scholarly journals A Novel Approach for 3D-Structural Identification through Video Recording: Magnified Tracking

Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 1229 ◽  
Author(s):  
Yunus Harmanci ◽  
Utku Gülan ◽  
Markus Holzner ◽  
Eleni Chatzi
Keyword(s):  
Computer Vision ◽  
Motion Tracking ◽  
Video Recording ◽  
Video Camera ◽  
Diagnostic Techniques ◽  
Modal Identification ◽  
Spatial Density ◽  
Operational Conditions ◽  
Novel Approach ◽  
Motion Magnification

Advancements in optical imaging devices and computer vision algorithms allow the exploration of novel diagnostic techniques for use within engineering systems. A recent field of application lies in the adoption of such devices for non-contact vibrational response recordings of structures, allowing high spatial density measurements without the burden of heavy cabling associated with conventional technologies. This, however, is not a straightforward task due to the typically low-amplitude displacement response of structures under ambient operational conditions. A novel framework, namely Magnified Tracking (MT), is proposed herein to overcome this limitation through the synergistic use of two computer vision techniques. The recently proposed phase-based motion magnification (PBMM) framework, for amplifying motion in a video within a defined frequency band, is coupled with motion tracking by means of particle tracking velocimetry (PTV). An experimental campaign was conducted to validate a proof-of-concept, where the dynamic response of a shear frame was measured both by conventional sensors as well as a video camera setup, and cross-compared to prove the feasibility of the proposed non-contact approach. The methodology was explored both in 2D and 3D configurations, with PTV revealing a powerful tool for the measurement of perceptible motion. When MT is utilized for tracking “imperceptible” structural responses (i.e., below PTV sensitivity), via the use of PBMM around the resonant frequencies of the structure, the amplified motion reveals the operational deflection shapes, which are otherwise intractable. The modal results extracted from the magnified videos, using PTV, demonstrate MT to be a viable non-contact alternative for 3D modal identification with the benefit of a spatially dense measurement grid.

scholarly journals Computer Vision Aided Structural Identification: Feature Tracking Using Particle Tracking Velocimetry versus Optical Flow

Proceedings ◽  
2018 ◽  
Vol 4 (1) ◽  
pp. 33 ◽  
Author(s):  
Yunus Emre Harmanci ◽  
Zhilu Lai ◽  
Utku Gülan ◽  
Markus Holzner ◽  
Eleni Chatzi
Keyword(s):  
Computer Vision ◽  
Optical Flow ◽  
Particle Tracking ◽  
Particle Tracking Velocimetry ◽  
Large Scale ◽  
Video Recording ◽  
Structural Features ◽  
Spatial Density ◽  
Motion Magnification ◽  
Shear Frame

Recent advances in computer vision techniques allow to obtain information on the dynamic behaviour of structures using commercial grade video recording devices. The advantage of such schemes lies in the non-invasive nature of video recording and the ability to extract information at a high spatial density utilizing structural features. This creates an advantage over conventional contact sensors since constraints such as cabling and maximum channel availability are alleviated. In this study, two such schemes are explored, namely Particle Tracking Velocimetry (PTV) and the optical flow algorithm. Both are validated against conventional sensors for a lab-scale shear frame and compared. In cases of imperceptible motion, the recently proposed Phase-based Motion Magnification (PBMM) technique is employed to obtain modal information within frequency bands of interest and further used for modal analysis. The optical flow scheme combined with (PBMM) is further tested on a large-scale post-tensioned concrete beam and validated against conventional measurements, as a transition from lab- to outdoor field applications.

scholarly journals Calving of Fuerza Aérea Glacier (Greenwich Island, Antarctica) observed with terrestrial laser scanning and continuous video monitoring

2016 ◽  
Vol 62 (235) ◽  
pp. 835-846 ◽  
Author(s):  
MICHAŁ PĘTLICKI ◽  
CHRISTOPHE KINNARD
Keyword(s):  
Laser Scanning ◽  
Video Recording ◽  
Terrestrial Laser Scanning ◽  
Video Camera ◽  
South Shetland Islands ◽  
High Temporal Resolution ◽  
Ice Flow ◽  
Quantitative Measurements ◽  
Short Period ◽  
Combination Of Methods

ABSTRACTA short-term series of quantitative observations of calving activity of Fuerza Aérea Glacier (Greenwich Island, the South Shetland Islands, Antarctica) was conducted in order to test new methods of monitoring calving. The volume of single calving events was quantified by combining terrestrial laser scanning (TLS) surveys with continuous video recording of the ice front. An empirical formula for area/volume scaling of the calved ice block was proposed based on the TLS measured calved ice volume and the calved ice front area obtained by manual delineation on the images acquired with the video camera. This combination of methods proves to be a valuable tool for glacier monitoring, providing both high-temporal resolution and precise quantitative measurements of the calving volume. The size distribution of calving events is best approximated by a power law and within the short period of observations (14 d) calving was found to be an intrinsic process not dependent on environmental forcings. Over the period of 21 January–04 February 2013 the ice flow velocity at the terminus of Fuerza Aérea Glacier was 0.26 ± 0.07 m d−1and the calving rate was 0.41 ± 0.07 m d−1.

scholarly journals Evaluation of the SteamVR Motion Tracking System with a Custom-Made Tracker

2021 ◽  
Vol 11 (14) ◽  
pp. 6390
Author(s):  
Marcin Maciejewski
Keyword(s):  
Motion Tracking ◽  
Tracking System ◽  
Training System ◽  
Random Errors ◽  
Operational Conditions ◽  
Custom Made ◽  
Systematic And Random Errors ◽  
Position And Orientation ◽  
Motion Tracking System ◽  
System Operating

The paper presents the research of the SteamVR tracker developed for a man-portable air-defence training system. The tests were carried out in laboratory conditions, with the tracker placed on the launcher model along with elements ensuring the faithful reproduction of operational conditions. During the measurements, the static tracker was moved and rotated in a working area. The range of translations and rotations corresponded to the typical requirements of a shooting simulator application. The results containing the registered position and orientation values were plotted on 3D charts which showed the tracker’s operation. Further analyses determined the values of the systematic and random errors for measurements of the SteamVR system operating with a custom-made tracker. The obtained results with random errors of 0.15 mm and 0.008° for position and orientation, respectively, proved the high precision of the measurements.

scholarly journals A new automated procedure of modal identification in operational conditions

2018 ◽  
Vol 211 ◽  
pp. 21003 ◽  
Author(s):  
Gabriele Marrongelli ◽  
Carmelo Gentile
Keyword(s):  
Parametric Identification ◽  
Modal Identification ◽  
Mode Shapes ◽  
Parameter Estimates ◽  
Reference List ◽  
Modal Parameter ◽  
Operational Conditions ◽  
Historic Masonry ◽  
Stabilization Diagram ◽  
Using Data

Structural Health Monitoring (SHM) strategies are aimed at the assessment of structural performance, using data acquired by sensing systems. Among the different available approaches, vibration-based methods - involving the automation of the modal parameter estimation (MPE) and modal tracking (MT) procedures - are receiving increasing attention. In the context of vibration-based monitoring, this paper presents an automated procedure of modal identification in operational conditions. The presented algorithms can be used to effectively manage the results obtained by any parametric identification method that involves the construction and the interpretation of stabilization diagrams. The implemented approach introduces improvements related to both the MPE and the MT tasks. The MPE procedure consists of three key steps aimed at: (1) filtering a high number of spurious poles in the stabilization diagram; (2) clustering the remaining poles that share same characteristics in term of modal parameters; (3) improving the accuracy of the modal parameter estimates. In the MT procedure the use of a simple statistical approach to define adaptive thresholds together with continuously updated dynamic reference list guarantee an efficient tracking of the most representative structural modes. The advantages obtained through the proposed procedures are exemplified using data continuously collected on the historic masonry tower of San Gottardo in Corte, located in the centre of Milan, Italy. In addition, the ability of the automated algorithms to identify contributions inherent to different vibration modes, even if they are characterized by closely-spaced frequencies and a low discriminant between mode shapes, will be described in details.

scholarly journals Speech Acts Analysis on Teaching and Learning Process Used by the Teacher in MAN 2 Mataram in Academic Year 2016-2017

2019 ◽  
Vol 5 (1) ◽  
pp. 46
Author(s):  
Yulia Isnaini
Keyword(s):  
Learning Process ◽  
Speech Acts ◽  
Teaching And Learning ◽  
Speech Act ◽  
Video Recording ◽  
Video Camera ◽  
Coding System ◽  
Perlocutionary Act ◽  
Academic Year ◽  
Research Show

This study was aimed at finding out Speech Acts Analysis on Teaching andLearning Process used by the Teacher in MAN 2 Mataram in Academic year 2016/2017. The method of this research is qualitative research The data of this research were the utterances performed by the Teachers of MAN 2 Mataram. The research instrument was the researcher himself. Participant is the subject from which the data obtained (Arikunto, 2010: 172)The Researcher’s participant actively classification speech act by the Teachers on teaching and learning process.T he instrument of data by using video camera and observation. To analyze the data Based on Louis (2005:181). This study used observation and video recording as an instrument of data collection, the researcher applied coding system. In this research, there are two validity principles applied by the researcher. The results of the research show that there are three classifications of speech act performed by the Teachers in the aching and learning process . The results of the research show that there are three classification of speech act performed by the Teachers in the aching and learning process. they are 4 data of locutionary act , 30 data of Illucotionary act, 7 data of Perlocutionary act . So the total of data were 41 data of speech act are used By the Teachers in MAN 2 Mataram.

scholarly journals Automated band selection for Bayesian FFT modal identification Based on RetinaNet

2021 ◽  
Vol 2078 (1) ◽  
pp. 012058
Author(s):  
Chen Wang ◽  
Zhilin Xue ◽  
Yipeng Su ◽  
Binbin Li
Keyword(s):  
Operation Time ◽  
Modal Identification ◽  
Ambient Vibration ◽  
Mode Shapes ◽  
Band Selection ◽  
Data Sets ◽  
Civil Structures ◽  
Frequency Bands ◽  
Operational Conditions ◽  
Vibration Data

Abstract Bayesian FFT algorithm is a popular method to identify modal parameters, e.g., modal frequencies, damping ratios, and mode shapes, of civil structures under operational conditions. It is efficient and provides the identification uncertainty in terms of posterior distribution. However, in utilizing the Bayesian FFT algorithm, it is tedious to manually select frequency bands and initial frequencies. This step requires professional knowledge and costs most of time, which prevents the automation of Bayesian FFT algorithm. Regarding the band selection as an object detection problem, we design a band selection network based on the RetinaNet to automatically select frequency bands and a peak prediction network to predict the initial frequencies. The designed networks are trained using the singular value spectrum of measured ambient vibration data and verified by various data sets. It can achieve the human accuracy with much less operation time, and thus provides a corner stone for the automation of Bayesian FFT algorithm.

scholarly journals A Novel Approach of Traffic Density Estimation Using CNNs and Computer Vision

2021 ◽  
Vol 5 (4) ◽  
pp. 80-84
Author(s):  
Luong Anh Tuan Nguyen ◽  
Thanh Xuan Ha
Keyword(s):  
Neural Networks ◽  
Computer Vision ◽  
Traffic Flow ◽  
Density Estimation ◽  
Traffic Density ◽  
Signal Control ◽  
Traffic Signal Control ◽  
Modern Life ◽  
Traffic Jam ◽  
Novel Approach

In modern life, we face many problems, one of which is the increasingly serious traffic jam. The cause is the large volume of vehicles, inadequate infrastructure and unreasonable distribution, and ineffective traffic signal control. This requires finding methods to optimize traffic flow, especially during peak hours. To optimize traffic flow, it is necessary to determine the traffic density at each time in the streets and intersections. This paper proposed a novel approach to traffic density estimation using Convolutional Neural Networks (CNNs) and computer vision. The experimental results with UCSD traffic dataset show that the proposed solution achieved the worst estimation rate of 98.48% and the best estimation rate of 99.01%.

Moving Object Detection and Tracking Based on the Contour Extraction and Centroid Representation

2019 ◽  
pp. 147-157
Author(s):  
Naveenkumar M ◽  
Sriharsha K. V. ◽  
Vadivel A
Keyword(s):  
Object Detection ◽  
Motion Tracking ◽  
Moving Object Detection ◽  
Moving Object ◽  
Absolute Difference ◽  
Contour Extraction ◽  
Object Detection And Tracking ◽  
Detection And Tracking ◽  
Novel Approach ◽  
Extraction Algorithm

This chapter presents a novel approach for moving object detection and tracking based on contour extraction and centroid representation (CECR). Firstly, two consecutive frames are read from the video, and they are converted into grayscale. Next, the absolute difference is calculated between them and the result frame is converted into binary by applying gray threshold technique. The binary frame is segmented using contour extraction algorithm. The centroid representation is used for motion tracking. In the second stage of experiment, initially object is detected by using CECR and motion of each track is estimated by Kalman filter. Experimental results show that the proposed method can robustly detect and track the moving object.

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