Time-of-flight camera phase unwrapping using world space coordinate search
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Time-of-flight cameras face challenges in accurately determining distances greater than 2π due to phase wrapping, leading to ambiguity and spurious measurements, and existing solutions either reduce modulation frequency for accuracy or increase power consumption with multi-frequency modulation.
Innovation Solution
A time-of-flight camera system that determines phase wrapping using a single modulation frequency by converting camera space coordinates to world space coordinates, employing searching algorithms to fit analytic functions to candidate positions, and calculating depth values based on phase difference and wrapping, thereby resolving phase ambiguity without increasing power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the modulation frequency is reduced to improve depth measurement accuracy for distances greater than 2π, then measurement precision is improved, but productivity decreases due to longer measurement time
Solution Approach 1:
The depth measurement process is segmented into two stages: first obtaining a preliminary depth map using high modulation frequency for speed, then performing phase unwrapping only in regions where depth exceeds the unambiguous range. This segmentation allows most of the scene to be measured quickly while applying enhanced processing only where necessary.
Solution Approach 2:
Instead of applying low modulation frequency to the entire scene, the system applies phase unwrapping processing only to pixels that exceed the unambiguous depth range. This partial action approach maintains high measurement speed for nearby objects while ensuring accurate depth measurement for distant objects that require phase unwrapping.
2Measurement precision
If multi-frequency modulation is used to resolve phase wrapping and improve measurement precision, then measurement precision is improved, but use of energy increases
Solution Approach 1:
The patent extracts and processes only the problematic pixels that exhibit phase wrapping errors from the overall depth map. By identifying pixels where depth exceeds the unambiguous range and applying phase unwrapping only to those specific regions, the system avoids the energy-intensive multi-frequency modulation approach while maintaining accuracy where needed.
Solution Approach 2:
The system changes the modulation frequency parameter dynamically based on the measured depth values. High modulation frequency is used for the initial rapid measurement, and then the system switches to phase unwrapping processing for pixels that require extended range, rather than continuously using low frequency or multi-frequency modulation.
3Measurement precision
If phase unwrapping is applied to all pixels to resolve wrapping ambiguity, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system applies phase unwrapping processing only to pixels that exceed the unambiguous depth range rather than to all pixels. This selective approach significantly reduces processing complexity while maintaining measurement precision for the critical regions where phase wrapping occurs.
Solution Approach 2:
The patent replaces complex iterative phase unwrapping algorithms with a simpler depth-based thresholding approach. By using the preliminary depth map to identify pixels requiring unwrapping and then applying a simplified unwrapping process, the system reduces computational complexity while maintaining accuracy.
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
Accurately determines depth values for subjects at distances greater than 2π without phase wrapping ambiguity, maintaining power efficiency by using a single modulation frequency and advanced searching algorithms to model subject surfaces effectively.
Implementation Method 1
a time-of-flight illuminator configured to emit active IR light
Implementation Method 2
the light signal may be modulated in amplitude temporally to illuminate the subject
Implementation Method 3
the amplitude of the back-reflected light signal may be evaluated to determine a phase difference. The distance that the light signal travels from the source to the subject may be determined based on the phase difference φ
Data Source
Figure 1~2
Figure 3
Figure 4A
AI summary
A time-of-flight (ToF) camera is configured to illuminate a subject with IR light. For each sensor of a sensor array, camera space coordinates of a locus of the subject are determined based on the measured IR light. The camera space coordinates include a phase difference between emitted IR light and reflected IR light. A plurality of candidate positions of the locus of the subject are determined in world space based on the camera space coordinates. Each candidate position corresponds to a different phase wrapping of the phase difference. A phase wrapping is determined based on performing a searching algorithm on the different candidate positions. A depth value for the sensor is calculated based on the phase difference and the phase wrapping determined from performing the searching algorithm. A matrix of pixels is outputted from the camera. Each pixel of the matrix includes a depth value.