Wearable AR Interface for Automated Camera Calibration Validation
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Solution Overview
Problem
Cameras used in vehicle navigational systems, such as unmanned aerial vehicles, require frequent recalibration due to position errors caused by stresses, thermal changes, and jostling, leading to unreliable output unless periodically recalibrated.
Innovation Solution
The use of a wearable head-mounted device with augmented reality and a moveable or fixed calibration target to automate the camera calibration process, allowing for real-time data collection and validation, reducing the need for manual intervention and increasing calibration fidelity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If cameras are manually calibrated by technicians, then calibration can be performed, but it requires significant time and human operators
Solution Approach 1:
The system enables self-service calibration where the camera system automatically performs calibration without human operators. The calibration engine autonomously processes images captured by cameras, detects calibration targets, computes camera parameters, and validates results without requiring technician intervention, thereby eliminating time loss associated with manual calibration operations.
Solution Approach 2:
The patent replaces the mechanical/manual calibration process with an automated computational system. Instead of technicians physically adjusting camera parameters, the system uses image processing algorithms and computer vision techniques to automatically determine and adjust calibration parameters based on captured images of calibration targets.
2Reliability
If cameras are recalibrated frequently to maintain accuracy, then reliable output is ensured, but operational efficiency decreases
Solution Approach 1:
The system implements feedback through automated validation that determines whether recalibration is actually needed. The validation process analyzes current camera output and comparison images to assess calibration quality, only triggering recalibration when necessary. This feedback mechanism maintains reliability by ensuring accurate output while avoiding unnecessary recalibrations that would reduce productivity.
Solution Approach 2:
The system employs periodic validation checks to monitor calibration status over time. Rather than continuous recalibration, the system performs scheduled validation assessments to determine if recalibration is needed, implementing recalibration only when the periodic checks indicate degradation in calibration quality, thus balancing reliability with operational efficiency.
3Productivity
If automated calibration systems are implemented, then time and human operators are reduced, but system complexity increases
Solution Approach 1:
The calibration system is designed with multi-functionality to justify its complexity. The same system infrastructure serves multiple purposes: capturing calibration images, detecting calibration targets, computing camera parameters, validating calibration results, and determining when recalibration is needed. This universal approach consolidates multiple functions into a single integrated system, improving productivity while managing complexity through consolidation rather than proliferation of separate systems.
Data Source
AI summary
Methods and systems for collecting camera calibration data using wearable devices are described. An augmented reality interface may be provided at a wearable device. Directions for a user to present a calibration target to a camera may be presented at the augmented reality interface. Calibration data collected by the camera viewing the calibration target may be received. Existing calibration data for the camera may be validated based at least in part on the collected calibration data.