Time-of-Flight Depth-Map Object Grouping for False Target Filtering
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Solution Overview
Problem
Time-of-flight ranging devices suffer from false targets due to blurring, veiling glare, flickering, and mismatched laser pulse responses, which compromise their accurate performance by generating erroneous readings and reducing contrast, leading to inaccurate range measurements.
Innovation Solution
Implementing object grouping algorithms for time-of-flight ranging devices that conduct raster or spiral searches to distinguish objects, detect edges, calculate high-level parameters, and apply thresholding techniques to separate objects and mitigate veiling glare effects, enhancing spatial awareness and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the ToF device is designed to be highly sensitive to detect actual targets, then detection precision is improved, but false targets are more susceptible to be generated
Solution Approach 1:
The patent segments the depth map into multiple objects by detecting edges and grouping connected regions. Each object is processed separately through thresholding operations, allowing the system to distinguish between real objects and false targets generated by veiling glare or other artifacts. This segmentation approach enables high sensitivity for actual targets while reducing false positives through localized analysis.
Solution Approach 2:
The patent converts the harmful veiling glare effect into a detectable pattern by searching for its characteristic bowl-shaped profile in the depth map. By identifying the specific geometric pattern of veiling glare, the system can distinguish it from real objects and apply appropriate filtering, effectively turning the harmful artifact into a recognizable signal for removal.
2Reliability
If veiling glare is present in the depth map, then contrast is reduced and false targets are created, but the system needs to maintain sensitivity for real objects
Solution Approach 1:
The patent introduces an intermediary processing layer that applies thresholding operations between the raw depth map and the final object identification. By searching for edges and grouping connected regions above a threshold, the system creates an intermediate representation that filters out veiling glare while preserving real objects, enabling reliable range measurements despite the presence of harmful factors.
Solution Approach 2:
The patent detects the characteristic bowl-shaped profile of veiling glare in the depth map and uses this pattern recognition to identify and remove the harmful effect. By converting the veiling glare's geometric signature into a detectable feature, the system can reliably distinguish it from real objects and maintain measurement accuracy.
3Measurement precision
If the laser pulse shape does not match the SPAD response, then measurement accuracy is compromised, but the system cannot change the fundamental detection mechanism
Solution Approach 1:
The patent extracts and removes the harmful components caused by laser pulse shape mismatches and SPAD after-pulsing effects through thresholding operations. By identifying and filtering out signals that do not correspond to actual objects based on their temporal and spatial characteristics, the system maintains measurement precision without fundamentally changing the detection mechanism or increasing processing 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
The algorithms effectively eliminate false targets, improve object recognition, and enhance the reliability and precision of range measurements by accurately distinguishing between different objects and compensating for veiling glare, thereby improving the overall performance of time-of-flight sensors.
Implementation Method 1
time-of-flight ranging devices
Implementation Method 2
blurring and veiling-glare of the lens
Data Source
AI summary
According to an embodiment, a method for object abstraction to distinguish between different objects in a depth map generated from a time-of-flight sensor is proposed. The method includes conducting a raster or spiral search on the depth map. The raster search includes alternating between sweeping left to right and then up and down systematically. The spiral search includes a circumferential-direction scanning. The method further includes detecting edges of an object to guide a continuation of the raster or spiral search, calculating one or more high-level parameters related to the object, and repeating the raster or spiral search for cells of the depth map that have not been previously swept to similarly identify other objects.