TOF Depth Map Accuracy via Parallax Noise Filtering
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Solution Overview
Problem
Time of flight 3D camera mapping systems face signal noise due to multipath interference from surfaces and environmental reflections, which current algorithms attempt to mitigate but at the cost of increased processing and power consumption.
Innovation Solution
The system employs non-mathematical assumptive rules and sequential viewing with parallax adjustments to reduce multipath noise by shifting the position of the TOF system to create additional views, allowing object recognition to filter out extraneous data and select the less noisy view for improved 3D depth mapping accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If computational algorithms are used to reduce multipath interference, then 3D depth mapping accuracy is improved, but processing power consumption increases
Solution Approach 1:
The system performs preliminary actions by capturing multiple images from different positions before processing. The TOF system is moved to multiple locations to capture images in advance, and the selection of the best image is made after capture but before final processing, thereby reducing the need for computationally intensive multipath filtering algorithms
Solution Approach 2:
The harmful multipath interference is extracted and removed by selecting only the direct reflection path. The system identifies and extracts the cleanest image with the least multipath interference by comparing multiple captured images, thereby eliminating the need for complex algorithms to filter out noise
2Measurement precision
If computational algorithms are used to reduce multipath interference, then 3D depth mapping accuracy is improved, but device complexity increases
Solution Approach 1:
The complex multipath filtering algorithms are replaced by extracting the essential information from multiple captured images. The system simply compares and selects the image with the least interference, thereby reducing device complexity while maintaining accuracy
Solution Approach 2:
Instead of using complex algorithms to process a single image, the system creates multiple copies of the scene from different positions and selects the best copy. This approach replaces computational complexity with physical redundancy
3Measurement precision
If multiple views with parallax are captured, then multipath noise is reduced, but imaging time increases
Solution Approach 1:
Multiple images are captured in advance from different positions, and the selection is made after capture. This preliminary action allows the system to gather all necessary data before processing, reducing the time needed during actual operation
Solution Approach 2:
The system captures more images than strictly necessary (excessive action) to ensure that at least one image with minimal multipath interference is obtained. This approach trades some imaging time for reliable 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
This approach enhances 3D depth mapping accuracy by reducing noise from reflections, specifically from surfaces like walls and ceilings, without the computational intensity of traditional algorithms, thereby improving the system's efficiency and reducing power consumption.
Implementation Method 1
timing the periods from laser transmission to reception of each reflection
Implementation Method 2
The time of flight for each detected reflection by a sensor, typically a complementary metal oxide semiconductor (CMOS) camera, is converted to distance to generate the depth map
Implementation Method 3
the position of the TOF system can be shifted in one or more axes, to create an additional view which produces parallax relative to the initial view
Data Source
AI summary
Parallax views of objects are used to generate 3D depth maps of the objects using time of flight (TOF) information. In this way, the deleterious effects of multipath interference can be reduced to improve 3D depth map accuracy without using computationally intensive algorithms.