The present study is a component of a doctoral thesis on Neolithic settlements in Western France, approached through digital modelling. Although 3D technologies are already employed in the research on megalithic architecture, their utilisation on settlement site is still relatively rare. This investigation focused on the southern coast of Ile d'Yeu and the prehistoric barred spur site, la Pointe de la Tranche. The site was excavated from 2010 to 2013, revealing two Late Neolithic enclosures. New fieldwork, including a drone video survey, was added to the data collected during this campaign. The results of this study corroborate and expand upon those of previous investigations, particularly with regard to the different modules utilised in the construction process. The initial hypothesis that existing data could create 3D scenes for new information was partially confirmed. This study's innovation lies in its scale and site type, suggesting further investigation into data reuse and the necessity of the modelling of certain structures.
This Poster (accompanying demos) presents an overview of creative approaches and considerations in the design research process of exploring different feelings of immersion and presence through Augmented Reality with headmounted devices in a museum. It shows ongoing work in the EU-funded project LoGaCulture (Locative Games in Cultural Heritage), in particular in the practical research that develops case studies for a Natural History museum. We summarise design criteria, concepts and prototypical implementations regarding the qualities of presence, playfulness and usability.
Dancing through Time is an interactive installation created to discover the Prix de Lausanne archive, a collection of dance performance recordings over fifty-one years. It consists of a 4k-touch screen mounted on a twelve-meter rail, allowing visitors to walk through the fifty-one editions of the Prix de Lausanne dance competition. This paper presents the installation and the results of an extensive evaluation of users' questionnaires. Our main findings validate Dancing through Time in terms of User Experience and User Engagement, indicating that receiving prior instructions only affects the latter. Furthermore, the interaction logs with the application inform us of the benefits of browsing through the entire collection thanks to the affordances of the interactive system. Finally, we extracted different users' interaction behaviours to understand better how visitors engaged with Dancing through Time in the situated context of the 2024 edition of the Prix.
Tablet computers like the iPad are user-friendly and reliable interaction devices for displaying XR content in museums. Although they are lacking the stereo view of a VR headset, they also avoid the hygiene, optics and usability challenges of head mounted displays in public spaces. In our paper we describe methods to improve the shortcomings of these devices: Placement, presentation and distracting branding. Our solution is a combination of a physical hanging system and custom designed acrylic cases disguising the hardware. In our example of an exhibition about a baroque architect the result is a series of floating baroque picture frames which users are grabbing and rotating to view into the XR scenes.
Cultural heritage is continuously subject to numerous risk factors that threaten and compromise its integrity, hence the need to activate effective risk mitigation practices. Increasingly, digital methodologies are contributing to this field, which enables the combination of operations for documentation, preservation, and enhancement of cultural heritage. The same techniques can be profitably and equally applied for now lost objects reconstruction: together with verified historical sources, using these technologies would allow the recovery of models as consistent and faithful. Based on this meta disciplinary approach between historical-philological research and digital technologies, a reconstruction project of the so-called armor of Theoderic is proposed. Different workflows and the data collected and produced will be made explicitly open, allowing cooperation processes in an Open Science perspective. This first 3D model of the so-called armor of Theoderic may be the basis for multiple possible uses to make an iconic object of great cultural significance usable again to the public and the scientific community.
Image-based 3D reconstruction is a commonly used technique for measuring the geometry and color of objects or scenes based on images. While the geometry reconstruction of state-of-the-art approaches is mostly robust against varying lighting conditions and outliers, these pose a significant challenge for calculating an accurate texture map. This work proposes a deep-learning based texturing approach called "DeepTex" that uses a custom learned blending method on top of a traditional mosaic-based texturing approach. The model was trained using a custom synthetic data generation workflow and showed a significantly increased accuracy when generating textures in the presence of outliers and non-uniform lighting.
Digital technologies are increasingly used in cultural heritage preservation and dissemination, but some monuments pose significant challenges due to substantial historical architectural and pictorial changes. This paper introduces a method to enrich multi-layered, multi-phase 3D models of cultural heritage with art history knowledge. This is achieved through imagebased annotations, interactive narratives, points of interest, text, and audio, creating guided tours of the monument's historical phases. The approach is user-friendly for art historians, requiring no programming skills for defining such elements. A pilot user evaluation demonstrated its effectiveness in enhancing visitor engagement and understanding, and allowed improving the final web-based application and narratives.
The Observatorio Astronomico de La Plata belonging to the Facultad de Ciencias Astronomicas y Geofisicas (FCAG) of the Universidad Nacional de La Plata (UNLP) is among the oldest astronomical institutions in South America. Its extensive collection includes thousands of spectroscopic and photographic glass plates, which were collected between the early 1900s and the 1980s by eminent Argentine astronomers. These plates represent a unique and valuable record that remains largely unpublished. In 2019, the Recuperation of Historical Observational Work (ReTrOH, for its initials in Spanish) project initiated a digitization programme to convert over 15,000 plates from the collection into digital format. Given that the manual processing of these plates is intricate, error-prone, and time-consuming, a multidisciplinary team of astronomers and computer scientists was assembled to create a software tool called PlateUNLP. This tool was specifically designed to streamline the digitization process, enhancing efficiency and reducing the potential for errors. PlateUNLP utilizes advanced signal processing and computer vision techniques to automatically identify and isolate each spectrum captured on the plates, attaching the relevant metadata and thus limiting the need for manual intervention. The system is released as open-source software, allowing for broad accessibility. While PlateUNLP was tailored to meet the demands of the ReTrOH project, its adaptable design makes it suitable for digitizing many other plate collections around the world.
Colour is considered a representative characteristic of material cultural heritage pieces, especially when documenting them. Especially under digitalization processes, colour needs to be handled and preserved with care, given that digital tools may introduce uncontrolled variations in its representation, if not irreversibly lose it to certain degrees. This work aims to present an empirical workflow in order to successfully respect colour integrity when performing photogrammetry as a cultural heritage documentation asset. An experimental battery based on different combinations of acquisition conditions, RGB debayering, calibration and photogrammetry is presented, and based on the most successful parameters, conclusions are drawn for building guidelines for the optimum performance. The fact that control must be held over all processes to avoid undesired losses of information has been regarded as the highest priority, with the sole exception of the unpredictable colour blending operations during the proper photogrammetry. This paper ultimately demonstrates that preservation of colour information can be achieved on an excellent degree, and that having control over the factors of acquisition and colour digitalization parameters contributes to its success.
The whole of Italy is characterized by small towns at risk of complete depopulation with a widespread and remarkable cultural heritage. These places, still little known and valued, are the testimony of the unique way of living and inhabiting the places belonging to the multifaceted wealth of Made in Italy. The work focuses on the knowledge and rediscovery of local materials and construction techniques using digital tools as a driver of sustainable development and resilience of small communities according to new models of the circular economy. The paper presents some preliminary results of research activities aimed at developing a proof-of-concept of Building Heritage Materials Passport (BHMPs) for the case study of the incannucciata construction technique found in the Rabatana, the ancient Arab district of the little town of Tursi in the Province of Matera (Basilicata, Italy).
MiDRASH is an international effort that aims to construct a groundbreaking interdisciplinary methodology for a global approach to the study of the treasure trove of medieval literary manuscripts in Hebrew script. It studies materiality, textuality, transmission and historical contexts of the digitized manuscripts in Hebrew, Aramaic, Judeo-Arabic and other vernacular languages.
This paper presents a project focused on enhancing cultural heritage experiences through a WebXR application by integrating generative AI characters. The application, designed for the Fichtelgebirge region in Upper Franconia, Germany, offers users an immersive digital time travel experience within a museum setting. Structured into six interconnected scenes, each representing a different historical period, the WebXR tour features AI-enhanced historic characters that interactively narrate stories and showcase artifacts. Key elements include animated speaking portraits, interactive 3D models, 360-degree panoramas, and style-transferred historic imagery. The project aims to connect physical museum objects with virtual experiences, enriching the user's engagement with local culture and regional identity. Compatible with multiple devices, including VR headsets, web browsers, and mobile devices, the application ensures broad accessibility and cross-media functionality.
Studying works that have completely or partially disappeared is always difficult due to the lack of information. In more fortunate scenarios where photographs were taken before the destruction, the study of the piece is limited by the viewpoints captured in the available photographs. In this interdisciplinary research, we present a new methodology for reconstructing lost altarpieces from a single historical image, utilizing differentiable rendering techniques. We test our methodology by reconstructing some reliefs from the altarpiece of Sant Joan Baptista (Valls, Spain), which was destroyed in 1936. These results are valuable for both experts and the public, as they facilitate a better understanding of the relief's volumetrics and their spatial relationships, representing a significant advancement in the virtual recovery of lost artifacts.
As Digital Ancient Near Studies (DANES) and Ancient Language Processing (ALP) require larger volumes of annotated documents, we focus on automatically computed graphical annotations for cuneiform tablets, which are among the oldest documents spanning at least three millennia of human history. Cuneiform consists of wedges imprinted on clay tablets, which are best captured by high-resolution 3D acquisition. Existing Open Access 3D models are therefore our data base and have been postprocessed by the GigaMesh software framework, which ensures clean meshes and provides MSII filter responses. This refers to the Gaussian curvature, which is a function value for each vertex of the mesh used for watersheds along the 2D manifold. Watershed labels are determined by non-minimum suppression using a merge parameter. The label contours, i.e., the polygonal lines enclosing the wedges, are smoothed using the Savitzky-Golay filter with the goal of projecting a low-poly line in 2D that can be quickly corrected by the image-based annotation tool known as Cuneur, which allows experts to annotate wedges, signs and semantics. Once the wedges have been determined, wedge types can be automatically proposed using the orientation of the wedges, which is the first step towards a paleographic representation of cuneiform signs, known as PaleoCode.
This proposal explores AR applications with engaging interaction patterns to provide immersive and entertaining museum experiences. Focusing on cultural heritage, this demonstration showcases innovative interaction patterns for navigation and exhibit activation. The navigation interaction pattern uses dynamic visual and auditory cues, while the exhibit activation interaction pattern incorporates playful orca-inspired elements. Implemented in Unity3D and deployed on HoloLens 2, the demonstration effectively balances usability and entertainment, enhancing visitor engagement and showcasing new AR possibilities for museums.
Archaeological artifacts are often only preserved in fragments. Their reassembly is thus a common task for conservators and archaeologists. Unfortunately, this reassembly process is anything but trivial. Major complicating factors are given if fragments are (1) eroded and weathered, (2) incomplete and missing, and (3) expose little to no geometric surface features or surface-color variations. Artifacts made of white marble, which was generally used in antiquity, pose an additional challenge for reassembly due to (4) their weight and (5) the fragility of the crystalline material. This holds for both freestanding marble sculptures and relief stones or otherwise decorated slabs. In this work, we focus on the reassembly problem of marble slabs with a flat surface, for which fragments are pre-oriented such that their top faces point upward. While computer-based reassembly algorithms exist, they are typically tuned for specific types of artifacts and rely on joining fragments based on a combination of a geometric and surface-color correspondence. Hence, methods that reassemble broken and deteriorated white marble slabs typically perform worse than the respective domain experts. Due to the foreseeable shortcomings of reassembly algorithms when applied to eroded, incomplete, and widely feature-less white marble fragments, we refrain from designing an algorithm for the specific problem at hand. Instead, we incorporate a large number of users from the broad public in the reassembly process. To that end, we provide an intuitive interactive web platform that allows users access to 3D digital twins of the Christian marble-slab fragments. Transferring the fragments to the virtual domain also enables the introduction of algorithmic automatisms to assist the users in the process. In this paper, we present the system design and the provided basic geometric automatisms, and report on their efficiency and utilization in an ongoing large-scale citizen-science experiment that involves several thousand users.
LanternOperAR is a hybrid gift designed to engage with Yue Opera in a handheld experience. With a physical installation and a digital application, users can interact with cultural content through meaningful visualizations and gamified interaction. In this paper, we detail the design process, including the methodologies for processing, analyzing, and presenting cultural data, as well as the presenting the physical prototype. Our evaluation supplies empirical evidence and practical guidelines on designing hybrid gifts that transcend traditional cultural products to promote cultural heritage in interactive experiences. It provides valuable insights to researchers and practitioners in the cultural application area.
Multi-Light Image Collections (MLICs) are often transformed into geometric normals and BRDF normals for visual exploration under novel illumination. However, discrepancies between the chosen BRDF space and the complete optical behavior of objects, along with the possible presence of non-local lighting effects in measurements, often lead to sub-optimal visual outcomes even with the most accurate geometric normal recovery. In this paper, we introduce a modular component designed to convert the geometric normals into well-behaved shading normals, under the common and general assumption that the reflectance must be a monotonic function of the angle between the shading normal and the bisector of lighting and viewing directions. Since it does not require the coupling of shape and material estimation, the module allows seamless integration into existing reconstruction pipelines, supporting the mixing and matching of Photometric Stereo methods, BRDF models, and BRDF fitters. The performance and versatility of the approach are demonstrated through experiments.
In this demonstration description, a prototype is presented that addresses the problem of isolation caused by single-user Augmented Reality (AR) applications used on cultural heritage (CH) sites. Using Microsoft's HoloLens 2 and Android smartphones, multiple visitors can experience the playful AR space together. Visitors follow a virtual guide together whereby authors can customize to how many users the system reacts, and engage in a labeling game in which visitors can collaboratively match Latin names and human bones to physical vertebrates' bones.
We present DeepHadad, a novel deep learning approach to improve the readability of severely damaged ancient Northwest Semitic inscriptions. By leveraging concepts of displacement maps and image-to-image translation, DeepHadad effectively recovers text from barely recognizable inscriptions, such as the one on the Hadad statue. A main challenge is the lack of pairs of well-preserved and damaged glyphs as training data since each available glyph instance has a unique shape and is not available in different states of erosion. We overcome this issue by generating synthetic training data through a simulated erosion process, on which we then train a neural network that successfully generalizes to real data. We demonstrate significant improvements in readability and historical authenticity compared to existing methods, opening new avenues for AI-assisted epigraphic analysis.
