Stedman, Harvey;
Lu, Ziwen;
Pawar, Vijay M;
(2023)
Automated Multimodal Data Capture for Photorealistic Construction Progress Monitoring in Virtual Reality.
In:
Proceedings of the IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW) 2023.
(pp. pp. 108-112).
Institute of Electrical and Electronics Engineers (IEEE)
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Abstract
Construction monitoring is vital for the timely delivery of projects. However manual data collection and fusion methods are arduous. We propose a framework for autonomous multimodal data collection and VR visualisation. Based on “work-in-progress” results we demonstrate its capabilities in-the-lab and validate its functionality on a real site. We explore how such a framework could complement construction-centric deep learning and 4D as-built datasets to aid human decision-making using VR
| Type: | Proceedings paper |
|---|---|
| Title: | Automated Multimodal Data Capture for Photorealistic Construction Progress Monitoring in Virtual Reality |
| Event: | 2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW) |
| Dates: | 25 Mar 2023 - 29 Mar 2023 |
| ISBN-13: | 979-8-3503-4839-2 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/vrw58643.2023.00028 |
| Publisher version: | https://doi.org/10.1109/VRW58643.2023.00028 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions. |
| Keywords: | Autonomous mobile inspection, deep learning construction monitoring, laser scanning, human-robot decision making, virtual reality. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10169513 |
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