Hybrid approach for alignment of a pre-processed three-dimensional point cloud, video, and CAD model using partial point cloud in retrofitting applications
Acquiring the three-dimensional point cloud data of a scene using a laser scanner and the alignment of the point cloud data within a real-time video environment view of a camera is a very new concept and is an efficient method for constructing, monitoring, and retrofitting complex engineering models...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2018-03-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/1550147718766452 |
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| _version_ | 1849400549659639808 |
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| author | Ashok Kumar Patil G Ajay Kumar Tae-Hyoung Kim Young Ho Chai |
| author_facet | Ashok Kumar Patil G Ajay Kumar Tae-Hyoung Kim Young Ho Chai |
| author_sort | Ashok Kumar Patil |
| collection | DOAJ |
| description | Acquiring the three-dimensional point cloud data of a scene using a laser scanner and the alignment of the point cloud data within a real-time video environment view of a camera is a very new concept and is an efficient method for constructing, monitoring, and retrofitting complex engineering models in heavy industrial plants. This article presents a novel prototype framework for virtual retrofitting applications. The workflow includes an efficient 4-in-1 alignment, beginning with the coordination of pre-processed three-dimensional point cloud data using a partial point cloud from LiDAR and alignment of the pre-processed point cloud within the video scene using a frame-by-frame registering method. Finally, the proposed approach can be utilized in pre-retrofitting applications by pre-generated three-dimensional computer-aided design models virtually retrofitted with the help of a synchronized point cloud, and a video scene is efficiently visualized using a wearable virtual reality device. The prototype method is demonstrated in a real-world setting, using the partial point cloud from LiDAR, pre-processed point cloud data, and video from a two-dimensional camera. |
| format | Article |
| id | doaj-art-89574051dcf4451fb782c8663d765d0e |
| institution | Kabale University |
| issn | 1550-1477 |
| language | English |
| publishDate | 2018-03-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-89574051dcf4451fb782c8663d765d0e2025-08-20T03:38:01ZengWileyInternational Journal of Distributed Sensor Networks1550-14772018-03-011410.1177/1550147718766452Hybrid approach for alignment of a pre-processed three-dimensional point cloud, video, and CAD model using partial point cloud in retrofitting applicationsAshok Kumar Patil0G Ajay Kumar1Tae-Hyoung Kim2Young Ho Chai3Graduate School of Advanced Imaging Science, Multimedia and Film, Chung-Ang University, Seoul, Republic of KoreaGraduate School of Advanced Imaging Science, Multimedia and Film, Chung-Ang University, Seoul, Republic of KoreaDepartment of Mechanical Engineering, Chung-Ang University, Seoul, Republic of KoreaGraduate School of Advanced Imaging Science, Multimedia and Film, Chung-Ang University, Seoul, Republic of KoreaAcquiring the three-dimensional point cloud data of a scene using a laser scanner and the alignment of the point cloud data within a real-time video environment view of a camera is a very new concept and is an efficient method for constructing, monitoring, and retrofitting complex engineering models in heavy industrial plants. This article presents a novel prototype framework for virtual retrofitting applications. The workflow includes an efficient 4-in-1 alignment, beginning with the coordination of pre-processed three-dimensional point cloud data using a partial point cloud from LiDAR and alignment of the pre-processed point cloud within the video scene using a frame-by-frame registering method. Finally, the proposed approach can be utilized in pre-retrofitting applications by pre-generated three-dimensional computer-aided design models virtually retrofitted with the help of a synchronized point cloud, and a video scene is efficiently visualized using a wearable virtual reality device. The prototype method is demonstrated in a real-world setting, using the partial point cloud from LiDAR, pre-processed point cloud data, and video from a two-dimensional camera.https://doi.org/10.1177/1550147718766452 |
| spellingShingle | Ashok Kumar Patil G Ajay Kumar Tae-Hyoung Kim Young Ho Chai Hybrid approach for alignment of a pre-processed three-dimensional point cloud, video, and CAD model using partial point cloud in retrofitting applications International Journal of Distributed Sensor Networks |
| title | Hybrid approach for alignment of a pre-processed three-dimensional point cloud, video, and CAD model using partial point cloud in retrofitting applications |
| title_full | Hybrid approach for alignment of a pre-processed three-dimensional point cloud, video, and CAD model using partial point cloud in retrofitting applications |
| title_fullStr | Hybrid approach for alignment of a pre-processed three-dimensional point cloud, video, and CAD model using partial point cloud in retrofitting applications |
| title_full_unstemmed | Hybrid approach for alignment of a pre-processed three-dimensional point cloud, video, and CAD model using partial point cloud in retrofitting applications |
| title_short | Hybrid approach for alignment of a pre-processed three-dimensional point cloud, video, and CAD model using partial point cloud in retrofitting applications |
| title_sort | hybrid approach for alignment of a pre processed three dimensional point cloud video and cad model using partial point cloud in retrofitting applications |
| url | https://doi.org/10.1177/1550147718766452 |
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