Depth Imaging With 2D-to-1D Dot-Trail Downsampling
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Solution Overview
Problem
Existing depth-imaging systems face challenges with multipath interference, subsurface diffusion, and high computational requirements in determining dot locations, leading to inaccurate depth measurements, particularly in complex environments.
Innovation Solution
A method involving downsampling 2D pixel grid data to 1D dot trail vectors, combining time-of-flight and triangulation measurements to accurately determine dot locations and depths, reducing computational complexity and enhancing accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If 2D pixel grid data is processed to determine dot locations, then depth measurement accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent segments the 2D pixel grid data processing into distinct stages: first identifying candidate pixels, then determining precise dot locations only for those candidates. This segmentation reduces computational complexity by avoiding exhaustive processing of all pixels while maintaining depth measurement accuracy through focused refinement on relevant regions.
Solution Approach 2:
The patent applies local quality by using different processing strategies for different regions: candidate pixel identification uses broader criteria, while precise dot location determination uses refined local analysis. This allows the system to maintain high measurement accuracy where needed while reducing computational effort in other areas.
2Reliability
If dot detection and identification is performed in complex environments, then depth measurement reliability is improved, but computational resources increase
Solution Approach 1:
The patent applies partial action by performing dot detection only on candidate pixels identified through initial filtering, rather than processing all pixels. This partial processing approach maintains reliability in complex environments by focusing computational resources on relevant regions while reducing overall energy consumption.
Solution Approach 2:
The patent uses preliminary action by first identifying candidate pixels using time-of-flight depth measurements and triangulation factors before performing more intensive dot location determination. This preliminary filtering reduces the number of pixels requiring full processing, thereby reducing computational resources while maintaining reliability.
3Measurement precision
If time-of-flight and triangulation measurements are combined, then depth measurement accuracy is improved, but device complexity increases
Solution Approach 1:
The patent merges time-of-flight depth measurements with triangulation factor calculations to determine dot locations. This combination of measurement techniques improves depth measurement accuracy by leveraging the strengths of both methods while integrating them into a unified processing framework.
Solution Approach 2:
The patent implements multi-functionality by using the combined time-of-flight and triangulation approach for multiple purposes: candidate pixel identification, dot location determination, and depth measurement. This universal approach improves accuracy across different measurement scenarios without requiring separate specialized systems.
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 improves depth measurement accuracy by simplifying dot detection and identification, allowing detection at further ranges and resolving subsurface diffusion issues, while reducing computational resources.
Implementation Method 1
an optical source configured to output modulated structured light comprising a pattern of dots
Implementation Method 2
Reflected illumination is received at an optical sensor comprising a 2D pixel grid
Implementation Method 3
a time-of-flight depth measurement
Data Source
AI summary
A method for operating a depth imaging system is presented. The method comprises illuminating an environment using an optical source configured to output modulated structured light comprising a pattern of dots. Reflected illumination is received at an optical sensor comprising a 2D pixel grid. Received reflected illumination from the 2D pixel grid is downsampled to a plurality of 1D dot trail vectors. For each dot trail vector, a depth is indicated based on a time-of-flight depth measurement and a triangulation factor.