.png){kind=icon}
返回
A target-free video structural motion estimation method based on multi-path optimization
.png){kind=icon}
PRE
AI
DOI：10.1016/j.ymssp.2023.110452.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The vibration data are quite important for structural health monitoring (SHM). This paper proposed a novel method, to adaptively estimate video motions of the structure in subpixel accuracy, without attaching any targets. The proposed method includes three steps. In the first step, to remove outliers and simultaneously preserve feature points, the Gaussian range kernel is used along with the Gaussian spatial kernel, and calculated by the polynomial fitting and recursive integrals computing. In the second step, to calculate video pixel motions varied with spatial coordinates in the region of interest (ROI) for testing, the ROI is divided into multiple grid cells. Motions in each grid cell are modeled as local spatially-variant homography matrices, and their spatial consistency are enhanced by a shape-preserving constraint. The third step is to enhance both spatial and temporal correlations of the calculated homography matrices, achieved by the data term and the smoothness term in both space and time domains. The superiority of the proposed method over traditional methods was validated in several case studies for analyzing structural motions. Among the comparisons, the proposed method can produce image denoising, camera motions, structural motions, and structural modal information in subpixel accuracy, and with the best accuracy.
Keyword:
Structural motion estimation
Camera motion estimation
video signal processing
Target-free
Multi-path optimization
期刊
IF:
8.9
论文数:
1.3W
被引数:
6.6W
机构
引用论文
.png){kind=icon}
A framework for quantifying the value of vibration-based structural health monitoring基于振动的结构健康监测价值量化框架
OAAI
OAAI分享收藏
查看更多内容