A Framework for 3D Modeling of Construction Sites Using Aerial Imagery and Semantic NeRFs
Creators
Description
The 30th International Conference, MMM 2024, took place in Amsterdam, The Netherlands, January 29 – February 2, 2024, in which our ASHVIN partner CERTH / ITI presented a conference paper entitled “A framework for 3D modelling of construction sites using aerial imagery and semantic NeRFs”. This peer-reviewed publication was authored by Panagiotis Vrachnos, Marios Krestenitis, Ilias Koulalis, Konstantinos Ioannidis and Stefanos Vrochidis, all researchers at CERTH/ITI. This paper is related to the ASHVIN Demonstration Site #7 - Bridges in highway network in Spain.
Abstract
The rapid evolution of drone technology has revolutionized data acquisition in the construction industry, offering a cost-effective and efficient method to monitor and map engineering structures. However, a significant challenge remains in transforming the drone-collected data into semantically meaningful 3D models. 3D reconstruction techniques usually lead to raw point clouds that are typically unstructured and lack the semantic and geometric information of objects needed for civil engineering tools. Our solution applies semantic segmentation algorithms to the data produced by NeRF (Neural Radiance Fields), effectively transforming drone-captured 3D volumetric representations into semantically rich 3D models. This approach offers a cost-effective and automated way to digitalize physical objects of construction sites into semantically annotated digital counterparts facilitating the development of digital twins or XR applications in the construction sector.
Note
THIS VERSION IS THE SUBMITTED ONE (not the final version published by the MMM2024 editor).
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A_Framework_for_3D_Modeling_of_Construction_Sites_Using_Aerial_Imagery_and_Semantic_NeRFs_Camera_Ready.pdf
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Additional details
Funding
Dates
- Accepted
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2024-01