Portable Camera-Accelerometer Calibration Using a Known Pattern
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Solution Overview
Problem
Existing methods for determining optical parameters of portable electronic devices, such as smartphones, require complex and costly laboratory calibration processes that are not scalable and rely on specific metrological equipment and trained professionals, making them impractical for widespread use.
Innovation Solution
A calibration method that allows untrained users to accurately determine parameters of portable electronic devices using image acquisition modules by providing a known pattern, guiding the device through different positions, and processing images to determine parameters like focal length without requiring specialized equipment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional laboratory calibration processes are used, then measurement precision is improved, but device complexity and ease of operation deteriorate due to requiring specialized equipment and trained professionals
Solution Approach 1:
The patent replaces complex laboratory metrological equipment with a simplified copy - a known geometric pattern (chessboard or circular grid) that can be captured by the device's own image acquisition module. This pattern serves as a surrogate calibration target that encodes spatial information needed for parameter determination, eliminating the need for expensive specialized equipment while maintaining measurement accuracy.
Solution Approach 2:
The patent substitutes mechanical/optical laboratory measurement systems with a digital image processing approach. Instead of using specialized optical equipment and manual measurement procedures, the system captures images of the known pattern using the device's camera and automatically computes calibration parameters through image processing algorithms, replacing complex mechanical systems with software-based solutions.
2Measurement precision
If laboratory calibration with metrological equipment is used, then measurement precision is improved, but ease of operation deteriorates due to requiring trained professionals
Solution Approach 1:
The calibration process is designed to be self-service, where the end user performs the calibration themselves without needing trained professionals. The user simply captures images of the known pattern using the device camera, and the system automatically processes these images to determine calibration parameters. This eliminates the need for specialized knowledge while maintaining measurement precision through automated image processing.
Solution Approach 2:
The calibration procedure is structured as a preliminary action that users can perform themselves before actual measurements. By providing clear instructions and using a simple known pattern, the system enables users to complete calibration independently, removing the barrier of requiring trained professionals and making the device accessible to general users.
3Ease of operation
If manufacturer-provided metadata is used, then ease of operation is improved, but measurement precision deteriorates due to potential inaccuracy
Solution Approach 1:
The system implements feedback by comparing manufacturer-provided metadata with actual measurements derived from images of the known pattern. The calibration process uses the captured images to compute accurate parameters, and this measured data serves as feedback to correct or validate the manufacturer's metadata, ensuring both ease of operation and measurement precision.
Solution Approach 2:
The system performs preliminary calibration by capturing and processing images of the known pattern before actual measurements. This preliminary action establishes accurate device parameters that can then be used for subsequent measurements, ensuring precision while maintaining ease of operation through automation. The manufacturer's metadata can be used as an initial estimate, but the actual calibration is performed through image processing.
Data Source
AI summary
A calibration method for determining angles between an image acquisition module reference frame and an accelerometer reference frame of a portable electronic device. The method includes receiving a set of images of a known pattern from the image acquisition module of the portable electronic device from different positions, the known pattern being in the same spatial position when acquired, and each image being associated with gravity data corresponding to the measurement of gravity by the accelerometer of the portable electronic device expressed in the accelerometer reference frame, determining the angles between the image acquisition module reference frame and the known pattern reference frame based on the received pictures of the set of pictures, and determining the angles between the image acquisition module reference frame and the accelerometer reference frame based on the determined angles between the image acquisition module reference frame and the known pattern reference frame and assuming the gravity measured by the accelerometer is the same for each image.