学术前沿|基于深度学习的高分辨率100k帧每秒条纹投影轮廓测量技术(Accelerating fringe projection profilometry to 100k fps at high-resolution using deep learning)

类型:

内容转述

来源:

Light: Science & Applications

发布时间:

2025-03-27

资讯来源(SourceLight: Science & Applications

研究团队(AuthorsJie XuJindong Tian

发表时间(Published20250327

文献DOI10.1038/s41377-025-01894-9

原文链接(Linkhttps://www.nature.com/articles/s41377-025-01802-4

核心研究进展(Core Research Progress

条纹投影轮廓测量技术(Fringe Projection Profilometry, FPP)广泛应用于三维成像(3D Imaging)与精密测量领域,普遍存在速度与精度难以兼顾的问题。该研究利用深度学习算法优化FPP技术,在保留高分辨率的同时,将成像帧率提升至100k fps,突破传统三维测量的速度瓶颈。

 

技术应用价值(Technical Application Value

该深度学习赋能方案兼顾超高帧率与高精度,可捕捉传统设备无法识别的瞬态动态场景,大幅拓宽FPP技术应用范围。适用于超快动态三维测量、工业高速精密检测等场景,为高速高精度三维感知技术提供全新优化思路。

 

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