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 (PMM) is one of the techniques to magnify the motion in target frequency bands and identify system dynamics. Optical flow (OF) 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.