Deep-learning-enabled temporally super-resolved multiplexed fringe projection profilometry: high-speed kHz 3D imaging with low-speed camera

被引：0
|
作者：
Chen, Wenwu [1 ,2 ,3 ]
Feng, Shijie [1 ,2 ,3 ]
Zuo, Chao [1 ,2 ,3 ]
机构：
[1] Nanjing Univ Sci & Technol, Smart Computat Imaging Lab SCILab, Nanjing, Peoples R China
[2] Nanjing Univ Sci & Technol, Smart Computat Imaging Res Inst SCIRI, Nanjing, Peoples R China
[3] Jiangsu Key Lab Spectral Imaging & Intelligent Se, Nanjing, Peoples R China
来源：
OPTICS AND PHOTONICS FOR ADVANCED DIMENSIONAL METROLOGY III | 2024年 / 12997卷
基金：
中国国家自然科学基金;
关键词：
fringe projection profilometry; multiplex; deep learning; temporal super-resolution;
D O I：
10.1117/12.3016412
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Deep learning-enabled multiplexed fringe projection profilometry allows to achieve high-resolution and highspeed 3D imaging at near-one-order of magnitude-higher 3D frame rate with conventional low-speed cameras. Then the method is demonstrated by measuring 2 transient scenes: rotating fan blades and bullet fired from a toy gun, at kHz using cameras of around 100 Hz.
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页数：5
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