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Heritage
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XR and Artificial Intelligence for Heritage
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XR and Artificial Intelligence for Heritage

A special issue of Heritage (ISSN 2571-9408).

Deadline for manuscript submissions: closed (29 February 2024) | Viewed by 20155

Special Issue Editor

Dr. Bruno Fanini

E-Mail Website
Guest Editor
CNR, ISPC, 34900 Rome, Italy
Interests: WebXR; immersive VR; 3D interfaces; spatial user interfaces; social VR
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The recent growth of Artificial Intelligence (AI) applications, as well as advancements in the XR domain, are providing strong opportunities for advancement of the heritage field. Indeed, heritage and  AI often find themselves entwined.

AI is rapidly affecting several pipelines within scientific visualization, generative arts, museum applications, natural language processing (NLP, digitization and documentation processes, recommendation systems, data classification, segmentation and analysis, reconstruction, and many more.

Recent applications in literature are providing new tools and approaches to accelerate or automate specific tasks, and also support or improve human-computer interactions.

XR segments, including immersive VR (Virtual Reality), Augmented Reality (AR) and Mixed Reality (MR), are creating new ways to perceive, inspect and experience cultural heritage, thanks to the rapid growth of related technologies and standards. Technological challenges still persist, pushing researchers to explore new solutions and new models within the domain of human-computer interaction (HCI) after proving their effectiveness and suitability for use in the application of XR to the heritage field.

Topics of interest include, but are not limited to:

  • AI in data segmentation, detection, classification or analysis;
  • AI in digital cultural content;
  • AI in 2D/3D digitization pipelines;
  • AI for semantics and knowledge representation;
  • AI in reconstruction or restoration processes;
  • AI for interactive or XR visualization;
  • AI in education and tourism;
  • AI in natural language processing (NLP) and CH applications;
  • Interactive WebXR applications, tools or services for heritage;
  • Interaction design process and methods for XR;
  • Human-computer interaction models for VR, AR or MR;
  • Spatial computing and 3D interfaces for XR;
  • Neural radiance fields (NeRF) targeting heritage field.

Dr. Bruno Fanini
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Heritage is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (7 papers)

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Research

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16 pages, 14921 KiB  
Article
Artificial Interpretation: An Investigation into the Feasibility of Archaeologically Focused Seismic Interpretation via Machine Learning
by Andrew Iain Fraser, Jürgen Landauer, Vincent Gaffney and Elizabeth Zieschang
Heritage 2024, 7(5), 2491-2506; https://doi.org/10.3390/heritage7050119 - 10 May 2024
Viewed by 1187
Abstract
The value of artificial intelligence and machine learning applications for use in heritage research is increasingly appreciated. In specific areas, notably remote sensing, datasets have increased in extent and resolution to the point that manual interpretation is problematic and the availability of skilled [...] Read more.
The value of artificial intelligence and machine learning applications for use in heritage research is increasingly appreciated. In specific areas, notably remote sensing, datasets have increased in extent and resolution to the point that manual interpretation is problematic and the availability of skilled interpreters to undertake such work is limited. Interpretation of the geophysical datasets associated with prehistoric submerged landscapes is particularly challenging. Following the Last Glacial Maximum, sea levels rose by 120 m globally, and vast, habitable landscapes were lost to the sea. These landscapes were inaccessible until extensive remote sensing datasets were provided by the offshore energy sector. In this paper, we provide the results of a research programme centred on AI applications using data from the southern North Sea. Here, an area of c. 188,000 km2 of habitable terrestrial land was inundated between c. 20,000 BP and 7000 BP, along with the cultural heritage it contained. As part of this project, machine learning tools were applied to detect and interpret features with potential archaeological significance from shallow seismic data. The output provides a proof-of-concept model demonstrating verifiable results and the potential for a further, more complex, leveraging of AI interpretation for the study of submarine palaeolandscapes. Full article
(This article belongs to the Special Issue XR and Artificial Intelligence for Heritage)
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24 pages, 18911 KiB  
Article
Proto-Early Renaissance Depictions, Iconographic Analysis and Computerised Facial Similarity Assessment Connections: The 16th Century Mural Paintings of St. Leocadia Church (Chaves, North of Portugal)
by Eunice Salavessa, José Aranha, Rafael Moreira and David M. Freire-Lista
Heritage 2024, 7(4), 2031-2054; https://doi.org/10.3390/heritage7040096 - 29 Mar 2024
Viewed by 1839
Abstract
The aim of this paper is to analyse facial similarity and apply it to identify the individuals depicted in the mural paintings of the apse of St. Leocadia Church, located in Chaves Municipality (North of Portugal), which were painted during the first quarter [...] Read more.
The aim of this paper is to analyse facial similarity and apply it to identify the individuals depicted in the mural paintings of the apse of St. Leocadia Church, located in Chaves Municipality (North of Portugal), which were painted during the first quarter of the 16th century. This study also compares the portraits of this mural paintings with the oil paintings by the Proto-Renaissance Portuguese painter Nuno Gonçalves. Through this research, the feasibility of face recognition technology is explored to answer many ambiguities about Manueline stylistic identity and iconography. Additionally, it aims to associate historical events, artistic discoveries, and the expansion of portraiture as propaganda of power during the Portuguese Proto-Renaissance and Early Renaissance. On the other hand, it focuses on the prevalence of the religious and devotional over the sacred in Manueline painting. A proposal was made to identify the characters that are fundamental to the meaning of the mural paintings. An experiment was conducted on seven characters from the paintings at St. Leocadia Church, which were then compared to Nuno Gonçalves’ portraits. Facial similarity analysis was conducted on the faces portrayed in the Panels of St. Vincent, a remarkable portrait gallery from 15th-century Portugal, which has been the subject of national and international research for 130 years. Other paintings that were analysed were the oil paintings of St. Peter and St. Paul and of Infanta St. Joana, which were created by the same Quattrocento master. The purpose of the mural paintings of St. Leocadia Church could be catechetical in nature or related to the ritual practices of royal ancestor worship in royal portrait apses of the churches. It could also be associated with the Portuguese maritime expansion and the macro-imperial ideology of D. Manuel I. Full article
(This article belongs to the Special Issue XR and Artificial Intelligence for Heritage)
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23 pages, 2925 KiB  
Article
Comparing the Impact of Non-Gamified and Gamified Virtual Reality in Digital Twin Virtual Museum Environments: A Case Study of Wieng Yong House Museum, Thailand
by Suepphong Chernbumroong, Pakinee Ariya, Suratchanee Yolthasart, Natchaya Wongwan, Kannikar Intawong and Kitti Puritat
Heritage 2024, 7(4), 1870-1892; https://doi.org/10.3390/heritage7040089 - 24 Mar 2024
Cited by 4 | Viewed by 2248
Abstract
Virtual reality (VR) is increasingly employed in various domains, notably enhancing learning and experiences in cultural heritage (CH). This study examines the effects of gamified and non-gamified VR experiences within virtual museum environments, highlighting the concept of a digital twin and its focus [...] Read more.
Virtual reality (VR) is increasingly employed in various domains, notably enhancing learning and experiences in cultural heritage (CH). This study examines the effects of gamified and non-gamified VR experiences within virtual museum environments, highlighting the concept of a digital twin and its focus on cultural heritage. It explores how these VR modalities affect visitor motivation, engagement, and learning outcomes. For this purpose, two versions were developed: a gamified virtual reality version incorporating interactive gaming elements like achievements, profiles, leaderboards, and quizzes and a non-gamified virtual reality version devoid of these elements. This study, using an experimental design with 76 participants (38 in each group for the gamified and non-gamified experiences), leverages the Wieng Yong House Museum’s digital twin and its fabric collection to assess the educational and experiential quality of virtual museum visits. The findings indicate that while gamification significantly boosts the reward dimension of visitor engagement, its influence is most pronounced in the effort dimension of motivation; however, its impact on learning outcomes is less marked. These insights are instrumental for integrating VR and gamification into museum environments. Full article
(This article belongs to the Special Issue XR and Artificial Intelligence for Heritage)
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20 pages, 5228 KiB  
Article
Potential Impact of Using ChatGPT-3.5 in the Theoretical and Practical Multi-Level Approach to Open-Source Remote Sensing Archaeology, Preliminary Considerations
by Nicodemo Abate, Francesca Visone, Maria Sileo, Maria Danese, Antonio Minervino Amodio, Rosa Lasaponara and Nicola Masini
Heritage 2023, 6(12), 7640-7659; https://doi.org/10.3390/heritage6120402 - 12 Dec 2023
Cited by 2 | Viewed by 3663
Abstract
This study aimed to evaluate the impact of using an AI model, specifically ChatGPT-3.5, in remote sensing (RS) applied to archaeological research. It assessed the model’s abilities in several aspects, in accordance with a multi-level analysis of its usefulness: providing answers to both [...] Read more.
This study aimed to evaluate the impact of using an AI model, specifically ChatGPT-3.5, in remote sensing (RS) applied to archaeological research. It assessed the model’s abilities in several aspects, in accordance with a multi-level analysis of its usefulness: providing answers to both general and specific questions related to archaeological research; identifying and referencing the sources of information it uses; recommending appropriate tools based on the user’s desired outcome; assisting users in performing basic functions and processes in RS for archaeology (RSA); assisting users in carrying out complex processes for advanced RSA; and integrating with the tools and libraries commonly used in RSA. ChatGPT-3.5 was selected due to its availability as a free resource. The research also aimed to analyse the user’s prior skills, competencies, and language proficiency required to effectively utilise the model for achieving their research goals. Additionally, the study involved generating JavaScript code for interacting with the free Google Earth Engine tool as part of its research objectives. Use of these free tools, it was possible to demonstrate the impact that ChatGPT-3.5 can have when embedded in an archaeological RS flowchart on different levels. In particular, it was shown to be useful both for the theoretical part and for the generation of simple and complex processes and elaborations. Full article
(This article belongs to the Special Issue XR and Artificial Intelligence for Heritage)
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13 pages, 1081 KiB  
Article
Experimenting with Training a Neural Network in Transkribus to Recognise Text in a Multilingual and Multi-Authored Manuscript Collection
by Carlotta Capurro, Vera Provatorova and Evangelos Kanoulas
Heritage 2023, 6(12), 7482-7494; https://doi.org/10.3390/heritage6120392 - 29 Nov 2023
Cited by 3 | Viewed by 1878
Abstract
This work aims at developing an optimal strategy to automatically transcribe a large quantity of uncategorised, digitised archival documents when resources include handwritten text by multiple authors and in several languages. We present a comparative study to establish the efficiency of a single [...] Read more.
This work aims at developing an optimal strategy to automatically transcribe a large quantity of uncategorised, digitised archival documents when resources include handwritten text by multiple authors and in several languages. We present a comparative study to establish the efficiency of a single multilingual handwritten text recognition (HTR) model trained on multiple handwriting styles instead of using a separate model for every language. When successful, this approach allows us to automate the transcription of the archive, reducing manual annotation efforts and facilitating information retrieval. To train the model, we used the material from the personal archive of the Dutch glass artist Sybren Valkema (1916–1996), processing it with Transkribus. Full article
(This article belongs to the Special Issue XR and Artificial Intelligence for Heritage)
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22 pages, 6963 KiB  
Article
A Quantitative Social Network Analysis of the Character Relationships in the Mahabharata
by Eren Gultepe and Vivek Mathangi
Heritage 2023, 6(11), 7009-7030; https://doi.org/10.3390/heritage6110366 - 29 Oct 2023
Viewed by 1996
Abstract
Despite the advances in computational literary analysis of Western literature, in-depth analysis of the South Asian literature has been lacking. Thus, social network analysis of the main characters in the Indian epic Mahabharata was performed, in which it was prepossessed into verses, followed [...] Read more.
Despite the advances in computational literary analysis of Western literature, in-depth analysis of the South Asian literature has been lacking. Thus, social network analysis of the main characters in the Indian epic Mahabharata was performed, in which it was prepossessed into verses, followed by a term frequency–inverse document frequency (TF-IDF) transformation. Then, Latent Semantic Analysis (LSA) word vectors were obtained by applying compact Singular Value Decomposition (SVD) on the term–document matrix. As a novel innovation to this study, these word vectors were adaptively converted into a fully connected similarity matrix and transformed, using a novel locally weighted K-Nearest Neighbors (KNN) algorithm, into a social network. The viability of the social networks was assessed by their ability to (i) recover individual character-to-character relationships; (ii) embed the overall network structure (verified with centrality measures and correlations); and (iii) detect communities of the Pandavas (protagonist) and Kauravas (antagonist) using spectral clustering. Thus, the proposed scheme successfully (i) predicted the character-to-character connections of the most important and second most important characters at an F-score of 0.812 and 0.785, respectively, (ii) recovered the overall structure of the ground-truth networks by matching the original centralities (corr. > 0.5, p < 0.05), and (iii) differentiated the Pandavas from the Kauravas with an F-score of 0.749. Full article
(This article belongs to the Special Issue XR and Artificial Intelligence for Heritage)
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Review

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23 pages, 4853 KiB  
Review
Artificial Intelligence for Digital Heritage Innovation: Setting up a R&D Agenda for Europe
by Sander Münster, Ferdinand Maiwald, Isabella di Lenardo, Juha Henriksson, Antoine Isaac, Manuela Milica Graf, Clemens Beck and Johan Oomen
Heritage 2024, 7(2), 794-816; https://doi.org/10.3390/heritage7020038 - 6 Feb 2024
Cited by 7 | Viewed by 6060
Abstract
Artificial intelligence (AI) is a game changer in many fields, including cultural heritage. It supports the planning and preservation of heritage sites and cities, enables the creation of virtual experiences to enrich cultural tourism and engagement, supports research, and increases access and understanding [...] Read more.
Artificial intelligence (AI) is a game changer in many fields, including cultural heritage. It supports the planning and preservation of heritage sites and cities, enables the creation of virtual experiences to enrich cultural tourism and engagement, supports research, and increases access and understanding of heritage objects. Despite some impressive examples, the full potential of AI for economic, social, and cultural change is not yet fully visible. Against this background, this article aims to (a) highlight the scope of AI in the field of cultural heritage and innovation, (b) highlight the state of the art of AI technologies for cultural heritage, (c) highlight challenges and opportunities, and (d) outline an agenda for AI, cultural heritage, and innovation. Full article
(This article belongs to the Special Issue XR and Artificial Intelligence for Heritage)
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