Time-of-Flight Depth Disambiguation for Reflective Surfaces
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Solution Overview
Problem
Conventional time-of-flight sensors are prone to erroneous depth determinations on highly reflective surfaces, leading to unreliable data and increased processing time, especially in environments with varied lighting and objects of different reflectivity.
Innovation Solution
The method involves generating multiple exposures at different modulation frequencies and applying selective depth determination techniques to subsets of pixels, using a more reliable technique for high-intensity pixels associated with reflective surfaces and a less resource-intensive technique for other pixels, followed by generating composite sensor data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional time-of-flight sensors are used to capture depth data, then the sensors can operate in real-time, but the depth measurements become unreliable on highly reflective surfaces
Solution Approach 1:
The patent segments the pixel array into multiple regions with different exposure settings. Specifically, it divides pixels into those requiring longer exposure times and those requiring shorter exposure times based on their reflectivity characteristics. This segmentation allows the system to capture reliable depth data from both highly reflective surfaces and non-reflective surfaces simultaneously by processing each segment with appropriate exposure parameters.
2Reliability
If multiple exposures are taken to improve depth measurement accuracy, then the reliability of depth data increases, but the processing time increases
Solution Approach 1:
The patent takes multiple exposures simultaneously by dividing the pixel array into segments that capture different exposure times in parallel. Rather than sequentially capturing multiple exposures, the system uses a segmented approach where different regions of the sensor capture different exposure durations at the same time, then combines these segments to produce a single composite depth image. This eliminates the time penalty of sequential processing while maintaining the reliability benefits of multiple exposures.
3Measurement precision
If a single exposure time is used for all pixels, then the device complexity is low, but the measurement precision decreases for highly reflective surfaces
Solution Approach 1:
The patent implements segmentation of the pixel array into multiple regions, each with optimized exposure settings tailored to the reflectivity characteristics of surfaces in that region. This allows the system to achieve high measurement precision for both highly reflective and non-reflective surfaces by applying appropriate exposure times to each segment, rather than using a single uniform exposure time for the entire sensor array.
4Measurement precision
If extensive post-processing is applied to correct depth errors, then the measurement precision improves, but the productivity decreases
Solution Approach 1:
The patent performs preliminary depth disambiguation during the data capture phase by segmenting pixels and applying appropriate exposure settings before the data is fully acquired. By resolving depth ambiguities for highly reflective surfaces during the exposure and initial processing stages rather than requiring extensive post-processing, the system maintains high measurement precision while preserving object identification efficiency and overall productivity.
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 the accuracy and reliability of depth measurements, reducing the need for extensive post-processing and enhancing the safety and efficiency of navigation systems by providing more robust sensor data.
Implementation Method 1
Time-of-flight sensors can generate both image (intensity) information and range (depth) information
Implementation Method 2
receiving, from the time-of-flight (ToF) sensor, first ToF data corresponding to a first exposure time associated with a first modulation frequency of the ToF sensor
Data Source
AI summary
Sensors, including time-of-flight sensors, may be used to detect objects in an environment. In an example, a vehicle may include a time-of-flight sensor that images objects around the vehicle, e.g., so the vehicle can navigate relative to the objects. Composite sensor data can be generated based on information from multiple exposures captured at different exposure times. In examples, a first depth determination technique is applied to a first subset of pixels and a second depth determination technique is applied to a second subset of the pixels. The first subset of pixels may correspond to pixels that are associated with a highly-reflective surface.