ToF Camera Reflectance Calibration via Phase Shift
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Solution Overview
Problem
Conventional time-of-flight (ToF) measurement techniques require multiple sequential exposures and complex calculations to determine depth maps, which can be inefficient and prone to errors, especially for high-precision measurements with extended unambiguous ranges.
Innovation Solution
A method and device for ToF measurement that calculates reflectance values using distance and intensity measurements from pixels in a ToF sensor, employing reflectance calibration factors to compensate for viewing angles and distances, allowing for the normalization of pixel values and formation of reflectance images and three-dimensional point-clouds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sequential exposures are used for high-precision depth measurements, then measurement precision is improved, but loss of time increases due to the sequential nature of the measurements
Solution Approach 1:
The patent uses periodic modulation of the light source at different phases (0°, 90°, 180°, 270°) to encode depth information in the temporal domain. By measuring the phase shift of the reflected modulated light, the system can determine depth with high precision while reducing the number of sequential exposures needed compared to conventional methods.
Solution Approach 2:
The patent changes the modulation phase parameter across multiple measurements to extract depth information. By varying the phase of the modulating signal and measuring the corresponding phase shift in the reflected light, the system achieves high-precision depth measurement more efficiently than conventional sequential exposure methods.
2Measurement precision
If multiple sequential exposures with different phase modulations are performed, then depth measurement accuracy is improved, but device complexity increases due to the need for multiple exposures and phase management
Solution Approach 1:
The system employs periodic phase modulation of the light source and corresponding phase-shifted demodulation at the pixel level. This periodic action allows the extraction of depth information through phase shift measurement, improving accuracy while managing complexity through systematic phase cycling rather than requiring complex multi-exposure sequences.
Solution Approach 2:
Each pixel in the sensor array performs self-demodulation of the reflected modulated light signal using locally generated reference signals at different phases. This distributed self-service approach at the pixel level simplifies the overall system architecture by eliminating the need for complex external phase control and synchronization mechanisms.
3Measurement precision
If reflectance calibration factors are calculated for each pixel to compensate for viewing angles and distances, then measurement precision is improved, but device complexity increases due to additional calibration and calculation requirements
Solution Approach 1:
The patent applies pixel-specific reflectance calibration factors that account for local variations in viewing angle and distance for each pixel or pixel group. This local quality approach compensates for geometric effects individually for each sensor element, improving reflectance measurement precision without requiring a single complex global calibration model.
Solution Approach 2:
The system performs preliminary calibration to determine reflectance calibration factors for each pixel before actual measurements are taken. This preliminary action stores the calibration data for reuse, eliminating the need to perform complex calibration calculations during every measurement sequence, thus improving precision while managing complexity through pre-computation.
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 and efficiency of ToF measurements by providing a reflectance map alongside depth maps, enabling improved object recognition, material classification, and additional data for applications like skin color detection and sweat detection, while reducing the number of required exposures.
Implementation Method 1
depth measurements, i.e., measurements of the distance to various features of an object or objects in view of an image sensor may be performed as so-called time-of-flight (ToF) measurements, which are distance measurements determined using the speed of light
Implementation Method 2
the reflectance calibration factor compensating for at least one of a viewing angle for the one or more pixels using Lambert's cosine law
Implementation Method 3
a difference between a distance to a planar, diffuse, calibration surface measured by the one or more pixels and a distance calibration value using inverse square law
Data Source
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AI summary
Techniques for obtaining reflectance measurements using a time-of-flight (ToF) measurement device. An example method comprises obtaining a distance measurement, using one or more pixels in a ToF sensor, obtaining an intensity measurement corresponding to the distance measurement, using the one or more pixels, and calculating a reflectance value, based on the distance measurement, the intensity measurement, and a reflectance calibration factor. In some embodiments, the calibration distance is obtained by measuring a reference distance to a calibration surface, using a reference pixel in the ToF sensor, and obtaining the calibration distance from the measured reference distance. In some of these embodiments, the reflectance calibration factor is obtained by obtaining a reference intensity corresponding to the reference distance, using the reference pixel, and calculating the reflectance calibration factor for the one or more pixels as a function of the reference intensity and a viewing angle for the one or more pixels.