Visualizing and quantifying small and nonstationary structural motions in video measurement

Rapid advancement in vision recording technologies is increasing the importance and production of video data in a wide range of applications. This paper proposed a novel perspective of multifrequency phase inference for characterizing especially challenging nonstationary and often small motions in o...

Full description

Saved in:
Bibliographic Details
Published in:Computer-aided civil and infrastructure engineering 2023-01, Vol.38 (2), p.135-159
Main Authors: Cai, Enjian, Zhang, Yi, Quek, Ser Tong
Format: Article
Language:English
Subjects:
Dynamic response
Motion simulation
Optical measurement
Phase retrieval
Phase unwrapping
Robustness (mathematics)
Structural health monitoring
Video data
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Rapid advancement in vision recording technologies is increasing the importance and production of video data in a wide range of applications. This paper proposed a novel perspective of multifrequency phase inference for characterizing especially challenging nonstationary and often small motions in optical measurement. The model estimates and adjusts the phase information by the multi‐frequency phase retrieval, which is derived from the maximum likelihood formulation with block matching 3D sparsity priors. Estimated phase jumps are removed by a robust solution of the 2D phase unwrapping problem. These considerations are supported by applications of dynamic response identification in structural health monitoring. When compared to state‐of‐the‐art techniques, the proposed method readily yielded high‐quality magnifications on real videos, with less noise and better anti‐noise performance. The proposed method also demonstrated uniformly high skill in extracting clearer time‐domain motion estimation of video components.
ISSN:1093-9687
1467-8667
DOI:10.1111/mice.12894