Real-Time Dynamic 3D Shape Reconstruction with SWIR InGaAs Camera

Fei, Cheng; Ma, Yanyang; Jiang, Shan; Liu, Junliang; Sun, Baoqing; Li, Yongfu; Gu, Yi; Zhao, Xian; Fang, Jiaxiong

doi:10.3390/s20020521

Cited by 8 publications

(2 citation statements)

References 27 publications

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“…Cheng Fei et al [ 58 ] used shortwave infrared cameras to monitor targets in low-brightness environments. Improved Fourier transform profilometry is used to obtain the depth information, and a plastic model is used in the experiment to evaluate the measurement accuracy of the system.…”

Section: Multi-view Stereo Vision Measurement Methodsmentioning

confidence: 99%

Three-Dimensional Morphology and Size Measurement of High-Temperature Metal Components Based on Machine Vision Technology: A Review

Wen

Wang

Zhang

et al. 2021

Sensors

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The three-dimensional (3D) size and morphology of high-temperature metal components need to be measured in real time during manufacturing processes, such as forging and rolling. Since the surface temperature of a metal component is very high during the forming and manufacturing process, manually measuring the size of a metal component at a close distance is difficult; hence, a non-contact measurement technology is required to complete the measurement. Recently, machine vision technology has been developed, which is a non-contact measurement technology that only needs to capture multiple images of a measured object to obtain the 3D size and morphology information, and this technology can be used in some extreme conditions. Machine vision technology has been widely used in industrial, agricultural, military and other fields, especially fields involving various high-temperature metal components. This paper provides a comprehensive review of the application of machine vision technology in measuring the 3D size and morphology of high-temperature metal components. Furthermore, according to the principle and method of measuring equipment structures, this review highlights two aspects in detail: laser scanning measurement and multi-view stereo vision technology. Special attention is paid to each method through comparisons and analyses to provide essential technical references for subsequent researchers.

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Section: Multi-view Stereo Vision Measurement Methodsmentioning

confidence: 99%

Three-Dimensional Morphology and Size Measurement of High-Temperature Metal Components Based on Machine Vision Technology: A Review

Wen

Wang

Zhang

et al. 2021

Sensors

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“…In recent years, with the emergence of different types of depth camera sensors, a more convenient and economical research method has been provided for the research of 3D reconstruction. More and more real-time 3D reconstruction technologies based on depth cameras have been continuously proposed [ 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 ]. Henry et al adopted a RGB-D closest point iteration method that makes full use of color information and depth information [ 11 ], and proposed a framework called RGB-D Mapping.…”

Section: Introductionmentioning

confidence: 99%

Real-Time 3D Reconstruction Method Based on Monocular Vision

Jia

Chang

Qiang

et al. 2021

Sensors

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Real-time 3D reconstruction is one of the current popular research directions of computer vision, and it has become the core technology in the fields of virtual reality, industrialized automatic systems, and mobile robot path planning. Currently, there are three main problems in the real-time 3D reconstruction field. Firstly, it is expensive. It requires more varied sensors, so it is less convenient. Secondly, the reconstruction speed is slow, and the 3D model cannot be established accurately in real time. Thirdly, the reconstruction error is large, which cannot meet the requirements of scenes with accuracy. For this reason, we propose a real-time 3D reconstruction method based on monocular vision in this paper. Firstly, a single RGB-D camera is used to collect visual information in real time, and the YOLACT++ network is used to identify and segment the visual information to extract part of the important visual information. Secondly, we combine the three stages of depth recovery, depth optimization, and deep fusion to propose a three-dimensional position estimation method based on deep learning for joint coding of visual information. It can reduce the depth error caused by the depth measurement process, and the accurate 3D point values of the segmented image can be obtained directly. Finally, we propose a method based on the limited outlier adjustment of the cluster center distance to optimize the three-dimensional point values obtained above. It improves the real-time reconstruction accuracy and obtains the three-dimensional model of the object in real time. Experimental results show that this method only needs a single RGB-D camera, which is not only low cost and convenient to use, but also significantly improves the speed and accuracy of 3D reconstruction.

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Indium composition effects on extended short-wave infrared photodetector performance

Chun

2023

J. Korean Phys. Soc.

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Real-Time Dynamic 3D Shape Reconstruction with SWIR InGaAs Camera

Cited by 8 publications

References 27 publications

Three-Dimensional Morphology and Size Measurement of High-Temperature Metal Components Based on Machine Vision Technology: A Review

Three-Dimensional Morphology and Size Measurement of High-Temperature Metal Components Based on Machine Vision Technology: A Review

Real-Time 3D Reconstruction Method Based on Monocular Vision

Indium composition effects on extended short-wave infrared photodetector performance

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