Eurographics Digital Library
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17121 research outputs found
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Beyond Entertainment: An Investigation of Externalization Design in Video Games
No full textThis article investigates when and how video games enable players to create externalizations in a diverse sample of 388 video games. We follow a grounded-theory approach, extracting externalizations from video games to explore design ideas and relate them to practices in visualization. Video games often engage players in problem-solving activities, like solving a murder mystery or optimizing a strategy, requiring players to interpret heterogeneous data-much like tasks in the visualization domain. In many cases, externalizations can help reduce a user's mental load by making tangible what otherwise only lives in their head, acting as external storage or a visual playground. Over five coding phases, we created a hierarchy of 277 tags to describe the video games in our collection, from which we extracted 169 externalizations. We characterize these externalizations along nine dimensions like mental load, visual encodings, and motivations, resulting in 13 categories divided into four clusters: quick access, storage, sensemaking, and communication. We formulate considerations to guide future work, looking at tasks and challenges, naming potentials for inspiration, and discussing which topics could advance the state of externalization.Computer Graphics ForumSports, Gaming, and Behavioral Pattern
A Data-Driven Approach to Analytical Dwivedi Guiding
No full textPath tracing remains the gold standard for high-fidelity subsurface scattering despite requiring numerous paths for noisefree estimates. We introduce a novel variance-reduction method based on two complementary zero-variance-theory-based approaches. The first one, analytical Dwivedi sampling, is lightweight but struggles with complex lighting. The second one, surface path guiding, learns incident illumination at boundaries to guide sampled paths, but it does not reduce variance from subsurface scattering. In our novel method, we enhance Dwivedi sampling by incorporating the radiance field learned only at the volume boundary. We use the average normal of points on an illuminated boundary region or directions sampled from distributions of incident light at the boundary as our analytical Dwivedi slab normals. Unlike previous methods based on Dwivedi sampling, our method is efficient even in scenes with complex light rigs typical for movie production and under indirect illumination. We achieve comparable noise reduction and even slightly improved estimates in some scenes compared to volume path guiding, and our method can be easily added on top of any existing surface path guiding system. Our method is particularly effective for homogeneous, isotropic media, bypassing the extensive training and caching inside the 3D volume that volume path guiding requires.Computer Graphics ForumSampling and Guiding44
Alias-Free Shadows with Ray Cones for Alpha Tested Geometry
No full textWe present a method for computing alias-free, smooth shadows for alpha-tested geometry using a single ray per pixel. Without mipmap filtering, hard shadows from alpha-tested geometry appear very noisy under camera motion. Typically, many ray samples are required to soften the shadows and reduce noise. We propose using mipmaps instead, to achieve a fast and temporally stable solution. To determine the appropriate mipmap level, we introduce novel ray cone operations that account for directional and point light sources.Vision, Modeling, and VisualizationReal-Time Renderin
I.PaC and semantic graphs to represent Italian Cultural Heritage
No full textI.PaC (Infrastructure and Services for Cultural Heritage) [CN23] is the technological core of the National Digital Ecosystem for Culture - Ecomic, an initiative developed within Italy's National Recovery and Resilience Plan (PNRR). It is designed to support the management, enrichment, and accessibility of digital cultural resources, and it is developed not merely as a data repository but as an advanced infrastructure that enables new models of interaction and valorization of cultural heritage. I.PaC represents the central hub of the ecosystem and it integrates and connects heterogeneous systems, allowing cultural institutions to ingest, manage, and reuse digital data through a comprehensive range of services. The infrastructure also provides services for digital asset management (DAM) and advanced content processing, allowing institutions to optimize digitization processes and improving the quality of their metadata. A key feature of I.PaC is the use of domain-specific and cross-domain graphs: these graphs allow to create relationships between cultural objects from different fields (archival, bibliographic, museum, and multimedia), enabling cross-domain navigation and a richer reconstruction of cultural contexts. On one hand the domain-specific graphs serve as vertical, in-depth models that structure and organize all the relevant information within each cultural sector. They ensure a high level of specialization and interoperability, since they are based on national and international description standard, and they enhance metadata thanks to AI technologies based on entity recognition, disambiguation, and data enrichment. Each domain graph retains its internal logic while benefiting from a shared semantic foundation. On the other hand, the cross-domain knowledge graph provides a transversal representation of information about cultural heritage, by modeling common entities and their relationships, which can then be reused across all domain-specific graphs. This approach enables the integration of information from traditionally separate disciplines, revealing unexpected connections. By implementing I.PaC's semantic graphs, Italy's cultural institutions can transition from static data repositories to dynamic, knowledge-driven platforms, creating new opportunities for accessibility and valorization.Digital HeritageData Analysis, Datasets and Multimodal Approache
WebGraphViz: A WebGL-Based Interactive Graph Visualization Tool for Retail Analytics
No full textThe growing volume and complexity of data from sources like social media, IoT systems, and security devices highlight the need for scalable, high-performance visualization tools. Traditional web technologies such as SVG and Canvas often struggle with large datasets, limiting interactivity. We present WebGraphViz, a WebGL-based graph visualization tool that leverages GPU parallelism to overcome these limitations. Performance evaluations across three interaction experiments in both high- and low-performance environments show that WebGraphViz significantly outperforms its SVG-based counterpart, enabling smooth exploration of large-scale graph data.EuroVis 2025 - PostersPoster
High-Resolution LiDAR for Archaeological Prospection in Mediterranean Forested Landscapes: Insights from Two Case Studies in Italy
No full textThis paper presents the results of two high-resolution airborne LiDAR surveys carried out in Mediterranean forested environments with rich archaeological potential. These case studies, located in southern Tuscany and within the presidential estate of Castel Porziano near Rome, illustrate the value of LiDAR-based approaches for identifying and interpreting cultural landscapes that are otherwise obscured by dense vegetation. In the Tuscan case study, which includes the ancient settlement of Roselle and the nearby hill of Moscona, UAV-mounted LiDAR sensors were employed to acquire data over an area of approximately 550 hectares. The resulting point clouds, with an average density of 750 points per square meter, allowed for the detection of subtle topographic features and archaeological structures, including buried walls, road systems, and necropolises. The complexity of the dataset required the development of a multi-stage processing pipeline, combining deep learning techniques and semantic segmentation to differentiate ground surfaces, vegetation, and structural elements, ultimately leading to the creation of detailed Digital Terrain and Feature Models (DTMs and DFMs). Conversely, the Castel Porziano survey covered a large protected area with limited modern disturbance and dense coastal vegetation. While the LiDAR dataset was acquired via manned airborne platforms due to legal and logistical restrictions on drone flights, the results proved equally rich in archaeological information. The high-resolution data enabled a diachronic interpretation of the landscape and revealed patterns of land use, infrastructural networks, and traces of earlier human occupation previously undocumented due to the site's inaccessibility and forest coverage. While the technological setup differed between the two contexts, particularly with regard to drone deployment, the central role of high-resolution LiDAR remains consistent. The comparison between these case studies highlights how adaptable and powerful LiDAR technology can be in supporting archaeological research in forested Mediterranean environments. Moreover, the integration of computational techniques such as AI-driven classification and multi-resolution analysis provides scalable solutions for managing large datasets and improving archaeological feature extraction. This contribution emphasizes not only the methodological advancements enabled by LiDAR and AI integration but also the importance of interdisciplinary collaboration between archaeologists, remote sensing specialists, and data scientists. It offers a flexible framework applicable to other Mediterranean contexts where environmental constraints, dense vegetation, and heritage protection pose challenges to traditional archaeological methods.Digital HeritageAnalysing and Documenting Sites and Landscape
Challenges in the Development, Distribution, and Maintenance of Software Visualization Tools in Biology and Medicine
No full textSoftware visualizations remain and will continue to serve as an important tool for domain scientists in order to advance, communicate, and investigate science. In this paper, we present our findings on a case study of the challenges involved with specialized visualization software. Through this case study, we provide insights into why building software and tools for scientists is challenging. We provide several recommendations at the end of our work in order to progress forward the ability to improve software quality when developing critical software visualization tools in domains such as biology and medicine. Key Learnings: For tools that require integration and/or implementation of multiple programming languages 1) start early with the development on all target platforms and 2) look for where to reimplement a function rather than bring in code with many extraneous dependencies.VisGap - The Gap between Visualization Research and Visualization SoftwarePaper Session
ClothingTwin: Reconstructing Inner and Outer Layers of Clothing Using 3D Gaussian Splatting
No full textWe introduce ClothingTwin, a novel end-to-end framework for reconstructing 3D digital twins of clothing that capture both the outer and inner fabric -without the need for manual mannequin removal. Traditional 2D ''ghost mannequin'' photography techniques remove the mannequin and composite partial inner textures to create images in which the garment appears as if it were worn by a transparent model. However, extending such method to photorealistic 3D Gaussian Splatting (3DGS) is far more challenging. Achieving consistent inner-layer compositing across the large sets of images used for 3DGS optimization quickly becomes impractical if done manually. To address these issues, ClothingTwin introduces three key innovations. First, a specialized image acquisition protocol captures two sets of images for each garment: one worn normally on the mannequin (outer layer exposed) and one worn inside-out (inner layer exposed). This eliminates the need to painstakingly edit out mannequins in thousands of images and provides full coverage of all fabric surfaces. Second, we employ a mesh-guided 3DGS reconstruction for each layer and leverage Non-Rigid Iterative Closest Point (ICP) to align outer and inner point-clouds despite distinct geometries. Third, our enhanced rendering pipeline-featuring mesh-guided back-face culling, back-to-front alpha blending, and recalculated spherical harmonic angles-ensures photorealistic visualization of the combined outer and inner layers without inter-layer artifacts. Experimental evaluations on various garments show that ClothingTwin outperforms conventional 3DGS-based methods, and our ablation study validates the effectiveness of each proposed component.Computer Graphics ForumDigital Clothing44
Exploring the Geometry of Swarm Intelligence: Negative Inertia and Ellipsoidal Search Space Evolution in PSO
No full textThis paper introduces a geometry-aware method for analyzing swarm behavior in Particle Swarm Optimization (PSO) based on ellipsoidal modeling. Inspired by the n-ball hitting probability, we propose an abstraction of the search space covered by particles over time. Using principal component analysis (PCA), we approximate the particle distribution at each iteration with ellipsoids, enabling a visual and quantitative assessment of how well the swarm explores and concentrates its search effort. We apply this technique to investigate a PSO variant with negative inertia weights, which has shown promising performance in prior empirical analysis. While negative inertia may appear counterintuitive, our ellipsoidal analysis reveals that it introduces oscillatory search dynamics that balance exploration and exploitation more effectively than standard strategies such as constant inertia or linear decreasing inertia. Our experiments include a six-dimensional medical image registration task and an illustrative two-dimensional Rastrigin function, which serves to visually demonstrate how the swarm structure evolves. The proposed analysis framework provides new insight into swarm dynamics and offers a tool for understanding and comparing the behavior of PSO variants beyond conventional performance metrics.Vision, Modeling, and VisualizationGeometry, Simulation, and Optimizatio