3D Image Sensor Calibration Using Distance Deviation Correction
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Solution Overview
Problem
3D image sensors, particularly TOF cameras, face reliability issues due to environmental and aging influences, leading to inaccurate distance measurements and impaired gesture recognition in vehicles, as they are sensitive to factors like temperature and humidity, affecting the precision of spatial area definitions and exclusion zones.
Innovation Solution
A method for calibrating 3D image sensors by measuring distances from fixed spatial points, determining distance deviations, and applying correction values to improve measurement reliability, which can be repeated to account for long-term accuracy despite external influences, using a computer-implemented process that includes parameters like time, temperature, and humidity for efficient calibration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If 3D image sensors are used for gesture recognition in vehicles, then user input capability is enhanced, but measurement precision deteriorates due to environmental and aging influences
Solution Approach 1:
The system performs preliminary calibration by measuring distances to multiple fixed spatial points and storing reference distance values before actual gesture recognition occurs. This preliminary action creates a baseline that compensates for environmental and aging influences, ensuring accurate distance measurements during subsequent gesture recognition operations.
Solution Approach 2:
The system changes calibration parameters by measuring distances to multiple spatial points at different locations and using these measurements to determine distance correction values. These correction values are then applied to adjust the 3D image sensor's distance measurements, compensating for environmental factors like temperature and humidity that cause parameter drift.
2Productivity
If distance measurements are performed without calibration, then measurement speed is maintained, but reliability deteriorates due to spatial shifts in regions of interest
Solution Approach 1:
The system performs preliminary calibration measurements to determine distance correction values before actual gesture recognition. These correction values are stored and applied during operation, enabling reliable measurements without slowing down the gesture recognition process. The preliminary action separates the calibration step from the measurement step, maintaining productivity while improving reliability.
3Device complexity
If calibration is performed using a single spatial point, then device complexity is reduced, but measurement precision deteriorates due to insufficient correction data
Solution Approach 1:
The calibration process is segmented into multiple independent measurements at different spatial points rather than a single complex measurement. The system measures distances to multiple fixed spatial points (at least two, preferably three or more) and processes each measurement separately to determine correction values. This segmentation improves precision by providing multiple data points for correction while keeping each individual measurement simple.
Solution Approach 2:
The calibration method using multiple spatial points serves multiple functions: it determines distance correction values for the entire field of view, identifies spatial shifts in regions of interest, and compensates for various environmental influences. This multi-functional approach improves measurement precision across the whole sensor field without proportionally increasing device complexity.
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
Enhances the reliability and accuracy of distance measurements and gesture recognition systems by providing a robust calibration method that compensates for environmental and aging factors, ensuring error-free interaction and long-term performance.
Implementation Method 1
a 3D image sensor, in particular a time-of-flight (TOF) camera
Data Source
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AI summary
The invention relates to a method and a device configured for carrying it out for calibrating a 3D image sensor. The method comprises: for each of a plurality of different predetermined spatial points on a radiation-reflecting surface, in particular a surface, of at least one physical structure in the field of view of a 3D image sensor, wherein the position of the spatial points in the field of view of the 3D image sensor is fixed in each case: initiating the measurement of a distance of the respective spatial point from the 3D image sensor and receiving a value for the distance measured in each case; and determining a distance deviation of the respective measured distance from a respective reference distance predetermined as a measure of the actual distance of the respective spatial point from the 3D image sensor.The method further comprises: determining a distance correction value as a function of the distance deviations determined for at least two of the spatial points, such that the distance correction value lies within the distance interval defined by these distance deviations; and taking the distance correction value into account when correcting the measurement result for at least one distance measured in a subsequent distance measurement using the 3D image sensor. The invention also relates to a computer program configured to carry out the method and to a gesture recognition system, in particular for gesture recognition in a vehicle, which includes the aforementioned calibration device.