Real-time displacement monitoring using camera video records with camera motion correction

被引:2
|
作者
Yi, Zhuoran [1 ]
Cao, Miao [2 ]
Kito, Yuya [2 ]
Sato, Gota [2 ]
Zhang, Xuan [2 ,3 ]
Xie, Liyu [1 ]
Xue, Songtao [1 ,2 ]
机构
[1] Tongji Univ, Dept Disaster Mitigat Struct, Shanghai 200092, Peoples R China
[2] Tohoku Inst Technol, Dept Architecture, Sendai 9828577, Japan
[3] Shandong Univ Sci & Technol, Coll Engn & Architecture, Qingdao 266590, Peoples R China
基金
中国国家自然科学基金;
关键词
Story drift; SHM system; Structure from Motion; Camera motion correction; Shaking table test; DAMAGE ASSESSMENT; SENSOR; IDENTIFICATION; BOUNDARY; MODEL;
D O I
10.1016/j.measurement.2024.114406
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Structure from Motion (SfM) method can reconstruct the story drift ratio, but the camera motion produced by earthquakes reduces the measuring accuracy. This paper improves the applicability of the traditional method by correcting camera motion according to the identification of translation and rotation of camera. Experiments at different levels are designed to prove the proposed method. First, one set of experiments proves the motion correction method by the Single-degree-of-freedom (SDOF) system. The error of maximum response is 4.5% for the case with less rotation. As for the camera motion with larger rotation, the average error increases to 7.9%, which still meets the practical utilization. After that, the accuracy of using SfM method is confirmed by the Multi-degree-of-freedom (MDOF) system with the average error of 4.9%. This paper is expected to extend approaches for the application of the SfM method in the case of huge earthquakes.
引用
收藏
页数:10
相关论文
共 50 条
  • [31] Abnormal Motion Detection in a Real-Time Smart Camera System
    Tehrani, Mona Akbarniai
    Kleihorst, Richard
    Meijer, Peter
    Spaanenburg, Lambert
    2009 THIRD ACM/IEEE INTERNATIONAL CONFERENCE ON DISTRIBUTED SMART CAMERAS, 2009, : 410 - +
  • [32] Beach Wrack Dynamics Using a Camera Trap as the Real-Time Monitoring Tool
    Pan, Yaoru
    Ayoub, Naeem
    Schneider-Kamp, Peter
    Flindt, Mogens
    Holmer, Marianne
    FRONTIERS IN MARINE SCIENCE, 2022, 9
  • [33] A Real-Time Respiration Monitoring and Classification System Using a Depth Camera and Radars
    He, Shan
    Han, Zixiong
    Iglesias, Cristovao
    Mehta, Varun
    Bolic, Miodrag
    FRONTIERS IN PHYSIOLOGY, 2022, 13
  • [34] Egocentric Real-time Workspace Monitoring using an RGB-D Camera
    Damen, Dima
    Gee, Andrew
    Mayol-Cuevas, Walterio
    Calway, Andrew
    2012 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2012, : 1029 - 1036
  • [35] Camera fusion for real-time temperature monitoring of neonates using deep learning
    Lyra, Simon
    Rixen, Joeran
    Heimann, Konrad
    Karthik, Srinivasa
    Joseph, Jayaraj
    Jayaraman, Kumutha
    Orlikowsky, Thorsten
    Sivaprakasam, Mohanasankar
    Leonhardt, Steffen
    Hoog Antink, Christoph
    MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING, 2022, 60 (06) : 1787 - 1800
  • [36] Real-time monitoring of maize phenology using ground camera fusion information
    Zhao, Qi
    Qu, Yonghua
    Liu, Dongyi
    SMART AGRICULTURAL TECHNOLOGY, 2025, 10
  • [37] Real-time camera motion tracking in planar view scenarios
    Alvarez, Luis
    Gomez, Luis
    Henriquez, Pedro
    Sanchez, Javier
    JOURNAL OF REAL-TIME IMAGE PROCESSING, 2016, 11 (02) : 287 - 299
  • [38] Real-time holographic camera
    Stolyarenko, A
    INTERNATIONAL CONFERENCE ON OPTICAL HOLOGRAPHY AND ITS APPLICATIONS, 1998, 3486 : 32 - 36
  • [39] An Intelligent Real-Time Occupancy Monitoring System Using Single Overhead Camera
    Ahmad, Jawad
    Larijani, Hadi
    Emmanuel, Rohinton
    Mannion, Mike
    Javed, Abbas
    INTELLIGENT SYSTEMS AND APPLICATIONS, INTELLISYS, VOL 2, 2019, 869 : 957 - 969
  • [40] Precise real-time correction of Anger camera deadtime losses
    Woldeselassie, T
    MEDICAL PHYSICS, 2002, 29 (07) : 1599 - 1610