id
	13174
Url
	https://chloe.cnr.it/s/BiDiAr/item/13174
Resource template
	Academic Article
Resource class
	bibo:AcademicArticle
Title
	A comparison between 3d reconstruction using nerf neural networks and mvs algorithms on cultural heritage images
Creator
	Condorelli, Francesca
	Rinaudo, Fulvio
	Salvadore, Francesco
	Tagliaventi, Stefano
Date
	2021
Language
	eng
Abstract
	In this research, an innovative comparison between 3D reconstructions obtained by means of Artificial Intelligence, in particular NeRF Neural Networks, and by Structure-from-Motion (SfM) and Multi-View-Stereo (MVS) open-source algorithms is proposed. The 3D reconstruction comparison is performed on two test cases, one of cultural interest, one useful only for technical discussion. It is known that the approaches are traditionally used with different objectives and in different contexts but they can however also be used with similar purpose, i.e., 3D reconstruction. In particular, we were interested in evaluating how NeRF reconstructions are accurate from a metric point of view and how the models obtained from the application of NeRF differ from the model obtained from the classical photogrammetry. By analyzing the results in the considered test cases, we show how NeRF networks, although computationally demanding, can be an interesting alternative or complementary methodology, especially in cases where classical photogrammetric techniques do not allow satisfactory results to be achieved. It is therefore suggested to expand efforts in this direction by exploiting, for example, the numerous improvement proposals of the original NeRF network.
Is Part Of
	The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Doi
	https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-565-2021
Issn
	1682-1750
Pages
	565-570
Uri
	https://isprs-archives.copernicus.org/articles/XLIII-B2-2021/565/2021/
Volume
	XLIII-B2-2021
Homepage
	https://www.zotero.org/groups/5293298/bidiar/items/2BPC4UMC/item-list

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