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.

引用

页数：5

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