Deep transformer-enhanced dynamic structured light for three-dimensional moving object imaging

Dynamic three-dimensional (3D) shape measurement techniques based on phase-shifting profilometry (PSP) have achieved considerable progress in previous studies. However, for dynamic scenes with arbitrary directional motion, accurately measuring the 3D shape and/or motion of objects remains an unsolved challenge. When an object moves in any direction within 3D space, both its spatial positions and the height values of individual surface points change. Moreover, the height variations at each pixel are typically inconsistent, resulting in different unknown phase-shift errors across various locations. To address the challenge, this paper proposes a PSP dynamic 3D shape measurement method that combines transformer-based motion tracking and motion compensation. We propose to use the COTR network to achieve motion tracking of objects under coded fringe illumination. By integrating this tracking information into the motion error estimation process of PSP, the proposed method enables pixel-wise error compensation, allowing for high-precision recovery of phase information for objects with 3D motion. Experimental results validate the effectiveness of the proposed method, demonstrating a significant reduction in motion-induced errors and improved recovery of true surface geometry.