ToF Camera Multi-Path Interference Detection and Correction
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Solution Overview
Problem
Time-of-flight cameras face challenges in generating accurate depth maps due to multi-path interference, which introduces distortion in the image data, reducing the confidence of the generated depth images.
Innovation Solution
A method is developed to detect and correct multi-path interference components by emitting two modulation signals of different frequencies, calculating the amplitude and offset of reflection modulation signals, and using a dual path model with a cost function to separate direct and indirect reflection components, thereby generating a corrected depth map.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multi-path interference components are included in reflection modulation signals, then the depth image can be generated using all available signal data, but the confidence and accuracy of the generated depth image deteriorates
Solution Approach 1:
The patent segments the reflection modulation signal into direct reflection components and indirect reflection components (multi-path interference). By separating these components, the system can process each independently, generating depth information from direct reflections with high accuracy while identifying distorted regions from indirect reflections, thus resolving the contradiction between utilizing all signal data and maintaining accuracy.
Solution Approach 2:
The patent introduces an intermediary detection mechanism that identifies multi-path interference components before they corrupt the depth image generation process. This intermediary step allows the system to filter or separately process distorted regions, preventing accuracy degradation while still utilizing non-distorted signal data for depth map generation.
2Measurement precision
If distortion correction is applied to the entire depth image, then the accuracy of distorted regions is improved, but the processing time and computational complexity increases
Solution Approach 1:
The patent applies local quality by selectively correcting only the distorted regions in the depth image rather than processing the entire image uniformly. By identifying specific areas affected by multi-path interference and applying correction algorithms only to those regions, the system maintains high accuracy where needed while minimizing unnecessary computational overhead in already-accurate regions.
Solution Approach 2:
The patent implements partial action by performing distortion correction only on the necessary portions of the depth image where multi-path interference is detected. This selective approach avoids the excessive processing that would result from applying correction to the entire image, thereby reducing processing time while still achieving the required accuracy in distorted regions.
3Measurement precision
If two modulation signals of different frequencies are emitted to detect multi-path interference, then the detection accuracy of distortion areas is improved, but the use of energy and device complexity increases
Solution Approach 1:
The patent employs periodic action by emitting modulation signals at different frequencies in an alternating or sequential manner rather than simultaneously. This time-division approach allows the system to use multiple frequencies for accurate distortion detection while reducing peak energy consumption and simplifying the hardware requirements compared to simultaneous multi-frequency emission.
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 enhances the accuracy of depth maps by identifying and minimizing distortion areas, improving processing efficiency and economic aspects by selectively correcting only the distorted portions of the image.
Implementation Method 1
a ToF method of obtaining a depth image by measuring a time for light emitted from a light source of the ToF camera to return to the ToF camera, after being reflected by a subject, and calculating a distance between the light source and the subject based on the time
Implementation Method 2
calculating a distance between the ToF camera and the subject by using a phase difference of a signal (hereinafter referred to as a 'reflection modulation signal') that is produced when the modulation signal is reflected by the subject and the wavelength of the modulation signal
Implementation Method 3
a reflection modulation signal that is produced when the modulation signal is reflected by the subject
Data Source
AI summary
Detecting a multi-path interference component in a time-of-flight (ToF) camera may be performed by generating a confidence map in which a distortion area attributable to a multi-path interference component included in a reflection modulation signals is specified, where the reflection modulation signals is generated when two modulation signals emitted from a light source to a subject return to the ToF camera after being reflected by the subject. Correcting the multi-path interference component corrects distortion attributable to a multi-path interference component, which may include correcting only the distortion area specified in the confidence map. Detecting the multi-path interference component in a ToF camera includes collecting the reflection modulation signal at a plurality of different times, calculating amplitudes and offsets of the collected reflection modulation signals, determining whether a multi-path interference component is included in the reflection modulation signal, and generating the confidence map.