During construction, continuous monitoring of underground tunnels can
mitigate potential hazards and facilitate an in-depth understanding of the
ground-tunnel interaction behavior. Traditional vision-based monitoring can
directly capture an extensive range of motion but cannot separate the tunnel's
vibration and deformation mode. Phase-based motion magnification is one of the
techniques to magnify the motion in target frequency bands and identify system
dynamics. Optical flow is a popular method of calculating the motion of image
intensities in computer vision and has a much lower computational cost than
Digital Image Correlation. This study combines PMM and OF to quantify the
underground tunnel scene's magnified deformation mode pixel displacements. As
motion magnification artifacts may lead to inaccurate quantification, the 2D
Wiener filter is used to smooth the high-frequency content. With GPU
acceleration, a dense OF algorithm computing each pixel's displacement is
adopted to derive the whole scene motion. A validation experiment is conducted
between the amplification motion and the actual motion of prisms preinstalled
in the tunnel.

通过结合位相移动放大技术和光流法，本研究定量化地测量了地下隧道场景中被放大的变形模式像素位移。利用 2D Wiener 滤波器平滑高频内容以减少运动放大产生的错误量化，并采用 GPU 加速的稠密光流算法计算整个场景的运动。通过验证实验与预安装在隧道中的棱柱的实际运动进行对比分析。