Deep-learning-enabled dual-frequency composite fringe projection profilometry for single-shot absolute 3D shape measurement

Yixuan Li, Smart Computational Imaging (SCI) Laboratory, Nanjing University of Science and Technology, Nanjing 210094, China, Jiaming Qian, Shijie Feng, Qian Chen, Chao Zuo, Jiangsu Key Laboratory of Spectral Imaging & Intelligent Sense, Nanjing University of Science and Technology, Nanjing 210094, China
2020 Opto-Electronic Advances  
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
more » ... liasing 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.
doi:10.29026/oea.2022.210021 fatcat:ddfczoourbf47pa6gsucalry6m