{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,11]],"date-time":"2026-04-11T15:07:12Z","timestamp":1775920032142,"version":"3.50.1"},"reference-count":48,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2024,1,11]],"date-time":"2024-01-11T00:00:00Z","timestamp":1704931200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Joint LAB project LIA Laboratoire International Associ\u00e9","award":["2636\/22"],"award-info":[{"award-number":["2636\/22"]}]},{"name":"Joint LAB project LIA Laboratoire International Associ\u00e9","award":["1476\/23"],"award-info":[{"award-number":["1476\/23"]}]},{"name":"French CNRS (National Center for Scientific Research)","award":["2636\/22"],"award-info":[{"award-number":["2636\/22"]}]},{"name":"French CNRS (National Center for Scientific Research)","award":["1476\/23"],"award-info":[{"award-number":["1476\/23"]}]},{"name":"ASTRO Laboratory of the University of Pisa","award":["2636\/22"],"award-info":[{"award-number":["2636\/22"]}]},{"name":"ASTRO Laboratory of the University of Pisa","award":["1476\/23"],"award-info":[{"award-number":["1476\/23"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>This paper conducts a comparative evaluation between Neural Radiance Fields (NeRF) and photogrammetry for 3D reconstruction in the cultural heritage domain. Focusing on three case studies, of which the Terpsichore statue serves as a pilot case, the research assesses the quality, consistency, and efficiency of both methods. The results indicate that, under conditions of reduced input data or lower resolution, NeRF outperforms photogrammetry in preserving completeness and material description for the same set of input images (with known camera poses). The study recommends NeRF for scenarios requiring extensive area mapping with limited images, particularly in emergency situations. Despite NeRF\u2019s developmental stage compared to photogrammetry, the findings demonstrate higher potential for describing material characteristics and rendering homogeneous textures with enhanced visual fidelity and accuracy; however, NeRF seems more prone to noise effects. The paper advocates for the future integration of NeRF with photogrammetry to address respective limitations, offering more comprehensive representation for cultural heritage preservation tasks. Future developments include extending applications to planar surfaces and exploring NeRF in virtual and augmented reality, as well as studying NeRF evolution in line with emerging trends in semantic segmentation and in-the-wild scene reconstruction.<\/jats:p>","DOI":"10.3390\/rs16020301","type":"journal-article","created":{"date-parts":[[2024,1,11]],"date-time":"2024-01-11T08:27:07Z","timestamp":1704961627000},"page":"301","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":45,"title":["Comparative Assessment of Neural Radiance Fields and Photogrammetry in Digital Heritage: Impact of Varying Image Conditions on 3D Reconstruction"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9601-3145","authenticated-orcid":false,"given":"Valeria","family":"Croce","sequence":"first","affiliation":[{"name":"LISPEN EA 7515, Arts et M\u00e9tiers Institute of Technology, 13100 Aix-en-Provence, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0210-6119","authenticated-orcid":false,"given":"Dario","family":"Billi","sequence":"additional","affiliation":[{"name":"Department of Civil and Industrial Engineering, ASTRO Laboratory, University of Pisa, 56122 Pisa, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3065-0616","authenticated-orcid":false,"given":"Gabriella","family":"Caroti","sequence":"additional","affiliation":[{"name":"Department of Civil and Industrial Engineering, ASTRO Laboratory, University of Pisa, 56122 Pisa, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0582-5314","authenticated-orcid":false,"given":"Andrea","family":"Piemonte","sequence":"additional","affiliation":[{"name":"Department of Civil and Industrial Engineering, ASTRO Laboratory, University of Pisa, 56122 Pisa, Italy"}]},{"given":"Livio","family":"De Luca","sequence":"additional","affiliation":[{"name":"UMR MAP 3495 CNRS\/MC, Campus CNRS Joseph-Aiguier, 13402 Marseille, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4062-2432","authenticated-orcid":false,"given":"Philippe","family":"V\u00e9ron","sequence":"additional","affiliation":[{"name":"LISPEN EA 7515, Arts et M\u00e9tiers Institute of Technology, 13100 Aix-en-Provence, France"}]}],"member":"1968","published-online":{"date-parts":[[2024,1,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Moyano, J., Nieto-Juli\u00e1n, J.E., Bienvenido-Huertas, D., and Mar\u00edn-Garc\u00eda, D. (2020). Validation of Close-Range Photogrammetry for Architectural and Archaeological Heritage: Analysis of Point Density and 3d Mesh Geometry. Remote Sens., 12.","DOI":"10.3390\/rs12213571"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"108291","DOI":"10.1016\/j.measurement.2020.108291","article-title":"Validation of Terrestrial Laser Scanning and Artificial Intelligence for Measuring Deformations of Cultural Heritage Structures","volume":"167","author":"Wojtkowska","year":"2021","journal-title":"Meas. J. Int. Meas. Confed."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"D\u00edaz-Rodr\u00edguez, N., and Pisoni, G. (2020). Accessible Cultural Heritage through Explainable Artificial Intelligence, Association for Computing Machinery.","DOI":"10.1145\/3386392.3399276"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"\u0160kola, F., Rizvi\u0107, S., Cozza, M., Barbieri, L., Bruno, F., Skarlatos, D., and Liarokapis, F. (2020). Virtual Reality with 360-Video Storytelling in Cultural Heritage: Study of Presence, Engagement, and Immersion. Sensors, 20.","DOI":"10.3390\/s20205851"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1016\/j.patrec.2020.02.017","article-title":"Machine Learning for Cultural Heritage: A Survey","volume":"133","author":"Fiorucci","year":"2020","journal-title":"Pattern Recognit. Lett."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1145\/3051480","article-title":"More than Meets the Eye: The Benefits of Augmented Reality and Holographic Displays for Digital Cultural Heritage","volume":"10","author":"Pedersen","year":"2017","journal-title":"J. Comput. Cult. Herit."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/1743873X.2020.1850742","article-title":"Innovating the Cultural Heritage Museum Service Model through Virtual Reality and Augmented Reality: The Effects on the Overall Visitor Experience and Satisfaction","volume":"17","author":"Trunfio","year":"2022","journal-title":"J. Herit. Tour."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"5981","DOI":"10.1038\/s41598-023-32504-9","article-title":"Faceting the Post-Disaster Built Heritage Reconstruction Process within the Digital Twin Framework for Notre-Dame de Paris","volume":"13","author":"Gros","year":"2023","journal-title":"Sci. Rep."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Croce, V., Caroti, G., De Luca, L., Jacquot, K., Piemonte, A., and V\u00e9ron, P. (2021). From the Semantic Point Cloud to Heritage-Building Information Modeling: A Semiautomatic Approach Exploiting Machine Learning. Remote Sens., 13.","DOI":"10.3390\/rs13030461"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1145\/3145534","article-title":"A Survey of Augmented, Virtual, and Mixed Reality for Cultural Heritage","volume":"11","author":"Bekele","year":"2018","journal-title":"J. Comput. Cult. Herit."},{"key":"ref_11","first-page":"161","article-title":"Digital Technology and Mechatronic Systems for the Architectural 3D Metric Survey","volume":"92","author":"Bevilacqua","year":"2018","journal-title":"Intell. Syst. Control Autom. Sci. Eng."},{"key":"ref_12","first-page":"1121","article-title":"The Heritage Management and Preservation Using the Mechatronic Survey","volume":"11","author":"Rea","year":"2017","journal-title":"Int. J. Archit. Herit."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Croce, V., Caroti, G., Piemonte, A., De Luca, L., and V\u00e9ron, P. (2023). H-BIM and Artificial Intelligence: Classification of Architectural Heritage for Semi-Automatic Scan-to-BIM Reconstruction. Sensors, 23.","DOI":"10.3390\/s23052497"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"259","DOI":"10.5194\/isprs-archives-XLII-2-259-2018","article-title":"Cultural Heritage Reconstruction from Historical Photographs and Videos","volume":"XLII-2","author":"Condorelli","year":"2018","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Mildenhall, B., Srinivasan, P.P., Tancik, M., Barron, J.T., Ramamoorthi, R., and Ng, R. (2020). NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis. arXiv.","DOI":"10.1007\/978-3-030-58452-8_24"},{"key":"ref_16","unstructured":"Gao, K., Gao, Y., He, H., Lu, D., Xu, L., and Li, J. (2022). NeRF: Neural Radiance Field in 3D Vision, a Comprehensive Review. arXiv."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1113","DOI":"10.5194\/isprs-archives-XLVIII-M-2-2023-1113-2023","article-title":"Initial Assessment on the Use of State-of-the-Art NeRF Neural Network 3D Reconstruction for Heritage Documentation","volume":"XLVIII-M-2-2023","author":"Murtiyoso","year":"2023","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Lorensen, W.E., and Cline, H.E. (1987, January 27\u201331). Marching Cubes: A High Resolution 3D Surface Construction Algorithm. Proceedings of the 14th Annual Conference on Computer Graphics and Interactive Techniques, Anaheim, CA, USA.","DOI":"10.1145\/37401.37422"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"423","DOI":"10.1016\/j.culher.2007.06.003","article-title":"Documentation of Cultural Heritage Using Digital Photogrammetry and Laser Scanning","volume":"8","author":"Yastikli","year":"2007","journal-title":"J. Cult. Herit."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/16864360.2016.1199751","article-title":"An Innovative Photogrammetry Color Segmentation Based Technique as an Alternative Approach to 3D Scanning for Reverse Engineering Design","volume":"14","author":"James","year":"2017","journal-title":"Comput. Aided Des. Appl."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Fiz, J.I., Mart\u00edn, P.M., Cuesta, R., Sub\u00edas, E., Codina, D., and Cartes, A. (2022). Examples and Results of Aerial Photogrammetry in Archeology with UAV: Geometric Documentation, High Resolution Multispectral Analysis, Models and 3D Printing. Drones, 6.","DOI":"10.3390\/drones6030059"},{"key":"ref_22","first-page":"170","article-title":"Integration of Laser Scanning and Photogrammetry in Architecture Survey. Open Issue in Geomatics and Attention to Details","volume":"1246","author":"Caroti","year":"2020","journal-title":"Commun. Comput. Inf. Sci."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Guimar\u00e3es, N., P\u00e1dua, L., Marques, P., Silva, N., Peres, E., and Sousa, J.J. (2020). Forestry Remote Sensing from Unmanned Aerial Vehicles: A Review Focusing on the Data, Processing and Potentialities. Remote Sens., 12.","DOI":"10.3390\/rs12061046"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1007\/s10064-008-0157-y","article-title":"Using Close Range Terrestrial Digital Photogrammetry for 3-D Rock Slope Modeling and Discontinuity Mapping in the United States","volume":"67","author":"Haneberg","year":"2008","journal-title":"Bull. Eng. Geol. Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"451","DOI":"10.5194\/isprsarchives-XL-5-451-2014","article-title":"Photogrammetry Applied to Problematic Artefacts","volume":"XL-5","author":"Nicolae","year":"2014","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_26","first-page":"959","article-title":"Digital Photogrammetry and Structure From Motion for Architectural Heritage: Comparison and Integration between Procedures","volume":"Volume 2","author":"Ippoliti","year":"2019","journal-title":"Geospatial Intelligence: Concepts, Methodologies, Tools, and Applications"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Barron, J.T., Mildenhall, B., Tancik, M., Hedman, P., Martin-Brualla, R., and Srinivasan, P.P. (2021, January 10\u201317). Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields. Proceedings of the 2021 IEEE\/CVF International Conference on Computer Vision (ICCV), Montreal, QC, Canada.","DOI":"10.1109\/ICCV48922.2021.00580"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Derksen, D., and Izzo, D. (2021, January 19\u201325). Shadow Neural Radiance Fields for Multi-View Satellite Photogrammetry. Proceedings of the 2021 IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Nashville, TN, USA.","DOI":"10.1109\/CVPRW53098.2021.00126"},{"key":"ref_29","unstructured":"Semeraro, F., Zhang, Y., Wu, W., and Carroll, P. (2023). NeRF Applied to Satellite Imagery for Surface Reconstruction. arXiv."},{"key":"ref_30","unstructured":"Kerr, J., Fu, L., Huang, H., Avigal, Y., Tancik, M., Ichnowski, J., Kanazawa, A., and Goldberg, K. (2022, January 14\u201318). Evo-NeRF: Evolving NeRF for Sequential Robot Grasping of Transparent Objects. Proceedings of the 6th Conference on Robot Learning, Auckland, New Zealand."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Zhou, A., Kim, M.J., Wang, L., Florence, P., and Finn, C. (2023). NeRF in the Palm of Your Hand: Corrective Augmentation for Robotics via Novel-View Synthesis. arXiv.","DOI":"10.1109\/CVPR52729.2023.01717"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"4606","DOI":"10.1109\/LRA.2022.3150497","article-title":"Vision-Only Robot Navigation in a Neural Radiance World","volume":"7","author":"Adamkiewicz","year":"2022","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Li, Y., Lin, Z.-H., Forsyth, D., Huang, J.-B., and Wang, S. (2023). ClimateNeRF: Extreme Weather Synthesis in Neural Radiance Field. arXiv.","DOI":"10.1109\/ICCV51070.2023.00299"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Mergy, A., Lecuyer, G., Derksen, D., and Izzo, D. (2021, January 19\u201325). Vision-Based Neural Scene Representations for Spacecraft. Proceedings of the 2021 IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Nashville, TN, USA.","DOI":"10.1109\/CVPRW53098.2021.00228"},{"key":"ref_35","unstructured":"Gafni, G., Thies, J., Zollh\u00f6fer, M., and Nie\u00dfner, M. (2023). Dynamic Neural Radiance Fields for Monocular 4D Facial Avatar Reconstruction. arXiv."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1051","DOI":"10.5194\/isprs-archives-XLVIII-M-2-2023-1051-2023","article-title":"NeRF for Heritage 3D Reconstruction","volume":"XLVIII-M-2-2023","author":"Mazzacca","year":"2023","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"565","DOI":"10.5194\/isprs-archives-XLIII-B2-2021-565-2021","article-title":"A Comparison between 3D Reconstruction Using NERF Neural Networks and MVS Algorithms on Cultural Heritage Images","volume":"XLIII-B2-2021","author":"Condorelli","year":"2021","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1599","DOI":"10.5194\/isprs-archives-XLVIII-M-2-2023-1599-2023","article-title":"Crowd-Sourced Surveying for Building Archaeology: The Potential of Structure From Motion (SFM) and Neural Radiance Fields (NERF)","volume":"XLVIII-M-2-2023","author":"Vandenabeele","year":"2023","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"155","DOI":"10.5194\/isprs-archives-XLVIII-M-2-2023-155-2023","article-title":"Few Shot Photogrametry: A Comparison Between Nerf and Mvs-Sfm for the Documentation of Cultural Heritage","volume":"48M2","author":"Balloni","year":"2023","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1149","DOI":"10.5194\/isprs-archives-XLVIII-M-2-2023-1149-2023","article-title":"Artificial Intelligence and Cultural Heritage: Design and Assessment of an Ethical Framework","volume":"XLVIII-M-2-2023","author":"Pansoni","year":"2023","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"453","DOI":"10.5194\/isprs-archives-XLVIII-M-2-2023-453-2023","article-title":"Neural Radiance Fields (NERF): Review and Potential Applications to Digital Cultural Heritage","volume":"XLVIII-M-2-2023","author":"Croce","year":"2023","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_42","first-page":"391","article-title":"La Torre Degli Upezzinghi a Caprona: Analisi storico-archivistica e rilievo digitale per la documentazione dell\u2019evoluzione temporale","volume":"Volume XIII","author":"Bevilacqua","year":"2023","journal-title":"Defensive Architecture of the Mediterranean, Proceedings of the International Conference on Fortifications of the Mediterranean Coast FORTMED 2023, Pisa, Italy, 23\u201325 March 2023"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Tancik, M., Weber, E., Ng, E., Li, R., Yi, B., Kerr, J., Wang, T., Kristoffersen, A., Austin, J., and Salahi, K. (2023, January 6\u201310). Nerfstudio: A Modular Framework for Neural Radiance Field Development. Proceedings of the SIGGRAPH\u201923: Special Interest Group on Computer Graphics and Interactive Techniques Conference, Los Angeles, CA, USA.","DOI":"10.1145\/3588432.3591516"},{"key":"ref_44","unstructured":"Kazhdan, M., Bolitho, M., and Hoppe, H. (2006, January 26\u201328). Poisson Surface Reconstruction. Proceedings of the Eurographics Symposium on Geometry Processing, Sardinia, Italy."},{"key":"ref_45","unstructured":"European Commission (2022). Directorate-General for Communications Networks, Content and Technology, Study on Quality in 3D Digitisation of Tangible Cultural Heritage\u2014Mapping Parameters, Formats, Standards, Benchmarks, Methodologies, and Guidelines\u2014Executive Summary, Publications Office of the European Union. Available online: https:\/\/data.europa.eu\/doi\/10.2759\/581678."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Zhi, S., Laidlow, T., Leutenegger, S., and Davison, A.J. (2021). In-Place Scene Labelling and Understanding with Implicit Scene Representation. arXiv.","DOI":"10.1109\/ICCV48922.2021.01554"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Martin-Brualla, R., Radwan, N., Sajjadi, M.S.M., Barron, J.T., Dosovitskiy, A., and Duckworth, D. (2021). NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collections. arXiv.","DOI":"10.1109\/CVPR46437.2021.00713"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"3854","DOI":"10.1109\/TVCG.2022.3203102","article-title":"FoV-NeRF: Foveated Neural Radiance Fields for Virtual Reality","volume":"28","author":"Deng","year":"2022","journal-title":"IEEE Trans. Visual. Comput. 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