Multi-Drone 3D Reconstruction of Architectural and Structural Entities

In this paper, we analyze the results of 3D reconstructions of buildings and monuments using a multi-drone sys-tem with predefined parameters. The drones follow an elliptical flight path with the same average speed in opposite directions and different altitudes for data acquisition of RGB videos. We set the drone cameras at a specific angle to avoid occlusion areas. Then, for 3D reconstructions, we used Convolutional Neural Networks techniques, specifically NeRF and Gaussian Splatting, in two different case studies: a simulation environment and a field test. As a result, we obtained detailed and visually accurate 3D models.

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Publication Details

Published
2024-11-13
DOI
https://doi.org/10.1109/sbr/wre63066.2024.10837817
Citations
1
Primary Topic
3D Surveying and Cultural Heritage
Type
article
Field-Weighted Citation Impact
0.83
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article

Multi-Drone 3D Reconstruction of Architectural and Structural Entities

Fábio Suim Chagas, Daniel Morais, Thiago J. M. Baldivieso, Gabriela Moutinho de Souza Dias et al.
1 citations
3D Surveying and Cultural Heritage
0.83
article

Multi-Drone 3D Reconstruction of Architectural and Structural Entities

Fábio Suim Chagas, Daniel Morais, Thiago J. M. Baldivieso, Gabriela Moutinho de Souza Dias, Paulo Fernando Ferreira Rosa
article en
1 citations

Abstract

In this paper, we analyze the results of 3D reconstructions of buildings and monuments using a multi-drone sys-tem with predefined parameters. The drones follow an elliptical flight path with the same average speed in opposite directions and different altitudes for data acquisition of RGB videos. We set the drone cameras at a specific angle to avoid occlusion areas. Then, for 3D reconstructions, we used Convolutional Neural Networks techniques, specifically NeRF and Gaussian Splatting, in two different case studies: a simulation environment and a field test. As a result, we obtained detailed and visually accurate 3D models.

University of South-Eastern Norway (NO), Military Institute of Engineering (BR)
Sustainable cities and communities
Openalex Percentile: Top 17%
3D Surveying and Cultural Heritage
0.83
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