Deep learning enabled single-shot absolute phase recovery in high-speed composite fringe pattern profilometry of separated objects
딥 러닝은 물체를 분리하는 고속 복합 줄무늬 모드 윤곽술에서의 단일 절대 위상 회복을 가능하게 한다
El aprendizaje profundo hace posible la recuperación de fase absoluta única en la silueta de modo rayado compuesto de alta velocidad de objetos separados
L'apprentissage en profondeur permet une récupération de phase absolue unique en contournage à grande vitesse en mode strié composite d'objets séparés
Глубокое обучение делает возможным однократное абсолютное восстановление фазы в высокоскоростном композитном полосовом режиме для отдельных объектов
Maciej Trusiak, Malgorzata Kujawinska
Institute of Micromechanics and Photonics, Warsaw University of Technology, 8 Sw. A. Boboli Street, Warsaw 02-525, Poland
Opto-Electronic Advances, 12 December 2023

A recent article in the Opto-Electronic Advances (OEA) journal from Prof. Qian Chen and Prof. Chao Zuo’s group introduced a new and efficient 3D imaging system that captures high-speed images using deep learning-enabled fringe projection profilometry (FPP).

In this News & Views article, we explore potential avenues for future advancements, including expanding the measurement range through an extended number-theoretical approach, enhancing quality through the incorporation of horizontal fringes, and integrating data from other modalities to broaden the system's applications.
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