  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.
