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Beyond the Prototype: Challenges of Long-Term Integration of Visual Analytics in Civic Spaces
No full textDespite the recognized benefits of visual analytics systems in supporting data-driven decision-making, their deployment in realworld civic contexts often faces significant barriers. Beyond technical challenges such as resource constraints and development complexity, sociotechnical factors-including organizational hierarchies, misalignment between designers and stakeholders, and concerns around technology adoption hinder their sustained use. In this work, we reflect on our collective experiences of designing, developing, and deploying visual analytics systems in the civic domain and discuss challenges across design and adoption aspects. We emphasize the need for deeper integration strategies, equitable stakeholder engagement, and sustainable implementation frameworks to bridge the gap between research and practice.VisGap - The Gap between Visualization Research and Visualization SoftwarePaper Session
Scalable Force Scheme: a fast method for projecting large datasets
No full textGlobal dimensionality reduction (DR) methods are widely used to project high-dimensional data into a low-dimensional representation, preserving the overall structure of the dataset. Global nonlinear DR techniques allow one to capture complex features of the data but are limited by their high computational cost, making them an unfeasible choice to process large datasets. Force scheme (FS) is one of the most popular of such examples, being adopted in a wide variety of domains, but limiting its application to small datasets. In this paper, we extend FS to improve its convergence quality and speed, by introducing several concepts from gradient descent (GD) theory and lowering its algorithmic complexity. Our new proposed method is less prone to generate distorted projections due to the presence of artifacts, while significantly improving the running times, allowing for nonlinear global DR projections of large datasets.EuroVis Workshop on Visual Analytics (EuroVA)Visual Analytics Methods and Approache
3DGM: Deformable and Texturable 3D Gaussian Model via Level-of-Detail Proxy
No full text3D Gaussian Splatting has markedly impacted neural rendering by achieving impressive fidelity and performance. Despite this achievement, it is not readily applicable to developing interactive applications. Real-time applications like XR apps and games require functions such as animation, UV mapping and level of detail (LOD) simultaneously manipulated through a 3D model. To address this need, we propose a modelling strategy analogous to typical 3D models, which we call 3D Gaussian Model (3DGM). 3DGM relies on attaching 3D Gaussians on the triangles of a mesh proxy, and the key idea is to bind sheared 3D Gaussians in texture space and re-projecting them back to world space through implicit shell mapping; this design naturally enables deformation and UV mapping via the proxy. Further, to optimize speed and fidelity based on different viewing distances, each triangle can be tessellated to change the number of involved 3D Gaussians adaptively. Application-wise, we will show that our proxy-based 3DGM is capable of enabling novel deformation without animated training data, texture transferring via UV mapping of the 3D Gaussians, and LOD rendering. The results indicate that our model achieves better fidelity for deformation and better optimization of fidelity and performance given different viewing distances. Further, we believe the results indicate the potential of our work for enabling interactive applications for 3D Gaussian Splatting.Computer Graphics ForumOriginal Article44
SUPQA: LLM-based Geo-Visualization for Subjective Urban Performance Question-Answering
No full textAs urbanization accelerates, urban performance has become a growing concern, impacting every aspect of residents' lives. However, urban performance exploration is a tedious and highly subjective process for users. Users need to manually collect and integrate various information, or spend a large amount of time and effort due to the steep learning curves of existing specialized tools. To address these challenges, we introduce SUPQA, a novel approach for urban performance exploration using natural language as input and interactive geographic visualizations as output. Our approach leverages Large Language Models (LLMs) to effectively interpret user intents and quantify various urban performance measures. We integrate progressive navigation and multi-geographic scale analysis in our visualization system, explaining the reasoning process and streamlining users' decision-making workflow. Two usage scenarios and evaluations demonstrate the effectiveness of SUPQA in helping residents and planners acquire desired information more efficiently and enhancing the quality of decision-making.Computer Graphics ForumAI-Enhanced Visualizatio
Rendering Success - An Evaluation of Cheat Sheets for a Third-year Computer Graphics and Image Processing Course
No full textStudent-created cheat sheets, also called crib sheets, exam notes, or reference sheets, have been used to reduce exam anxiety, de-emphasise memorisation, and enable students to focus on high level learning. Previous work has identified properties of cheat sheets which correlate with exam performance and has shown conflicting results about the benefits of cheat sheets for different subjects. However, no such study has been conducted for more advanced courses requiring knowledge from different fields and different representations, such as a text, (API) code, formulas, and images. In this research we investigate which characteristics of student cheat sheets predict exam performance for a third-year Computer Graphics and Image Processing course. We analyse exam results with reference to the cheat sheets and questions of different levels of Bloom's taxonomy, and we discuss implications for students and instructors. We found that higher exam scores are correlated with a better coverage of course material and more formulas. Having many example questions with sample solutions and missing lecture topics was correlated with lower grades. We found a correlation between several of our metrics and performance in questions related to Bloom's ''Apply'' category. We suggest that students should be taught how to identify key lecture concepts, how to represent them (source code vs. formulas), and how to use them in exams.Eurographics 2025 - Education PapersEducation
Learning Proper Object Spacing with Polygon Rendering for Layout Rearrangement
No full textSuccessful scene arrangement requires ensuring appropriate distances between objects and avoiding excessive overlaps or separations. This work proposes a method for automatically learning spatial relationships between objects in scene arrangement using a differentiable renderer loss. First, objects surrounding a dominant item (e.g., a table in a dining room) are identified and represented as nodes in a polygon that encodes their spatial relations. The difference between the predicted and ground truth polygons is minimized via a rendering loss, which is integrated into the training of a generative diffusion model. This approach continuously optimizes the spatial distribution of objects during generation, ensuring physical consistency and practical usability. Experimental results show a significant reduction in collision rates compared to state-of-the-art methods.Eurographics 2025 - PostersPoster
Guided Visual Analysis of Time Series Data with Spiral Views and View Quality Measures
No full textSeasonal variations in energy consumption and temperature, like many other time series, exhibit periodically repeating patterns. Identifying and analyzing these cyclic patterns is crucial for understanding underlying trends and predicting future behavior. Spiral visualizations are commonly used to highlight periodicity, as they intuitively arrange seasonal data in spirals. We introduce encompassing user-guided enhancements to spiral visualizations, supporting the search and analysis of patterns in cyclic time series. A key element is a parameter space visualization by an interactive heat map, which highlights important quality measures, such as similarity and monotonicity, across different segments of the spiral. This approach helps users efficiently locate areas of interest that meet specific criteria, thereby streamlining the discovery of significant patterns. To further support analysis, the system offers a linked stacked area or line chart representation of selected segments, providing a clearer understanding of the quality measures. The effectiveness of the quality measures is demonstrated by use cases on several datasets.EuroVis Workshop on Visual Analytics (EuroVA)Visual Analytics Methods and Approache
Burger Charts: A Quantitative Display of Set Intersections
No full textWe present Burger Charts, a quantitative display of set intersections that stack the contributing sets on top of each other. Sets are represented as horizontal layers. The size of each set intersection is encoded by the width of its layer section, forming a vertically stacked, burger-like visual representation. A visual skewer maintains the unity of the burger by bridging gaps of those set layers that do not contribute to the intersection. The color coding of the sets emphasizes which set contributes to which intersection. We use Burger Charts to visualize and analyze keyword co-occurrences of an argument search engine. They support a quantitative discourse analysis by providing insights into the distribution of sets of keyword occurrences. Users can interactively explore keywords of online discourses on controversial topics, identify prevalent keyword co-occurrences, and even uncover overlooked perspectives.EuroVis 2025 - Short PapersSystems and Application
Real-time Image-based Lighting of Glints
No full textImage-based lighting is a widely used technique to reproduce shading under real-world lighting conditions, especially in realtime rendering applications. A particularly challenging scenario involves materials exhibiting a sparkling or glittering appearance, caused by discrete microfacets scattered across their surface. In this paper, we propose an efficient approximation for image-based lighting of glints, enabling fully dynamic material properties and environment maps. Our novel approach is grounded in real-time glint rendering under area light illumination and employs standard environment map filtering techniques. Crucially, our environment map filtering process is sufficiently fast to be executed on a per-frame basis. Our method assumes that the environment map is partitioned into few homogeneous regions of constant radiance. By filtering the corresponding indicator functions with the normal distribution function, we obtain the probabilities for individual microfacets to reflect light from each region. During shading, these probabilities are utilized to hierarchically sample a multinomial distribution, facilitated by our novel dual-gated Gaussian approximation of binomial distributions. We validate that our real-time approximation is close to ground-truth renderings for a range of material properties and lighting conditions, and demonstrate robust and stable performance, with little overhead over rendering glints from a single directional light. Compared to rendering smooth materials without glints, our approach requires twice as much memory to store the prefiltered environment map.Computer Graphics ForumReal-Time Rendering44
Novel Documentation and Identification Methods for Combating Illicit Trafficking of Cultural Goods - ENIGMA Pilot Case Studies
No full textThe EU-funded ENIGMA project develops innovative methods and tools to enhance cultural heritage safeguarding, protection, and provenance management, specifically targeting the illicit trafficking of cultural goods. This paper presents two initial pilot case studies that evaluate and validate the project's developments. Pilot Case 1 focuses on novel documentation of museum items using the Unique Authenticity Identifier to improve traceability. Pilot Case 2 investigates the identification and tracking of unregistered cultural goods by employing advanced technologies and AI to uncover connections with known inventoried objects. The pilots scrutinize operational scenarios, user profiles, and initial object selection consisting of figurines from the Royal Museums of Art and History (KMKG). Preliminary findings suggest ENIGMA tools demonstrate their potential as a prototype solution, with resilient and adaptable workflows for various user groups. Future work includes integrating the complete tool suite into the ENIGMA Decision Support Platform and implementing further pilot cases.Digital HeritageDigital Tools for Monitoring Heritage at Ris