3D Camera Unambiguous Range Extension via Multi-Frequency Pipelining
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Solution Overview
Problem
Conventional 3D TOF cameras based on the photonic mixing principle have a limited range of unambiguity, leading to ambiguous distance measurements for objects beyond a certain range, as they rely on a single modulation frequency, resulting in imperfect 3D image data with uncertain absolute distance information.
Innovation Solution
A pipelined digital image processing approach is employed, where uncombined 3D image data from multiple modulation frequencies are processed in stages to extend the range of unambiguity and correct absolute distance information, allowing for improved image processing even with imperfect data, using a combination of coarse and fine filtering techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single modulation frequency is used in 3D TOF cameras, then the device complexity is reduced, but the range of unambiguity is limited and distance measurements become ambiguous for objects beyond a certain range
Solution Approach 1:
The patent segments the distance measurement task by using multiple modulation frequencies (e.g., first and second modulation frequencies with different frequencies) to measure distances in different ranges. The first modulation frequency is used for close-range measurements while the second modulation frequency is used for far-range measurements, allowing the system to overcome the limited unambiguous range of single-frequency TOF measurement.
Solution Approach 2:
The patent changes the modulation frequency parameter dynamically based on the required measurement range. By switching between different modulation frequencies, the system adjusts the unambiguous range parameter to accommodate objects at various distances, thereby resolving the contradiction between device simplicity and measurement precision.
2Measurement precision
If multiple modulation frequencies are used to extend the range of unambiguity, then the measurement precision is improved, but the device complexity and processing requirements increase
Solution Approach 1:
The patent segments the image processing into distinct stages: first processing the 3D image data obtained with the first modulation frequency, then processing the data from the second modulation frequency, and finally combining the results. This segmentation allows complex processing to be managed in manageable steps, reducing the overall complexity burden.
Solution Approach 2:
The patent performs preliminary processing of 3D image data from each modulation frequency separately before combining them. By preparing and processing the data from each frequency independently in advance, the system reduces the complexity of the final combination step and enables more efficient integrated processing.
3Reliability
If 3D image data is processed in conventional sequential manner, then the processing completeness is maintained, but the latency increases and real-time performance is reduced
Solution Approach 1:
The patent performs preliminary processing of 3D image data as soon as it is available from each modulation frequency, before the complete multi-frequency measurement sequence is finished. This allows intermediate results to be processed and ready for combination earlier, reducing overall latency while maintaining processing completeness.
Solution Approach 2:
The patent maintains continuous processing by overlapping the measurement and processing operations. While one modulation frequency is being measured, preliminary processing of previous frequency data can proceed simultaneously, ensuring continuous productive action and reducing idle time and latency.
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 reduces latency and improves the performance of 3D image processing by providing corrected absolute distance information and enhancing the detection of edges and structures, enabling more accurate 3D image rendering with reduced ambiguity.
Implementation Method 1
3D cameras which are for example based on the ToF principle (time-of-flight principle)
Implementation Method 2
first phase information of a first modulated optical signal and second phase information of a second modulated optical signal
Data Source
AI summary
A method comprises obtaining first information, the first information including depth information with a first range of unambiguity. A first image processing is performed on the first information to generate first modified information. Furthermore, second information is obtained, the second information including depth information with a second range of unambiguity.