Multi-Camera Calibration Using Device Reflections
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Solution Overview
Problem
Depth-sensing imaging devices with multiple cameras face accuracy and precision issues due to manufacturing variability, requiring recalibration over time due to temperature fluctuations and mechanical forces, necessitating improved user-friendly recalibration techniques.
Innovation Solution
The method involves capturing reflection images of the device itself using its cameras, analyzing recognizable components like light sources to determine calibration parameters, eliminating the need for specialized hardware and allowing recalibration with readily available reflecting surfaces such as computer screens.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional calibration methods using specialized hardware are used, then measurement precision is improved, but device complexity and ease of operation deteriorate
Solution Approach 1:
The device uses itself as the calibration object by capturing images of its own reflections in environmental surfaces. The imaging device's cameras photograph reflections of its light sources and structural features in mirrors, windows, or other reflective surfaces, eliminating the need for external specialized calibration hardware. This self-calibration approach maintains measurement precision while dramatically improving ease of operation.
Solution Approach 2:
The system creates virtual copies of the device's light sources and structural features through reflection images. By analyzing the positions and characteristics of reflected light sources in captured images, the system generates calibration data without requiring physical calibration objects. The reflection acts as a virtual copy that provides sufficient geometric information for accurate calibration.
2Measurement precision
If traditional calibration methods using specialized hardware are used, then measurement precision is improved, but device complexity worsens
Solution Approach 1:
The imaging device performs calibration using only its own components (cameras, light sources, and processing unit) without requiring external calibration equipment. The device captures reflection images with its built-in cameras, processes these images to extract calibration parameters, and updates its internal calibration data. This eliminates the need for separate calibration hardware, mirrors, or specialized tools, thereby reducing overall system complexity.
Solution Approach 2:
The imaging device's camera system serves dual purposes: it functions as both the operational imaging component and the calibration data acquisition device. The same cameras used for capturing scenes are also used to capture reflection images for calibration. This multi-functionality eliminates the need for dedicated calibration hardware, reducing device complexity while maintaining calibration precision.
3Measurement precision
If frequent recalibration is performed to maintain accuracy, then measurement precision is improved, but loss of time worsens
Solution Approach 1:
The device can perform rapid self-calibration at the user's convenience without requiring specialized calibration equipment or extended calibration procedures. The automated reflection-based calibration process takes only a few seconds to capture images and compute updated parameters, enabling frequent recalibration to maintain accuracy without significant time loss.
Solution Approach 2:
The calibration process uses only a subset of the device's full imaging capability, focusing specifically on capturing reflections of light sources rather than complete scene imaging. This partial action approach requires fewer computational resources and less time than full calibration sequences, allowing rapid recalibration while maintaining sufficient precision for positional determinations.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables quick and convenient recalibration with reduced overhead, allowing users to maintain accurate positional determinations without specialized equipment, adapting to changes in device parameters over time.
Implementation Method 1
capturing a plurality of images of a reflection of the motion capture device
Data Source
AI summary
The technology disclosed can provide capabilities such as calibrating an imaging device based on images taken by device cameras of reflections of the device itself. Implementations exploit device components that are easily recognizable in the images, such as one or more light-emitting devices (LEDs) or other light sources to eliminate the need for specialized calibration hardware and can be accomplished, instead, with hardware readily available to a user of the device—the device itself and a reflecting surface, such as a computer screen. The user may hold the device near the screen under varying orientations and capture a series of images of the reflection with the device's cameras. These images are analyzed to determine camera parameters based on the known positions of the light sources. If the positions of the light sources themselves are subject to errors requiring calibration, they may be solved for as unknowns in the analysis.