Deformation Monitoring of Tunnel using Phase-based Motion Magnification and Optical Flow

TL;DR

This paper presents a novel approach combining phase-based motion magnification and optical flow, accelerated by GPU, to monitor tunnel deformation accurately during construction, addressing limitations of traditional vision-based methods.

Contribution

It introduces a combined PMM and OF method with filtering and GPU acceleration for precise tunnel deformation monitoring, enhancing existing techniques.

Findings

Effective magnification of tunnel deformation modes

Accurate displacement quantification with filtering and GPU acceleration

Validation confirms method's reliability in real tunnel conditions

Abstract

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.