Monocular Vision-Based Target-free Three-dimensional (3D) Vibration Displacement Measurement for Civil Structures
| dc.contributor.author | Shao, Yanda | |
| dc.contributor.supervisor | Ling Li | en_US |
| dc.contributor.supervisor | Jun Li | en_US |
| dc.contributor.supervisor | Senjian An | en_US |
| dc.date.accessioned | 2024-09-04T04:28:47Z | |
| dc.date.available | 2024-09-04T04:28:47Z | |
| dc.date.issued | 2024 | en_US |
| dc.identifier.uri | http://hdl.handle.net/20.500.11937/95823 | |
| dc.description.abstract |
This dissertation introduces novel monocular vision-based approaches for 3D displacement measurement in civil engineering structures. They enable accurate measurement of 3D displacements using just a static monocular camera. The cornerstone of this innovation lies in the utilization of advanced deep learning neural networks, which have the capability to extract 3D information from a single input image. | en_US |
| dc.publisher | Curtin University | en_US |
| dc.title | Monocular Vision-Based Target-free Three-dimensional (3D) Vibration Displacement Measurement for Civil Structures | en_US |
| dc.type | Thesis | en_US |
| dcterms.educationLevel | PhD | en_US |
| curtin.department | School of Electrical Engineering, Computing and Mathematical Sciences | en_US |
| curtin.accessStatus | Fulltext not available | en_US |
| curtin.faculty | Science and Engineering | en_US |
| curtin.contributor.orcid | Shao, Yanda [0000-0002-6611-5842] | en_US |
| dc.date.embargoEnd | 2026-08-19 |