Eurographics Digital Library
Not a member yet
17121 research outputs found
Sort by
Discussion and Showcase of an Implementation of Task Taxonomies in Visualizations Based on the Dust and Magnet Metaphor
No full textIn order to visualize multivariate data, it is often necessary to reduce their dimensionality. Visualizations based on the Dust and Magnet metaphor aim to present the information of the reduced dimensions via interactivity, while also supporting user comprehension by using a metaphor of ferrous dust and magnets. We compare two approaches to implementing this metaphor into a visualization tool along a set of core visualization tasks and propose extensions to make such visualizations more comprehensible and less misleading.EuroVis 2025 - PostersPosters and Demo
Determining a General CH Digitization Process Based on a Scoping Review
No full textThe digitization of cultural heritage (CH) serves a range of critical purposes, including preservation, accessibility, research, and education. It also plays a key role in raising public awareness about the value of cultural assets, while fostering community engagement through thoughtfully developed digital heritage initiatives. This paper presents a qualitative analysis based on a scoping review of recent CH digitization literature, aiming to identify and synthesize key themes and approaches. The findings are clustered and abstracted to outline core steps in the digitization process, forming a structured framework. For each step, associated tasks and guiding questions are defined to support implementation. This process-oriented overview offers practical value for the planning and execution of new digitization projects. It also provides strategic guidance on resource allocation and stakeholder engagement, including timing, methods, and rationale for involving communities, tourism sectors, and other relevant actors.Digital HeritageInfrastructures, Platforms and Digital Ecosystem
Grace Notes and Ghost Data: Challenges in Digitising Intangible Cultural Heritage
No full textThis paper explores the challenges of digitizing intangible cultural heritage (ICH) through a focused study of Uilleann pipe performance using motion capture technology. While traditional Irish piping is rich in expressive micro-movements and ornamentation-such as grace notes, triplets, and subtle finger lifts-these nuanced gestures often fall below the detection threshold of standard motion capture systems. Drawing on empirical data collected at the Na Píobairí Uilleann headquarters, this study reflects on both the technical and conceptual issues encountered in translating embodied cultural practices into digital form. Key concerns include magnetic interference, sensor limitations, and the complexity of capturing expressivity that is not always visually pronounced but musically essential. The paper argues that such "ghost data"-the movements that are performed but incompletely captured-highlights broader tensions between the ephemeral nature of ICH and the technological imperative to document, preserve, and replicate. By critically engaging in these challenges, the research contributes to ongoing debates around authenticity, embodiment, and the role of digital tools in safeguarding living traditions.Digital HeritagePoster
Generative Motion Infilling from Imprecisely Timed Keyframes
No full textKeyframes are a standard representation for kinematic motion specification. Recent learned motion-inbetweening methods use keyframes as a way to control generative motion models, and are trained to generate life-like motion that matches the exact poses and timings of input keyframes. However, the quality of generated motion may degrade if the timing of these constraints is not perfectly consistent with the desired motion. Unfortunately, correctly specifying keyframe timings is a tedious and challenging task in practice. Our goal is to create a system that synthesizes high-quality motion from keyframes, even if keyframes are imprecisely timed. We present a method that allows constraints to be retimed as part of the generation process. Specifically, we introduce a novel model architecture that explicitly outputs a time-warping function to correct mistimed keyframes, and spatial residuals that add pose details. We demonstrate how our method can automatically turn approximately timed keyframe constraints into diverse, realistic motions with plausible timing and detailed submovements.Computer Graphics ForumBringing Motion to Life: Motion Reconstruction and Control44
PaMO: Parallel Mesh Optimization for Intersection-Free Low-Poly Modeling on the GPU
No full textReducing the triangle count in complex 3D models is a basic geometry preprocessing step in graphics pipelines such as efficient rendering and interactive editing. However, most existing mesh simplification methods exhibit a few issues. Firstly, they often lead to self-intersections during decimation, a major issue for applications such as 3D printing and soft-body simulation. Second, to perform simplification on a mesh in the wild, one would first need to perform re-meshing, which often suffers from surface shifts and losses of sharp features. Finally, existing re-meshing and simplification methods can take minutes when processing large-scale meshes, limiting their applications in practice. To address the challenges, we introduce a novel GPUbased mesh optimization approach containing three key components: (1) a parallel re-meshing algorithm to turn meshes in the wild into watertight, manifold, and intersection-free ones, and reduce the prevalence of poorly shaped triangles; (2) a robust parallel simplification algorithm with intersection-free guarantees; (3) an optimization-based safe projection algorithm to realign the simplified mesh with the input, eliminating the surface shift introduced by re-meshing and recovering the original sharp features. The algorithm demonstrates remarkable efficiency, simplifying a 2-million-face mesh to 20k triangles in 3 seconds on RTX4090. We evaluated the approach on the Thingi10K dataset and showcased its exceptional performance in geometry preservation and speed. https://seonghunn.github.io/pamo/Computer Graphics ForumShape Extraction44
Enhancing Apple Variety Testing with Ontology-Enriched Visual Analytics: A Decision-Support Framework
No full textIn this work, we propose an ontology-driven visual analytics approach to support apple variety testing by integrating heterogeneous data sources, including climate records and both qualitative and quantitative agronomic observations. Our methodology includes the development of the Apple Trait Ontology, which standardizes trait definitions and enhances semantic interoperability during data integration, and the implementation of an interactive visual analytics system. This system offers an in-depth overview of apple variety performance over the years by examining key attributes-such as red over color, size, firmness, acidity, starch content, and sugar levels-along with other qualitative and quantitative characteristics. By leveraging ontology-enriched data structuring, the system enables expert-driven interpretation of variety performance, providing a comprehensive decision-support tool for agricultural domain experts. The apple variety-testing visual analytics system integrates spatiotemporal analytics, multimodal visual representations, and interactive filtering, allowing users to explore trait performance trends, climate resilience, and overall suitability under different environmental conditions. The findings demonstrate that combining semantic models with visual analytics enhances the accessibility and usability of complex agricultural data, ultimately improving breeding strategies and decision-making in apple variety selection. This research contributes to the broader field of agricultural informatics by showcasing the potential of knowledge-based systems to support precision farming.Workshop on Visualisation in Environmental Sciences (EnvirVis)Session
Parallel Dense-Geometry-Format Topology Decompression
No full textDense Geometry Format (DGF) [BBM24] is a hardware-friendly representation for compressed triangle meshes specifically designed to support GPU hardware ray tracing. It decomposes a mesh into meshlets, i.e., small meshes with up to 64 positions, triangles, primitive indices, and opacity values, in a 128-byte block. However, accessing a triangle requires a slow sequential decompression algorithm with O(T) steps, where T is the number of triangles in a DGF block. We propose a novel parallel algorithm with O(logT) steps for arbitrary T. For DGF, where T ≤ 64, we transform our algorithm to allow O(1) access. We believe that our algorithm is suitable for hardware implementations. With our algorithm, a custom intersection shader outperforms the existing serial decompression method. Further, our mesh shader implementation achieves competitive rasterization performance with the vertex pipeline. Finally, we show how our method may parallelize other topology decompression schemes.Eurographics 2025 - Short PapersShort Paper
Brain Car: Un videojuego controlado por actividad cerebral para gestionar el estrés
No full textLa ansiedad es un problema mundial para el que el 75% de las personas no recibe tratamiento. Con el fin de ayudar a la prevención de este trastorno, se ha desarrollado un videojuego de conducción que pretende reducir el estrés entrenando la concentración. El juego consta de dos niveles en los que la velocidad máxima de un coche depende de la concentración del usuario. El primero implementa un modelo de control absoluto en trayectoria predefinida; y el segundo, un modelo híbrido en entorno de exploración tridimensional. El videojuego ha sido evaluado a través de un estudio piloto con 20 participantes, cuyos resultados han destacado el impacto positivo del entrenamiento atencional a través del videojuego en la reducción del estrés.Spanish Computer Graphics Conference (CEIG)Short Paper
PC-NCLaws: Physics-Embedded Conditional Neural Constitutive Laws for Elastoplastic Materials
No full textWhile data-driven methods offer significant promise for modeling complex materials, they often face challenges in generalizing across diverse physical scenarios and maintaining physical consistency. To address these limitations, we propose a generalizable framework called Physics-Embedded Conditional Neural Constitutive Laws for Elastoplastic Materials, which combines the partial differential equations with neural networks. Specifically, the model employs two separate neural networks to model elastic and plastic constitutive laws. Simultaneously, the model incorporates physical parameters as conditional inputs and is trained on comprehensive datasets encompassing multiple scenarios with varying physical parameters, thereby enabling generalization across different properties without requiring retraining for each individual case. Furthermore, the differentiable architecture of our model, combined with its explicit parameter inputs, enables the inverse estimation of physical parameters from observed motion sequences. This capability extends our framework to objects with unknown or unmeasured properties. Experimental results demonstrate state-of-the-art performance in motion reconstruction, robust long-term prediction, geometry generalization, and precise parameters estimation for elastoplastic materials, highlighting its versatility as a unified simulator and inverse analysis tool.Pacific Graphics Conference Papers, Posters, and DemosPhysical Simulatio
StructuReiser: A Structure-preserving Video Stylization Method
No full textWe introduce StructuReiser, a novel video-to-video translation method that transforms input videos into stylized sequences using a set of user-provided keyframes. Unlike most existing methods, StructuReiser strictly adheres to the structural elements of the target video, preserving the original identity while seamlessly applying the desired stylistic transformations. This provides a level of control and consistency that is challenging to achieve with text-driven or keyframe-based approaches, including large video models. Furthermore, StructuReiser supports real-time inference on standard graphics hardware as well as custom keyframe editing, enabling interactive applications and expanding possibilities for creative expression and video manipulation.Computer Graphics ForumStylization and Image Processing44