Stereo-TOF Fusion for Accurate 3D Coordinate Extraction
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Solution Overview
Problem
Current methods for obtaining 3D coordinates, such as stereoscopic image processing and Time of Flight (TOF) sensors, face challenges in reliability due to variations in illumination, texture, and occlusion, leading to inaccurate depth information and high costs for active methods, while passive methods like stereo matching are cost-effective but have lower reliability.
Innovation Solution
A system combining a stereoscopic image photographing unit and a TOF sensor unit, with a controller to calculate disparity values based on pixel coordinates and distance measurements, and a calibration unit to map pixel coordinates to 3D coordinates, enhancing reliability by filtering out inaccurate results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If passive methods like stereo matching are used, then cost is reduced and resolution is improved, but reliability of depth information deteriorates due to image characteristics such as variation of illumination, texture, and presence of shield region
Solution Approach 1:
The patent combines two different measurement methods: stereo matching (passive method using image correlation) and TOF (active method using time-of-flight measurement). The controller integrates results from both methods, using TOF data to correct and refine stereo matching results, thereby improving reliability while maintaining cost-effectiveness through the use of standard camera hardware.
Solution Approach 2:
The TOF sensor acts as an intermediary that provides reliable depth information to compensate for the weaknesses of stereo matching. The controller uses TOF measurements as a reference to calibrate and correct disparity calculations from the stereo camera, effectively mediating between the two measurement approaches to produce more accurate 3D coordinates.
2Reliability
If active methods like 3D scanner or structured light are used, then reliability of 3D information is improved, but cost of device becomes very high
Solution Approach 1:
The patent uses a standard stereo camera setup (two ordinary photographing units) instead of expensive active 3D scanning equipment. The system leverages the inexpensive TOF sensor and standard image processing to achieve reliable 3D information, avoiding the need for costly specialized hardware while maintaining acceptable reliability through intelligent fusion of multiple measurement approaches.
3Device complexity
If stereo matching method is used, then cost is reduced, but reliability of depth information is lower due to various image characteristics
Solution Approach 1:
The system implements feedback by continuously comparing and validating stereo matching results against TOF measurements. The controller uses TOF data as a reference to correct discrepancies in disparity calculations, creating a feedback loop that iteratively refines the 3D coordinate extraction to improve reliability while maintaining the cost-effectiveness of the original stereo matching approach.
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
The system achieves highly reliable 3D coordinate extraction by integrating stereoscopic image processing with TOF sensor data, improving accuracy and reducing errors associated with texture and occlusion, while maintaining cost-effectiveness.
Implementation Method 1
a Time Of Flight (TOF) sensor unit to measure a value of a distance to the object
Data Source
AI summary
A system and method for extracting 3D coordinates, the method includes obtaining, by a stereoscopic image photographing unit, two images of a target object, and obtaining 3D coordinates of the object on the basis of coordinates of each pixel of the two images, measuring, by a Time of Flight (TOF) sensor unit, a value of a distance to the object, and obtaining 3D coordinates of the object on the basis of the measured distance value, mapping pixel coordinates of each image to the 3D coordinates obtained through the TOF sensor unit, and calibrating the mapped result, determining whether each set of pixel coordinates and the distance value to the object measured through the TOF sensor unit are present, calculating a disparity value on the basis of the distance value or the pixel coordinates, and calculating 3D coordinates of the object on the basis of the calculated disparity value.