Multi-camera Acquisition System for Virtual Model Generation with Underwater Photogrammetry
| dc.contributor.affiliation | Pontificia Universidad Católica del Perú. Departamento de Ingeniería | |
| dc.contributor.author | Mendoza, R. | |
| dc.contributor.author | Menacho, D. | |
| dc.contributor.author | Cuellar, F. | |
| dc.contributor.author | Carranza, C. | |
| dc.contributor.author | Arce, D. | |
| dc.date.accessioned | 2026-03-13T16:59:59Z | |
| dc.date.issued | 2021 | |
| dc.description.abstract | Underwater photogrammetry has been used over the last few years to generate virtual models of underwater elements, structures and ecosystems. However, its applications required specialized equipment in order to obtain relevant images that could be used to generate virtual models. This paper presents the design, implementation and preliminary tests of a multi camera acquisition system that can be used to obtain images of underwater ecosystems with tourism potential This system includes elements that allow adaptable lightning capabilities based on depth and amount of light, and a position estimation of the images acquired. The images and data obtained are used to generate virtual models using underwater photogrammetry that will be later used to generate virtual tours. The system has been designed to be used by professional divers or can be operated with a Remotely Operated Vehicle (ROV) up to 500m depth. The preliminary results were aimed to estimate the performance of the system in terms of cost, energy consumption and memory capacity; and to validate the model generation methodology using underwater photogrammetty. Based on the results, an image processing strategy will be developed to optimize the characteristics of the 3D model obtained using underwater photogrammetry combined with the position estimation algorithm. | |
| dc.description.sponsorship | Funding: ACKNOWLEDGMENT The authors would like to acknowledge CONCYTEC and its program PROCIENCIA (project 161-2020) for providing funds to the project within which this work was developed. The authors also gratefully acknowledge the support from the Pontifica Universidad Catolica del Perú. | |
| dc.identifier.doi | https://doi.org/10.23919/OCEANS44145.2021.9705932 | |
| dc.identifier.uri | http://hdl.handle.net/20.500.14657/206512 | |
| dc.language.iso | eng | |
| dc.publisher | Institute of Electrical and Electronics Engineers | |
| dc.relation.conferencename | Oceans Conference Record (IEEE); Vol. 2021-September (2021) | |
| dc.relation.ispartof | urn:isbn:978-1-6654-4317-3 | |
| dc.rights | info:eu-repo/semantics/closedAccess | |
| dc.subject | Underwater | |
| dc.subject | Photogrammetry | |
| dc.subject | Computer science | |
| dc.subject | Remotely operated underwater vehicle | |
| dc.subject | Artificial intelligence | |
| dc.subject | Computer vision | |
| dc.subject | Position (finance) | |
| dc.subject | Robot | |
| dc.subject | Geology | |
| dc.subject | Mobile robot | |
| dc.subject.ocde | https://purl.org/pe-repo/ocde/ford#1.02.00 | |
| dc.title | Multi-camera Acquisition System for Virtual Model Generation with Underwater Photogrammetry | |
| dc.type | http://purl.org/coar/resource_type/c_5794 | |
| dc.type.other | Comunicación de congreso | |
| dc.type.version | https://vocabularies.coar-repositories.org/version_types/c_970fb48d4fbd8a85/ |
