Structured Light Depth Perception Using Adaptive Pre-Processing
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Solution Overview
Problem
Current machine vision systems face challenges in acquiring real-time and high-precision depth information, and existing image depth perception technologies are limited in providing natural human-machine interaction, especially in varying lighting conditions and computational complexity.
Innovation Solution
A hardware structure comprising an image adaptive pre-processing sub-module, a block-matching motion estimation sub-module, and a depth calculating sub-module, which processes speckle image sequences from external sensors, compares them with standard speckle images to calculate motion vectors and generate high-resolution depth images using structured light models, and employs noise-reducing filters for improved accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If binocular stereo camera is used for depth perception, then depth information can be acquired, but the system is affected by ambient light and has complex stereo matching process
Solution Approach 1:
The patent replaces the binocular stereo camera system with an active vision system using structured light projection. Instead of relying on passive ambient light and complex stereo matching, the system projects known pattern images onto the object surface and captures the deformed patterns to directly compute depth through triangulation, simplifying the overall process while improving reliability
Solution Approach 2:
The system pre-processes the captured image by comparing it with the original projected pattern image to calculate motion vectors before depth computation. This preliminary motion estimation step simplifies the subsequent depth calculation by providing direct motion information from the structured light patterns
2Productivity
If high-resolution depth image sequences are generated in real-time, then processing speed improves, but computational complexity increases
Solution Approach 1:
The patent divides the depth perception process into distinct modular steps: image acquisition, motion vector calculation through pattern matching, and depth computation. By segmenting the complex processing into independent stages, each can be optimized separately, enabling real-time high-resolution output without overwhelming computational complexity
Solution Approach 2:
The system dynamically adjusts processing parameters based on image characteristics and depth requirements. By optimizing parameters such as block size for motion estimation, threshold values for pattern matching, and resolution levels for depth output, the system achieves real-time performance while maintaining high resolution
3Measurement precision
If adaptive pre-processing is applied to speckle images with different characteristics, then image quality improves, but processing time increases
Solution Approach 1:
The patent implements adaptive pre-processing that dynamically adjusts processing intensity and parameters based on the characteristics of the input speckle images. The system automatically detects image quality metrics and applies appropriate processing levels, avoiding unnecessary processing time on already high-quality images while ensuring sufficient processing for low-quality images
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 solution enables high-precision, real-time generation of depth image sequences with reduced computational complexity and improved stability, allowing for natural human-machine interaction and extensive applications in gaming, healthcare, and education.
Implementation Method 1
infrared laser projects images of fixed model onto a surface of a subject, which forms speckles after the diffuse reflection of the surface of the object
Data Source
AI summary
In view of the active vision model based on structured light, a hardware structure of a depth perception device (a chip or an IP core) for high-precision images is disclosed. Simultaneously, the module is not only capable of serving as an independent chip, but also an embedded IP core in application. Main principle of the module is as follows. Speckle image sequence (obtained from an external image sensor and unknown depth information) is processed by adaptive and uniform pre-processing sub-module, then is inputted to the module to be compared with the standard speckle image (known depth information), then motion-vector information of the inputted speckle image is obtained by pattern matching of image blocks (similarity calculation) by the block-matching motion estimation sub-module, then depth image is obtained by depth calculation, and finally high-resolution sequence of depth image is outputted by post-processing the depth image.