TY - GEN
T1 - Dense 3D displacement and strain measurement framework of miter gates using computer vision
AU - Narazaki, Yasutaka
AU - Hoskere, Vedhus
AU - Spencer, Billie F.
AU - Foltz, Stuart
AU - Smith, Matthew D.
PY - 2019
Y1 - 2019
N2 - This paper investigates the framework of vision-based dense 3D displacement and strain measurement using a digital camera. The framework has three components: (i) Estimation of 3D displacement and strain from images before and after deformation (water-fill event), (ii) evaluation of the expected accuracy of the measurement, and (iii) selection of the measurement setting with the highest expected accuracy. The framework first estimates the full-field optical flow between the images before and after water-fill event, and project the flow to the finite element (FE) model to estimate the 3D displacement and strain. Then, the expected displacement/strain estimation accuracy is evaluated at each node/element of the FE model. Finally, methods and measurement settings with the highest expected accuracy are selected to achieve the best results from the field measurement. Physics-based graphics model (PBGM) is used effectively to simulate the vision-based measurements in a photo-realistic environment and evaluate the performance of different methods and measurement settings by comparing the estimated values with the ground-truth values. The framework investigated in this paper can be used to analyze and optimize the performance of the measurement with different camera placement and post-processing steps prior to the field test.
AB - This paper investigates the framework of vision-based dense 3D displacement and strain measurement using a digital camera. The framework has three components: (i) Estimation of 3D displacement and strain from images before and after deformation (water-fill event), (ii) evaluation of the expected accuracy of the measurement, and (iii) selection of the measurement setting with the highest expected accuracy. The framework first estimates the full-field optical flow between the images before and after water-fill event, and project the flow to the finite element (FE) model to estimate the 3D displacement and strain. Then, the expected displacement/strain estimation accuracy is evaluated at each node/element of the FE model. Finally, methods and measurement settings with the highest expected accuracy are selected to achieve the best results from the field measurement. Physics-based graphics model (PBGM) is used effectively to simulate the vision-based measurements in a photo-realistic environment and evaluate the performance of different methods and measurement settings by comparing the estimated values with the ground-truth values. The framework investigated in this paper can be used to analyze and optimize the performance of the measurement with different camera placement and post-processing steps prior to the field test.
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U2 - 10.12783/shm2019/32462
DO - 10.12783/shm2019/32462
M3 - Conference contribution
AN - SCOPUS:85074270378
T3 - Structural Health Monitoring 2019: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT) - Proceedings of the 12th International Workshop on Structural Health Monitoring
SP - 3065
EP - 3072
BT - Structural Health Monitoring 2019
A2 - Chang, Fu-Kuo
A2 - Guemes, Alfredo
A2 - Kopsaftopoulos, Fotis
PB - DEStech Publications Inc.
T2 - 12th International Workshop on Structural Health Monitoring: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT), IWSHM 2019
Y2 - 10 September 2019 through 12 September 2019
ER -