Time-of-Flight Depth Sensor Self-Calibration via Movable Obstruction
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Solution Overview
Problem
Traditional time-of-flight depth sensors require calibration using external objects, which is cumbersome and limits on-the-fly calibration capabilities, especially in scenarios where multiple systems need simultaneous calibration.
Innovation Solution
The implementation of on-the-fly calibration systems that utilize the placement of the imaging sensor and light source with respect to each other, incorporating a movable obstruction to adjust signal reception, allowing for self-calibration without external objects and enabling simultaneous calibration of multiple systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional calibration methods using external objects are used, then calibration can be performed, but the process becomes cumbersome and cannot be performed on-the-fly
Solution Approach 1:
The system performs self-calibration by using its own internal components (light source, imaging sensor, and integrated obstruction) to determine calibration parameters. The processor utilizes signals from the imaging sensor and knowledge of the obstruction's position to calculate calibration information without requiring external calibration objects or manual intervention, enabling on-the-fly calibration.
2Measurement precision
If external calibration objects are used, then calibration accuracy can be achieved, but multiple systems cannot be calibrated simultaneously
Solution Approach 1:
The patent extracts the calibration function from external objects and integrates it into the system itself. The obstruction, which is already part of the system structure, is utilized as the calibration target. This eliminates the need for external calibration objects and allows multiple systems to be calibrated simultaneously using their respective integrated obstructions without interference.
3Illumination intensity
If the obstruction is positioned closer to the light emitter, then signal level increases, but the system cannot distinguish between direct light and reflected light
Solution Approach 1:
The system performs preliminary actions by capturing images at multiple distinct distances from the obstruction before actual calibration is needed. These pre-captured images at different distances provide the processor with data to distinguish between direct light and reflected light paths, enabling accurate calibration without requiring the obstruction to be positioned at a specific distance during calibration.
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
Enables accurate and efficient self-calibration of time-of-flight depth sensors, allowing for simultaneous calibration of multiple systems, reducing the need for external calibration objects and improving calibration speed and accuracy.
Implementation Method 1
a light source configured to emit light
Implementation Method 2
reflected light comprising a plurality of pixels
Implementation Method 3
measuring the time-of-flight of a light signal between the camera and the subject for each point of the image
Implementation Method 4
an image sensor for collecting incoming signals including reflected light
Data Source
AI summary
An image processing system having on-the-fly calibration uses the placement of the imaging sensor and the light source for calibration. The placement of the imaging sensor and light source with respect to each other affect the amount of signal received by a pixel as a function of distance to a selected object. For example, an obstruction can block the light emitter, and as the obstruction is positioned an increasing distance away from the light emitter, the signal level increases as light rays leave the light emitters, bounce off the obstruction and are received by the imaging sensor. The system includes a light source configured to emit light, and an image sensor to collect incoming signals including reflected light, and a processor to determine a distance measurement at each of the pixels and calibrate the system.