Cargando…

An Improved Vision Method for Robust Monitoring of Multi-Point Dynamic Displacements with Smartphones in an Interference Environment

Current research on dynamic displacement measurement based on computer vision mostly requires professional high-speed cameras and an ideal shooting environment to ensure the performance and accuracy of the analysis. However, the high cost of the camera and strict requirements of sharp image contrast...

Descripción completa

Detalles Bibliográficos
Autores principales: Chen, Taicong, Zhou, Zhou
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7589830/
https://www.ncbi.nlm.nih.gov/pubmed/33092260
http://dx.doi.org/10.3390/s20205929
_version_ 1783600669194715136
author Chen, Taicong
Zhou, Zhou
author_facet Chen, Taicong
Zhou, Zhou
author_sort Chen, Taicong
collection PubMed
description Current research on dynamic displacement measurement based on computer vision mostly requires professional high-speed cameras and an ideal shooting environment to ensure the performance and accuracy of the analysis. However, the high cost of the camera and strict requirements of sharp image contrast and stable environment during the shooting process limit the broad application of the technology. This paper proposes an improved vision method to implement multi-point dynamic displacement measurements with smartphones in an interference environment. A motion-enhanced spatio-temporal context (MSTC) algorithm is developed and applied together with the optical flow (OF) algorithm to realize a simultaneous tracking and dynamic displacement extraction of multiple points on a vibrating structure in the interference environment. Finally, a sine-sweep vibration experiment on a cantilever sphere model is presented to validate the feasibility of the proposed method in a wide-band frequency range. In the test, a smartphone was used to shoot the vibration process of the sine-sweep-excited sphere, and illumination change, fog interference, and camera jitter were artificially simulated to represent the interference environment. The results of the proposed method are compared to conventional displacement sensor data and current vision method results. It is demonstrated that, in an interference environment, (1) the OF method is prone to mismatch the feature points and leads to data deviated or lost; (2) the conventional STC method is sensitive to target selection and can effectively track those targets having a large proportion of pixels in the context with motion tendency similar to the target center; (3) the proposed MSTC method, however, can ease the sensitivity to target selection through in-depth processing of the information in the context and finally enhance the robustness of the target tracking. In addition, the MSTC method takes less than one second to track each target between adjacent frame images, implying a potential for online measurement.
format Online
Article
Text
id pubmed-7589830
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-75898302020-10-29 An Improved Vision Method for Robust Monitoring of Multi-Point Dynamic Displacements with Smartphones in an Interference Environment Chen, Taicong Zhou, Zhou Sensors (Basel) Article Current research on dynamic displacement measurement based on computer vision mostly requires professional high-speed cameras and an ideal shooting environment to ensure the performance and accuracy of the analysis. However, the high cost of the camera and strict requirements of sharp image contrast and stable environment during the shooting process limit the broad application of the technology. This paper proposes an improved vision method to implement multi-point dynamic displacement measurements with smartphones in an interference environment. A motion-enhanced spatio-temporal context (MSTC) algorithm is developed and applied together with the optical flow (OF) algorithm to realize a simultaneous tracking and dynamic displacement extraction of multiple points on a vibrating structure in the interference environment. Finally, a sine-sweep vibration experiment on a cantilever sphere model is presented to validate the feasibility of the proposed method in a wide-band frequency range. In the test, a smartphone was used to shoot the vibration process of the sine-sweep-excited sphere, and illumination change, fog interference, and camera jitter were artificially simulated to represent the interference environment. The results of the proposed method are compared to conventional displacement sensor data and current vision method results. It is demonstrated that, in an interference environment, (1) the OF method is prone to mismatch the feature points and leads to data deviated or lost; (2) the conventional STC method is sensitive to target selection and can effectively track those targets having a large proportion of pixels in the context with motion tendency similar to the target center; (3) the proposed MSTC method, however, can ease the sensitivity to target selection through in-depth processing of the information in the context and finally enhance the robustness of the target tracking. In addition, the MSTC method takes less than one second to track each target between adjacent frame images, implying a potential for online measurement. MDPI 2020-10-20 /pmc/articles/PMC7589830/ /pubmed/33092260 http://dx.doi.org/10.3390/s20205929 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Chen, Taicong
Zhou, Zhou
An Improved Vision Method for Robust Monitoring of Multi-Point Dynamic Displacements with Smartphones in an Interference Environment
title An Improved Vision Method for Robust Monitoring of Multi-Point Dynamic Displacements with Smartphones in an Interference Environment
title_full An Improved Vision Method for Robust Monitoring of Multi-Point Dynamic Displacements with Smartphones in an Interference Environment
title_fullStr An Improved Vision Method for Robust Monitoring of Multi-Point Dynamic Displacements with Smartphones in an Interference Environment
title_full_unstemmed An Improved Vision Method for Robust Monitoring of Multi-Point Dynamic Displacements with Smartphones in an Interference Environment
title_short An Improved Vision Method for Robust Monitoring of Multi-Point Dynamic Displacements with Smartphones in an Interference Environment
title_sort improved vision method for robust monitoring of multi-point dynamic displacements with smartphones in an interference environment
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7589830/
https://www.ncbi.nlm.nih.gov/pubmed/33092260
http://dx.doi.org/10.3390/s20205929
work_keys_str_mv AT chentaicong animprovedvisionmethodforrobustmonitoringofmultipointdynamicdisplacementswithsmartphonesinaninterferenceenvironment
AT zhouzhou animprovedvisionmethodforrobustmonitoringofmultipointdynamicdisplacementswithsmartphonesinaninterferenceenvironment
AT chentaicong improvedvisionmethodforrobustmonitoringofmultipointdynamicdisplacementswithsmartphonesinaninterferenceenvironment
AT zhouzhou improvedvisionmethodforrobustmonitoringofmultipointdynamicdisplacementswithsmartphonesinaninterferenceenvironment