A Quantitative Investigation of the Effect of Scan Planning and Multi-Technology Fusion for Point Cloud Data Collection on Registration and Data Quality: A Case Study of Bond University’s Sustainable Building
The construction industry requires comprehensive and accurate as-built information for a variety of applications, including building renovations, historic building preservation and structural health monitoring. Reality capture technology facilitates the recording of as-built information in the form...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-06-01
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| Series: | Buildings |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-5309/13/6/1473 |
| _version_ | 1797595690562486272 |
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| author | Zicheng Zhu Tianzhuo Chen Steve Rowlinson Rosemarie Rusch Xianhu Ruan |
| author_facet | Zicheng Zhu Tianzhuo Chen Steve Rowlinson Rosemarie Rusch Xianhu Ruan |
| author_sort | Zicheng Zhu |
| collection | DOAJ |
| description | The construction industry requires comprehensive and accurate as-built information for a variety of applications, including building renovations, historic building preservation and structural health monitoring. Reality capture technology facilitates the recording of as-built information in the form of point clouds. However, the emerging development trends of scan planning and multi-technology fusion in point cloud acquisition methods have not been adequately addressed in research regarding their effects on point cloud registration quality and data quality in the built environment. This study aims to extensively investigate the impact of scan planning and multi-technology fusion on point cloud registration and data quality. Registration quality is evaluated using registration error (RE) and scan overlap rate (SOR), representing registration accuracy and registration coincidence rate, respectively. Conversely, data quality is assessed using point error (PE) and coverage rate (CR), which denote data accuracy and data completeness. Additionally, this study proposes a voxel centroid approach and the PCP rate to calculate and optimize the CR, tackling the industry’s challenge of quantifying point cloud completeness. |
| first_indexed | 2024-03-11T02:39:53Z |
| format | Article |
| id | doaj.art-92c8cd696ee047d5bc12caca6d5ba6d2 |
| institution | Directory Open Access Journal |
| issn | 2075-5309 |
| language | English |
| last_indexed | 2024-03-11T02:39:53Z |
| publishDate | 2023-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Buildings |
| spelling | doaj.art-92c8cd696ee047d5bc12caca6d5ba6d22023-11-18T09:38:47ZengMDPI AGBuildings2075-53092023-06-01136147310.3390/buildings13061473A Quantitative Investigation of the Effect of Scan Planning and Multi-Technology Fusion for Point Cloud Data Collection on Registration and Data Quality: A Case Study of Bond University’s Sustainable BuildingZicheng Zhu0Tianzhuo Chen1Steve Rowlinson2Rosemarie Rusch3Xianhu Ruan4Faculty of Society & Design, Bond University, Robina, Gold Coast 4226, AustraliaFaculty of Society & Design, Bond University, Robina, Gold Coast 4226, AustraliaCentre for Comparative Construction Research, Bond University, Robina, Gold Coast 4226, AustraliaFaculty of Society & Design, Bond University, Robina, Gold Coast 4226, AustraliaSchool of Civil Engineering, Chongqing Jiaotong University, Chongqing 400074, ChinaThe construction industry requires comprehensive and accurate as-built information for a variety of applications, including building renovations, historic building preservation and structural health monitoring. Reality capture technology facilitates the recording of as-built information in the form of point clouds. However, the emerging development trends of scan planning and multi-technology fusion in point cloud acquisition methods have not been adequately addressed in research regarding their effects on point cloud registration quality and data quality in the built environment. This study aims to extensively investigate the impact of scan planning and multi-technology fusion on point cloud registration and data quality. Registration quality is evaluated using registration error (RE) and scan overlap rate (SOR), representing registration accuracy and registration coincidence rate, respectively. Conversely, data quality is assessed using point error (PE) and coverage rate (CR), which denote data accuracy and data completeness. Additionally, this study proposes a voxel centroid approach and the PCP rate to calculate and optimize the CR, tackling the industry’s challenge of quantifying point cloud completeness.https://www.mdpi.com/2075-5309/13/6/1473reality capturepoint cloud datadata qualityregistration qualitylaser scanningdigital photogrammetry |
| spellingShingle | Zicheng Zhu Tianzhuo Chen Steve Rowlinson Rosemarie Rusch Xianhu Ruan A Quantitative Investigation of the Effect of Scan Planning and Multi-Technology Fusion for Point Cloud Data Collection on Registration and Data Quality: A Case Study of Bond University’s Sustainable Building Buildings reality capture point cloud data data quality registration quality laser scanning digital photogrammetry |
| title | A Quantitative Investigation of the Effect of Scan Planning and Multi-Technology Fusion for Point Cloud Data Collection on Registration and Data Quality: A Case Study of Bond University’s Sustainable Building |
| title_full | A Quantitative Investigation of the Effect of Scan Planning and Multi-Technology Fusion for Point Cloud Data Collection on Registration and Data Quality: A Case Study of Bond University’s Sustainable Building |
| title_fullStr | A Quantitative Investigation of the Effect of Scan Planning and Multi-Technology Fusion for Point Cloud Data Collection on Registration and Data Quality: A Case Study of Bond University’s Sustainable Building |
| title_full_unstemmed | A Quantitative Investigation of the Effect of Scan Planning and Multi-Technology Fusion for Point Cloud Data Collection on Registration and Data Quality: A Case Study of Bond University’s Sustainable Building |
| title_short | A Quantitative Investigation of the Effect of Scan Planning and Multi-Technology Fusion for Point Cloud Data Collection on Registration and Data Quality: A Case Study of Bond University’s Sustainable Building |
| title_sort | quantitative investigation of the effect of scan planning and multi technology fusion for point cloud data collection on registration and data quality a case study of bond university s sustainable building |
| topic | reality capture point cloud data data quality registration quality laser scanning digital photogrammetry |
| url | https://www.mdpi.com/2075-5309/13/6/1473 |
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