Structured Light Depth Detection Using Symbol Patterns
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Solution Overview
Problem
Existing depth detection systems in vehicle headlights face challenges in accurately determining distances and features of objects using structured light patterns, particularly in complex environments, due to the need for high-resolution light projection and precise symbol recognition.
Innovation Solution
The system employs a spatial light modulator (SLM) and a camera to project and capture a pattern of unique symbols, using epipolar lines and an essential matrix to determine the depth of symbols, allowing for reduced resolution requirements and efficient depth detection by searching for symbol sequences along approximated epipolar lines.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution light projection is used for accurate depth detection, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent segments the depth detection process into distinct stages: projecting structured light patterns with symbols, capturing images at multiple focal depths, identifying symbol locations and sequences, and calculating depth values. This segmentation allows each component to be optimized independently, reducing overall system complexity while maintaining measurement precision through systematic multi-focal-plane analysis
Solution Approach 2:
The patent introduces symbolic markers as intermediaries between the light projection system and the depth detection algorithm. These symbols serve as detectable features that bridge the optical field and computational processing, enabling accurate depth measurement without requiring direct high-resolution projection of the entire scene, thus reducing device complexity while preserving measurement accuracy
2Measurement precision
If multiple focal planes are captured for depth detection, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The patent employs periodic action by rapidly switching the focal plane of the imaging system between multiple predetermined depths in a sequential manner. Each focal plane capture is brief, and the rapid switching minimizes total integration time while still gathering sufficient data from multiple depths. The symbol sequences are designed to be captured across these periodic focal shifts, enabling accurate depth determination without excessive time loss
Solution Approach 2:
The patent performs preliminary action by pre-calculating and storing the relationships between symbol sequences at different focal planes and their corresponding depth values. During actual depth detection, the system only needs to capture images and match symbol sequences against the pre-established relationships, significantly reducing processing time while maintaining measurement precision through the pre-computed depth mappings
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 enables accurate and efficient depth detection in real-time, reducing integration complexity and improving the ability to detect distances and features of objects, even in non-continuous surfaces, enhancing safety features like autonomous driving and obstacle detection.
Implementation Method 1
instruct an SLM to project the symbol pattern
Implementation Method 2
obtain an image of a reflection of the symbol pattern
Data Source
AI summary
An example apparatus includes: a controller configured to: generate a symbol pattern as a result of placing symbols based on epipolar lines; instruct an SLM to project the symbol pattern; obtain an image of a reflection of the symbol pattern; determine a first location of a symbol in the image; determine a second location of the symbol in the image; and determine a depth of the symbol as based on the first location, the second location, and an essential matrix.