind, vibrations, and object impacts, leading to inaccurate imaging, and traditional calibration methods require the vehicle to stop, which is impractical.
Innovation Solution
A mobile camera calibration system that periodically or intermittently calibrates cameras using imaging targets, either stationary or on other mobile vehicles, by capturing images and comparing them to stored reference data to adjust for focal length, skew, distortion, and other parameters, allowing for continuous operation without the need to stop.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional calibration method is used (vehicle stops to focus on known image), then calibration accuracy is improved, but vehicle operation continuity deteriorates
Solution Approach 1:
The patent transforms the static calibration process into a dynamic one by enabling calibration to be performed while the vehicle is moving. The system captures images of calibration targets at different positions and orientations during motion, then uses computational algorithms to determine calibration parameters from these dynamic images, eliminating the need to stop the vehicle.
Solution Approach 2:
The system performs preliminary actions by capturing multiple images of calibration targets at various positions before processing. These pre-captured images from different viewpoints are then used to compute calibration parameters, allowing the system to maintain calibration accuracy without requiring the vehicle to stop for focused single-image capture.
2Measurement precision
If camera calibration is performed frequently to maintain accuracy in mobile environment, then imaging accuracy is improved, but system complexity and processing time worsen
Solution Approach 1:
The calibration system is designed to be universal and multi-functional. It can capture images of calibration targets at various positions and orientations using the existing camera hardware, and the same image processing pipeline handles both calibration computation and normal imaging tasks. This reduces the need for specialized dedicated calibration hardware.
Solution Approach 2:
The system performs self-calibration by automatically capturing images of calibration targets in the environment and computing its own calibration parameters without external intervention. The processing system automatically identifies calibration targets, extracts features, and determines calibration parameters, reducing operational complexity.
3Stability of the object's composition
If calibration is performed using stationary targets only, then calibration stability is improved, but adaptability to mobile environment deteriorates
Solution Approach 1:
The system accepts calibration targets in both stationary and mobile states, adapting to the dynamic mobile environment. It processes images of calibration targets captured during vehicle motion, accounting for varying positions, orientations, and distances, thereby maintaining calibration stability while being adaptable to mobile conditions.
Solution Approach 2:
The calibration system handles variations in imaging parameters such as focal length, principal point, and distortion coefficients by capturing images at different positions and orientations. The computational algorithm adjusts for these parameter changes to determine accurate calibration parameters, enabling adaptability to mobile environment while maintaining stability.
Data Source
AI summary
Camera calibration may be performed in a mobile environment. One or more cameras can be mounted on a mobile vehicle, such as an unmanned aerial vehicle (UAV) or an automobile. Because of the mobility of the vehicle the one or more cameras may be subjected to inaccuracy in imagery caused by various factors, such as environmental factors (e.g., airflow, wind, etc.), impact by other objects (e.g., debris, vehicles, etc.), vehicle vibrations, and the like. To reduce the inaccuracy in imagery, the mobile vehicle can include a mobile camera calibration system configured to calibrate the one or more cameras while the mobile vehicle is traveling along a path. The mobile camera calibration system can cause the one or more cameras to capture an image of an imaging target while moving, and calibrate the one or more cameras based on a comparison between the image and imaging target data.