Source：Light: Science & Applications

Authors：Jie Xu、Jindong Tian

Published：2025-03-27

DOI：10.1038/s41377-025-01894-9

Link：https://www.nature.com/articles/s41377-025-01802-4

Core Research Progress

Fringe Projection Profilometry (FPP) is widely applied in the fields of 3D imaging and precision measurement. A common challenge of this technique lies in the inherent trade-off between measurement speed and accuracy. This study optimizes FPP via deep learning algorithms. While maintaining high resolution, the imaging frame rate is increased to 100k fps, breaking the speed bottleneck of traditional three-dimensional measurement.

Technical Application Value

This deep learning-enabled solution achieves both ultra-high frame rate and high precision. It can capture transient dynamic scenarios undetectable by conventional equipment, greatly expanding the application scope of Fringe Projection Profilometry (FPP). Suited for ultra-fast dynamic 3D measurement, high-speed precision industrial inspection and other scenarios, it offers a novel optimization approach for high-speed and high-precision 3D sensing technologies.

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