Time-of-Flight Camera Multipath Reflection Reduction
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Solution Overview
Problem
Time-of-flight camera systems used for volume dimensioning face distortion issues due to multipath reflections, especially in uncontrolled environments where background sources of reflection are unknown or changeable, leading to inaccurate depth estimation.
Innovation Solution
The system employs a sequence of illumination patterns, including an initial spatial pattern and refined spatial patterns, to adjust and reduce multipath reflections by determining the approximate boundary of the target object and selectively illuminating areas that contribute to distortion, using a control subsystem to modulate the illumination and reduce background interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional TOF camera systems are used for volume dimensioning, then depth measurement is obtained, but distortion occurs due to multipath reflections from background surfaces
Solution Approach 1:
The system performs preliminary actions by first capturing an image of the target object, determining its approximate boundary, and identifying distortion-causing background areas before performing volume dimensioning. This preliminary identification allows the system to exclude harmful reflections from the measurement calculation, thereby resolving the contradiction between obtaining depth measurement and avoiding multipath reflection distortion.
Solution Approach 2:
The system extracts and separates the target object from the background by determining the object's approximate boundary and identifying background areas that cause distortion. By taking out the harmful background elements from the measurement process and using only the cleaned image data for volume calculation, the system eliminates multipath reflection distortion while maintaining accurate depth measurement.
2Measurement precision
If sequential illumination patterns are used to reduce multipath reflections, then measurement accuracy is improved, but processing time increases
Solution Approach 1:
The system performs preliminary image capture and boundary determination before the actual volume dimensioning measurement. By preparing the cleaned image data and identifying distortion areas in advance, the system enables faster processing during the measurement phase, thus improving volume dimensioning accuracy without excessive time loss.
Solution Approach 2:
The system applies partial action by using only the necessary portions of the image data (areas within the object boundary and excluding distortion-causing background areas) for volume calculation. This selective use of data reduces processing requirements while maintaining measurement accuracy, thereby balancing precision with processing time efficiency.
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 significantly reduces distortion in image data, enabling more accurate volume dimensioning of non-standard sized and shaped parcels and packages by minimizing the impact of multipath reflections, thereby improving the precision of volume measurement.
Implementation Method 1
TOF camera systems typically determine depth of an object, or portion thereof, based on the time which passes between emitting the illumination and detecting return of the illumination
Implementation Method 2
The illumination sources provide modulated illumination, allowing active illumination by the illumination sources to be discerned from background illumination
Implementation Method 3
In an ideal situation, a ray of light is emitted, travels to the target object, is reflected, and detected by the optical sensor
Data Source
AI summary
Volume dimensioning employs techniques to reduce multipath reflection or return of illumination, and hence distortion. Volume dimensioning for any given target object includes a sequence of one or more illuminations and respective detections of returned illumination. A sequence typically includes illumination with at least one initial spatial illumination pattern and with one or more refined spatial illumination patterns. Refined spatial illumination patterns are generated based on previous illumination in order to reduce distortion. The number of refined spatial illumination patterns in a sequence may be fixed, or may vary based on results of prior illumination(s) in the sequence. Refined spatial illumination patterns may avoid illuminating background areas that contribute to distortion. Sometimes, illumination with the initial spatial illumination pattern may produce sufficiently acceptable results, and refined spatial illumination patterns in the sequence omitted.


