GCH 2023 - Eurographics Workshop on Graphics and Cultural Heritage

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https://diglib.eg.org/handle/10.2312/3543875

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Browsing GCH 2023 - Eurographics Workshop on Graphics and Cultural Heritage by Subject "Applied computing → Arts and humanities"

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    Authenticity in VR and XR Experiences: a Conceptual Framework for Digital Heritage
    (The Eurographics Association, 2023) Pescarin, Sofia; Città, Giuseppe; Gentile, Manuel; Spotti, Samuele; Bucciero, Alberto; Fanini, Bruno; Graf, Holger; Pescarin, Sofia; Rizvic, Selma
    Although people search for authentic, memorable and meaningful experiences in cultural tourism, these requirements are not considered as part of a virtual or hybrid experience and therefore are not considered keys in their design. This paper presents an analysis of the concept of authenticity, extending its meaning well beyond the traditional interpretation in ICT. Through the study of how this concept has been developed and used in different domains and through an exploration in the wild, adopting a Cultural Probe Kit approach, it has been possible to identify the three interconnected dimensions of authenticity, their characteristics and design strategies that should be adopted to strengthen the perception of authenticity in the users of Virtual and Hybrid experiences.
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    DataSpace-ISPC: a Semantic Platform for Heritage Science
    (The Eurographics Association, 2023) Bucciero, Alberto; Chirivì, Alessandra; Anglada, Gerardo; Demetrescu, Emanuel; Fanini, Bruno; Paraciani, Nicolò; Bucciero, Alberto; Fanini, Bruno; Graf, Holger; Pescarin, Sofia; Rizvic, Selma
    The contribution presents the DataSpace of the Institute of Heritage Science (ISPC) of the Italian National Council for Research. Cultural Heritage is well known to be a multidisciplinary domain where heterogeneous data, methods and techniques overlap, co-exist and collaborate to create evidence-based wisdom represented with local and (rarely) inter-operable standards. DataSpace aims to overcome the need to harmonise converging research perspectives, allow collaborative research, and debabelize the presentation of data. This horizontal perspective is based on a graph of knowledge, ruled by a semantic reference model, and acts as a glue to connect different digital resources created with different perspectives. The DataSpace, which is built on top of the Arches platform integrated and customised with original tools, has been validated with positive results against two case studies to cover the wider domain of Heritage Science. The contribution explains the activities and technological solutions adopted and goes into detail about the problems and limitations that arose with the implementation of the DataSpace offering a critical yet positive perspective on the use of the DataSpace-ISPC in production scenarios.
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    Effective Interactive Visualization of Neural Relightable Images in a Web-based Multi-layered Framework
    (The Eurographics Association, 2023) Righetto, Leonardo; Bettio, Fabio; Ponchio, Federico; Giachetti, Andrea; Gobbetti, Enrico; Bucciero, Alberto; Fanini, Bruno; Graf, Holger; Pescarin, Sofia; Rizvic, Selma
    Relightable images created from Multi-Light Image Collections (MLICs) are one of the most commonly employed models for interactive object exploration in cultural heritage. In recent years, neural representations have been shown to produce higherquality images, at similar storage costs, with respect to the more classic analytical models such as Polynomial Texture Maps (PTM) or Hemispherical Harmonics (HSH). However, their integration in practical interactive tools has so far been limited due to the higher evaluation cost, making it difficult to employ them for interactive inspection of large images, and to the difficulty in integration cost, due to the need to incorporate deep-learning libraries in relightable renderers. In this paper, we illustrate how a state-of-the-art neural reflectance model can be directly evaluated, using common WebGL shader features, inside a multiplatform renderer. We then show how this solution can be embedded in a scalable framework capable to handle multi-layered relightable models in web settings. We finally show the performance and capabilities of the method on cultural heritage objects.
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    HerMeS - HERitage sMart social mEdia aSsistant: from Requirement Elicitation to Data Modelling for Feeding Artificial Intelligence Recommendation System
    (The Eurographics Association, 2023) Bucciero, Alberto; Chirivì, Alessandra; Jaziri, Mohamed Ali; Muci, Irene; Orlandini, Andrea; Umbrico, Alessandro; Bucciero, Alberto; Fanini, Bruno; Graf, Holger; Pescarin, Sofia; Rizvic, Selma
    In the last years, several mobile APPs have been developed within the cultural tourism domain to give new impetus to this sector which is booming both in Italy and worldwide. In the wake of the increasing importance of technologies based on artificial intelligence, even mobile applications for the use of cultural tourism heritage are increasingly taking advantage of these techniques. Machine learning strategies are increasingly used to recommend points of interest and itineraries that are compatible with the user's preferences, requirements and constraints. The quality and integrity of the data acquired become the starting point for training and implementing AI models. By levering well-structured data, these algorithms can offer valuable insights, personalised recommendations, and enhanced user interaction in the cultural tourism domain. The HerMeS APP that we present in this paper was designed starting from these premises. The application aims to provide a wide range of artificial intelligence-based features to enhance the enjoyment and exploration of cultural heritage, both tangible and intangible.
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    Interaction Design as Catalyzer of Creative and Interpretative Praxes in Museum Context
    (The Eurographics Association, 2023) Veggi, Manuele; Bucciero, Alberto; Fanini, Bruno; Graf, Holger; Pescarin, Sofia; Rizvic, Selma
    This paper argues that interaction design (IxD) can suggest valid solutions in rethinking museum mediation, focusing on conservation data as reference case study. Eliciting interest, it is possible to conceive meaningful and authentic experiences, aimed at activating a transformative dialogue with the visitors: with this approach, audiences are creatively engaged to reconsider their own expectations, behaviours and beliefs. To support this hypothesis, major attention will be paid to describe the set up and the results of a first proof of concept, conceived in the framework of the PERCEIVE Project and based on Les demoiselles à la rivière by Matisse, now exhibited at the Art Institute of Chicago.
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    Interactive Digital Narrative Authoring Tools and Hybrid Experiences in Cultural Heritage: An Integrated Review
    (The Eurographics Association, 2023) Massidda, Marcello; Travaglini, Laura; Pescarin, Sofia; Bucciero, Alberto; Fanini, Bruno; Graf, Holger; Pescarin, Sofia; Rizvic, Selma
    Interactive Digital Narrative Authoring Tools (IDN-AT) are software applications that allow users, without the need for programming skills, to create, design, and publish interactive digital narrative applications. In the field of Digital Heritage and specifically in that of Virtual Museums there is an increasing need of such tools, to enable non programmers (designers, creatives and curators) to design and develop hybrid experiences in cultural contexts. This paper aims at reviewing available solutions, defining the gaps and still missing features, tools or services, with the goal of paving the way for a webXR integrated solution.
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    Portrait2Bust: DualStyleGAN-based Portrait Image Stylization Based on Bust Sculpture Images
    (The Eurographics Association, 2023) Sinha, Saptarshi Neil; Weinmann, Michael; Bucciero, Alberto; Fanini, Bruno; Graf, Holger; Pescarin, Sofia; Rizvic, Selma
    In cultural heritage, portrait paintings and busts are special genres of artworks which are used to show the appearance and expression of a human subject. The purpose of such artwork is to serve as remembrance of the person who is depicted in that portrait or bust. The bust can moreover serve as a 3D representation of a portrait painting. Therefore, it would be interesting to stylize a portrait painting based on a specific bust, i.e. the generation of a 2D image of a bust corresponding to the person depicted in the portrait image. In this paper, we analyze and discuss the stylization of portrait paintings and photographs of human faces with busts using a deep learning based style transfer approach. To capture the characteristics in the appearance of busts, we created a novel dataset of busts and used DualStyleGAN for the use cases of stylizing portrait paintings and stylizing human faces based on our novel bust style. Our experiments show the potential of this approach. Stylizing human faces as busts might not only be appealing to experts that might save time and effort for generating an initial stylization to refine later on, but also increase the engagement of novice users and exhibition visitors with cultural heritage.