Marker-Based Structural Displacement Measurement Models with Camera Movement Error Correction Using Image Matching and Anomaly Detection
To prevent collapse accidents at construction sites, the marker-based displacement measurement method was developed. However, it has difficulty in obtaining accurate measurements at long distances (>50 m) in an outdoor environment because of camera movements. To overcome this problem, marker-base...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-10-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/20/19/5676 |
| _version_ | 1827704833479540736 |
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| author | Jisung Kim Youngdo Jeong Hyojin Lee Hongsik Yun |
| author_facet | Jisung Kim Youngdo Jeong Hyojin Lee Hongsik Yun |
| author_sort | Jisung Kim |
| collection | DOAJ |
| description | To prevent collapse accidents at construction sites, the marker-based displacement measurement method was developed. However, it has difficulty in obtaining accurate measurements at long distances (>50 m) in an outdoor environment because of camera movements. To overcome this problem, marker-based structural displacement measurement models using image matching and anomaly detection were designed in this study. Then, the performance of each model in terms of camera movement error correction was verified through comparison with that of a conventional model. The results show that the systematic errors due to camera movements (<1.7°) were corrected. The detection rate of markers with displacement reached 95%, and the probability that the error size would be less than 10 mm was ≥ 95% with a 95% confidence interval at a distance of more than 100 m. Moreover, the normalized mean square error was less than 0.1. The models developed in this study can measure the pure displacement of an object without the systematic errors caused by camera movements. Furthermore, these models can be used to measure the displacements of distant structures using closed-circuit television cameras and markers in an outdoor environment with high accuracy. |
| first_indexed | 2024-03-10T15:50:42Z |
| format | Article |
| id | doaj.art-69938014166443f59aa07844ffae1f0f |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T15:50:42Z |
| publishDate | 2020-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-69938014166443f59aa07844ffae1f0f2023-11-20T16:06:03ZengMDPI AGSensors1424-82202020-10-012019567610.3390/s20195676Marker-Based Structural Displacement Measurement Models with Camera Movement Error Correction Using Image Matching and Anomaly DetectionJisung Kim0Youngdo Jeong1Hyojin Lee2Hongsik Yun3School of Civil, Architectural Engineering & Landscape Architecture, Sungkyunkwan University, Suwon 16419, KoreaInfra Research Group, R&D Center, POSCO E&C, Incheon 21985, KoreaInstitute of Geographic & Environmental Technology, GEOMEXSOFT Ltd., Chuncheon 24461, KoreaSchool of Civil, Architectural Engineering & Landscape Architecture, Sungkyunkwan University, Suwon 16419, KoreaTo prevent collapse accidents at construction sites, the marker-based displacement measurement method was developed. However, it has difficulty in obtaining accurate measurements at long distances (>50 m) in an outdoor environment because of camera movements. To overcome this problem, marker-based structural displacement measurement models using image matching and anomaly detection were designed in this study. Then, the performance of each model in terms of camera movement error correction was verified through comparison with that of a conventional model. The results show that the systematic errors due to camera movements (<1.7°) were corrected. The detection rate of markers with displacement reached 95%, and the probability that the error size would be less than 10 mm was ≥ 95% with a 95% confidence interval at a distance of more than 100 m. Moreover, the normalized mean square error was less than 0.1. The models developed in this study can measure the pure displacement of an object without the systematic errors caused by camera movements. Furthermore, these models can be used to measure the displacements of distant structures using closed-circuit television cameras and markers in an outdoor environment with high accuracy.https://www.mdpi.com/1424-8220/20/19/5676camera movement errorimage matchinganomaly detectionmarker-based displacement measurementerror correction |
| spellingShingle | Jisung Kim Youngdo Jeong Hyojin Lee Hongsik Yun Marker-Based Structural Displacement Measurement Models with Camera Movement Error Correction Using Image Matching and Anomaly Detection Sensors camera movement error image matching anomaly detection marker-based displacement measurement error correction |
| title | Marker-Based Structural Displacement Measurement Models with Camera Movement Error Correction Using Image Matching and Anomaly Detection |
| title_full | Marker-Based Structural Displacement Measurement Models with Camera Movement Error Correction Using Image Matching and Anomaly Detection |
| title_fullStr | Marker-Based Structural Displacement Measurement Models with Camera Movement Error Correction Using Image Matching and Anomaly Detection |
| title_full_unstemmed | Marker-Based Structural Displacement Measurement Models with Camera Movement Error Correction Using Image Matching and Anomaly Detection |
| title_short | Marker-Based Structural Displacement Measurement Models with Camera Movement Error Correction Using Image Matching and Anomaly Detection |
| title_sort | marker based structural displacement measurement models with camera movement error correction using image matching and anomaly detection |
| topic | camera movement error image matching anomaly detection marker-based displacement measurement error correction |
| url | https://www.mdpi.com/1424-8220/20/19/5676 |
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