摘要
Single-shot high-speed 3D imaging is important for reconstructions of dynamic objects.For fringe projection profilometry(FPP),however,it is still challenging to recover accurate 3D shapes of isolated objects by a single fringe image.In this paper,we demonstrate that the deep neural networks can be trained to directly recover the absolute phase from a unique fringe image that involves spatially multiplexed fringe patterns of different frequencies.The extracted phase is free from spectrum-aliasing problem which is hard to avoid for traditional spatial-multiplexing methods.Experiments on both static and dynamic scenes show that the proposed approach is robust to object motion and can obtain high-quality 3D reconstructions of isolated objects within a single fringe image.
基金
This work was supported by National Natural Science Foundation of China(62075096,62005121,U21B2033)
Leading Technology of Jiangsu Basic Research Plan(BK20192003)
“333 Engineering”Research Project of Jiangsu Province(BRA2016407)
Jiangsu Provincial“One belt and one road”innovation cooperation project(BZ2020007)
Fundamental Research Funds for the Central Universities(30921011208,30919011222,30920032101)
Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX21_0273)
Open Research Fund of Jiangsu Key Laboratory of Spectral Imaging&Intelligent Sense(JSGP202105).
