[ { "id": "komon-2025-dco", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/224640", "title": "Data-Driven Compute Overlays for Interactive Geographic Simulation and Visualization", "date": "2025-12-30", "abstract": "We present interactive data-driven compute overlays for native and web-based 3D geographic map applications based on WebGPU. Our data-driven overlays are generated in a multi-step compute workflow from multiple data sources on the GPU. We demonstrate their potential by showing results from snow cover and avalanche simulations, where simulation parameters can be adjusted interactively and results are visualized instantly. Benchmarks show that our approach can compute large-scale avalanche simulations in milliseconds to seconds, depending on the size of the terrain and the simulation parameters, which is multiple orders of magnitude faster than a state-of-the-art Python implementation.", "authors_et_al": false, "substitute": null, "main_image": { "description": "Rendered 2.5D terrain with avalanche simulation output as overlay, color encodes velocity.", "filetitle": "Teaser image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 2527, "image_height": 1270, "name": "komon-2025-dco-Teaser image.png", "type": "image/png", "size": 3968804, "path": "Publication:komon-2025-dco", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/komon-2025-dco/komon-2025-dco-Teaser image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/komon-2025-dco/komon-2025-dco-Teaser image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1859, 1869, 1013, 1110 ], "booktitle": "2025 IEEE Visualization and Visual Analytics (VIS)", "date_from": "2025-11-01", "date_to": "2025-11-07", "doi": "10.1109/VIS60296.2025.00043", "event": "IEEE VIS 2025", "isbn": "979-8-3315-6613-5", "lecturer": [ 1869 ], "location": "Vienna", "pages": "5", "pages_from": "186", "pages_to": "190", "publisher": "IEEE", "research_areas": [], "keywords": [ "3D geographic visualization", "geographic simulation", "WebGPU" ], "weblinks": [ { "href": "https://arxiv.org/abs/2506.23364", "caption": "Paper preprint", "description": null, "main_file": 1 }, { "href": "https://webigeo.alpinemaps.org/", "caption": "Online demo", "description": null, "main_file": 1 }, { "href": "https://youtu.be/pZq0H_l-8Bs?t=1580", "caption": "Talk recording", "description": null, "main_file": 0 }, { "href": "https://github.com/weBIGeo/webigeo", "caption": "GitHub repository", "description": null, "main_file": 0 } ], "files": [ { "description": "Rendered 2.5D terrain with avalanche simulation output as overlay, color encodes velocity.", "filetitle": "Teaser image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 2527, "image_height": 1270, "name": "komon-2025-dco-Teaser image.png", "type": "image/png", "size": 3968804, "path": "Publication:komon-2025-dco", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/komon-2025-dco/komon-2025-dco-Teaser image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/komon-2025-dco/komon-2025-dco-Teaser image:thumb{{size}}.png" } ], "projects_workgroups": [ "d9555" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/komon-2025-dco/", "__class": "Publication" }, { "id": "miklautsch_florian-baa", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "First-time Localization of Scans", "date": "2025-12-30", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 414, "image_height": 616, "name": "miklautsch_florian-baa-image.png", "type": "image/png", "size": 406923, "path": "Publication:miklautsch_florian-baa", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/miklautsch_florian-baa/miklautsch_florian-baa-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/miklautsch_florian-baa/miklautsch_florian-baa-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5466 ], "co_supervisor": [ 948 ], "date_end": "2025-12-30", "date_start": "2025-04-07", "matrikelnr": "12023974", "supervisor": [ 193 ], "research_areas": [ "Geometry" ], "keywords": [ "slam", "registration", "mobile" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 414, "image_height": 616, "name": "miklautsch_florian-baa-image.png", "type": "image/png", "size": 406923, "path": "Publication:miklautsch_florian-baa", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/miklautsch_florian-baa/miklautsch_florian-baa-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/miklautsch_florian-baa/miklautsch_florian-baa-image:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "miklautsch_florian-baa-thesis.pdf", "type": "application/pdf", "size": 862347, "path": "Publication:miklautsch_florian-baa", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/miklautsch_florian-baa/miklautsch_florian-baa-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/miklautsch_florian-baa/miklautsch_florian-baa-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "WorldScale" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/miklautsch_florian-baa/", "__class": "Publication" }, { "id": "xmas-2025", "type_id": "xmascard", "tu_id": null, "repositum_id": null, "title": " X-Mas Card 2025", "date": "2025-12-24", "abstract": "The Research Unit of Computer Graphics wishes you a Merry Christmas with this brilliantly illuminated Christmas tree.\nIts temperature field is simulated using GPU-accelerated photon tracing: millions of perfectly traced rays\ncontributing to a radiative transport operator driving a non-linear Newton-Raphson solver. In this season of light, let us\ncelebrate the beauty that emerges when physics meets festive geometry, Monte Carlo convergence brings tidings of joy,\nand your RTX card finally earns its keep doing something other than training yet another diffusion model. Wishing you\nlow RMSE in your experiments, convergence in your solvers, and just enough noise to make the magic feel real.\nMerry Christmas and a radiantly rendered New Year!", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "name": "xmas-2025-image.jpg", "type": "image/jpeg", "size": 669944, "path": "Publication:xmas-2025", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/xmas-2025/xmas-2025-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/xmas-2025/xmas-2025-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5496, 1128, 1946 ], "research_areas": [], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "card", "main_file": true, "use_in_gallery": false, "access": "public", "name": "xmas-2025-card.pdf", "type": "application/pdf", "size": 2292169, "path": "Publication:xmas-2025", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/xmas-2025/xmas-2025-card.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/xmas-2025/xmas-2025-card:thumb{{size}}.png" }, { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "name": "xmas-2025-image.jpg", "type": "image/jpeg", "size": 669944, "path": "Publication:xmas-2025", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/xmas-2025/xmas-2025-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/xmas-2025/xmas-2025-image:thumb{{size}}.png" } ], "projects_workgroups": [ "rend" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/xmas-2025/", "__class": "Publication" }, { "id": "lanzarotti-2025-viseps", "type_id": "journalpaper", "tu_id": null, "repositum_id": "20.500.12708/225225", "title": "VisEPS: a visual explorer of parameter spaces for networked models", "date": "2025-12-23", "abstract": "Simulations of complex social systems, such as those represented by epidemiological models, have been very useful in supporting decision makers during the last pandemic. These models generally comprise a high number of parameters, which makes it hard to identify the values that best reproduce the empirical data. Furthermore, different combinations of parameters may achieve a good fit, which renders an automatic solution ill-suited to the task. A human expert is required to make the final decisions about the optimal parameter values. We present VisEPS (Visual Explorer of Parameter Spaces), a framework for visually analyzing the effects of a very large set of parameters, with the aim of fitting a geographically explicit networked model to data obtained during the COVID-19 pandemic. We use a networked extension of a susceptible-infected-recovered (SIR) model to reproduce the epidemic dynamics in the city of Buenos Aires and its neighboring interconnected districts. We overlay binned scatterplots on a map, which facilitates the visual identification of each district and its connections. To further explore the model’s performance against data, additional views, such as parallel coordinates and histograms, along with drill-down mechanisms, have been incorporated. Finally, a use case is described in which the level of connectivity between districts is included in the analysis. The identification of suitable parameter ranges is facilitated by an iterative and incremental process, whereby new sets of simulations are incrementally requested, guided by interactive visual inspections. This permits the exploration of a parameter space that would otherwise be impossible to fully explore.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": "20.500.12708/225781", "authors": [ 5537, 235, 5538, 166, 5539 ], "date_from": "2025-07-03", "date_to": "2025-07-04", "doi": "10.1007/s12650-025-01093-2", "event": "The 2nd Japan Visualization Symposium (JapanVis 2025)", "issn": "1875-8975", "journal": "Journal of Visualization", "lecturer": [ 235 ], "location": "Tokyo", "pages": "15", "publisher": "SPRINGER", "research_areas": [], "keywords": [ "Interactive visual exploration", "Networked simulation models", "Scalable visual parameter tuning", "Visual model parameter fitting" ], "weblinks": [], "files": [], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/lanzarotti-2025-viseps/", "__class": "Publication" }, { "id": "sakai-2025-stater", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/222799", "title": "Statistical Error Reduction for Monte Carlo Rendering", "date": "2025-12-14", "abstract": "Denoising is an important post-processing step in physically based Monte Carlo (MC) rendering. While neural networks are widely used in practice, statistical analysis has recently become a viable alternative for denoising. In this paper, we present a general framework for statistics-based error reduction of both estimated radiance and variance. Specifically, we introduce a novel denoising approach for variance estimates, which can either improve variance-aware adaptive sampling or provide additional input for image denoising in a cascaded manner. Furthermore, we present multi-transform denoising: a general and efficient correction scheme for non-normal distributions, which typically occur in MC rendering. All these contributions combine to a robust denoising pipeline that does not require any pretraining and can run efficiently on current GPU hardware. Our results show distinct advantages over previous denoising methods, especially in the range of a few hundred samples per pixel, which is of high practical relevance. Finally, we demonstrate good convergence behavior as the number of samples increases, providing predictable results with low bias that are free of hallucinated neural artifacts. In summary, our statistics-based algorithms for adaptive sampling and denoising deliver fast, consistent, low-bias variance and radiance estimates.", "authors_et_al": false, "substitute": null, "main_image": { "description": "“Veach, Bidir Room” scene by Benedikt Bitterli, dedicated to the public domain under CC0 1.0 Universal (https://benedikt-bitterli.me/resources/).", "filetitle": "Representative Image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1500, "image_height": 1000, "name": "sakai-2025-stater-Representative Image.png", "type": "image/png", "size": 711915, "path": "Publication:sakai-2025-stater", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/sakai-2025-stater/sakai-2025-stater-Representative Image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/sakai-2025-stater/sakai-2025-stater-Representative Image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1129, 1128, 193, 1946 ], "booktitle": "Proceedings of the SIGGRAPH Asia 2025 Conference Papers", "date_from": "2025-12-15", "date_to": "2025-12-18", "doi": "10.1145/3757377.3763995", "event": "SIGGRAPH Asia 2025 Conference", "isbn": "979-8-4007-2137-3", "lecturer": [ 1129 ], "location": "Hong Kong", "open_access": "yes", "pages": "12", "pages_from": "1", "pages_to": "12", "publisher": "ACM", "research_areas": [ "Rendering" ], "keywords": [ "Monte Carlo rendering", "path tracing", "denoising", "image filtering", "statistics" ], "weblinks": [ { "href": "https://www.cg.tuwien.ac.at/StatER", "caption": "Project Page", "description": null, "main_file": 1 } ], "files": { "0": { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": true, "access": "public", "name": "sakai-2025-stater-paper.pdf", "type": "application/pdf", "size": 10120331, "path": "Publication:sakai-2025-stater", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/sakai-2025-stater/sakai-2025-stater-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/sakai-2025-stater/sakai-2025-stater-paper:thumb{{size}}.png" }, "1": { "description": "“Veach, Bidir Room” scene by Benedikt Bitterli, dedicated to the public domain under CC0 1.0 Universal (https://benedikt-bitterli.me/resources/).", "filetitle": "Representative Image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1500, "image_height": 1000, "name": "sakai-2025-stater-Representative Image.png", "type": "image/png", "size": 711915, "path": "Publication:sakai-2025-stater", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/sakai-2025-stater/sakai-2025-stater-Representative Image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/sakai-2025-stater/sakai-2025-stater-Representative Image:thumb{{size}}.png" }, "3": { "description": null, "filetitle": "Supplementary Document", "main_file": true, "use_in_gallery": false, "access": "public", "name": "sakai-2025-stater-Supplementary Document.pdf", "type": "application/pdf", "size": 29341520, "path": "Publication:sakai-2025-stater", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/sakai-2025-stater/sakai-2025-stater-Supplementary Document.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/sakai-2025-stater/sakai-2025-stater-Supplementary Document:thumb{{size}}.png" } }, "projects_workgroups": [ "d9259" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/sakai-2025-stater/", "__class": "Publication" }, { "id": "stauss-2025-gfd", "type_id": "talk", "tu_id": null, "repositum_id": "20.500.12708/225556", "title": "Green Facade Digital Twin : GreenFDT", "date": "2025-11-28", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5429, 5548, 1303, 5549, 5550, 5551, 1799 ], "date_from": "2025-11-28", "date_to": "2025-11-28", "event": "GCD Symposium on Geometry and Computational Design 2025 (GCD_25)", "lecturer": [ 5429, 1799 ], "location": "Wien", "research_areas": [], "keywords": [ "Green Facades", "Digital Twin" ], "weblinks": [], "files": [], "projects_workgroups": [ "d10070" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/stauss-2025-gfd/", "__class": "Publication" }, { "id": "gruber-2025-vps", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Visualising the Permutation Space", "date": "2025-11-11", "abstract": "Seriations, i.e. arranging multidimensional data in a list that follows a logical sequence, are part of a technique called Exploratory Data Analysis. They reduce dimensions\nand give experts a way to assess images and other complex data, enabling them to compare their content and find similarities and differences. But only a few are used at a\nregular basis, e.g. the historgram seriation. The tool described here tries to add a more wholesome approach by showing all possible seriations in the permutation space. The\nspace grows factorially with the input size, i.e. the number of pixels, and by far not all are meaningful. The goal is to look for patterns in the space, as patterns may indicate\nfurther interesting seriations beside the historgram ones. The question is whether one is able to see such patterns when ordering the permutations and/or comparing two ordered\nspaces. Based on mathematical findings and algorithmic constraints, it will be shown that some patterns can be found even in a simplified setting using images with a size of\n3-by-2.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5517 ], "date_end": "2025-11-11", "date_start": "2025-04-19", "matrikelnr": "00121092", "supervisor": [ 166 ], "research_areas": [ "IllVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "Bachelor thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "gruber-2025-vps-Bachelor thesis.pdf", "type": "application/pdf", "size": 1805314, "path": "Publication:gruber-2025-vps", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/gruber-2025-vps/gruber-2025-vps-Bachelor thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/gruber-2025-vps/gruber-2025-vps-Bachelor thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 312, "image_height": 356, "name": "gruber-2025-vps-image.png", "type": "image/png", "size": 29267, "path": "Publication:gruber-2025-vps", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/gruber-2025-vps/gruber-2025-vps-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/gruber-2025-vps/gruber-2025-vps-image:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/gruber-2025-vps/", "__class": "Publication" }, { "id": "wolter-2025-mdv", "type_id": "talk", "tu_id": null, "repositum_id": "20.500.12708/225940", "title": "Multi-Agent Data Visualization and Narrative Generation", "date": "2025-11-03", "abstract": "Recent advancements in the field of AI agents have impacted the way we work, enabling greater automation and collaboration between humans and agents. In the data visualization field, multiagent systems can be useful for employing agents throughout the entire data-to-communication pipeline. We present a lightweight multi-agent system that automates the data analysis workflow, from data exploration to generating coherent visual narratives for insight communication. Our approach combines a hybrid multi-agent architecture with deterministic components, strategically externalizing critical logic from LLMs to improve transparency and reliability. The system delivers granular, modular outputs that enable surgical modifications without full regeneration, supporting sustainable human-AI collaboration. We evaluated our system across 4 diverse datasets, demonstrating strong generalizability, narrative quality, and computational efficiency with minimal dependencies.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5534, 5552, 5553, 5554, 1892 ], "date_from": "2025-11-03", "date_to": "2025-11-03", "event": "1st Workshop on Logo GenAI, Agents, and the Future of VIS (IEEE VIS 2025)", "lecturer": [ 5534 ], "location": "Vienna", "research_areas": [], "keywords": [ "Multiagentensystem" ], "weblinks": [], "files": [], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/wolter-2025-mdv/", "__class": "Publication" }, { "id": "dhanoa-2025-ave", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/225028", "title": "Agentic Visualization: Extracting Agent-Based Design Patterns From Visualization Systems", "date": "2025-11", "abstract": "Autonomous agents powered by large language models are transforming artificial intelligence (AI), creating an imperative for the visualization area. However, our field's focus on a human in the sensemaking loop raises critical questions about autonomy, delegation, and coordination for such agentic visualization that preserve human agency while amplifying analytical capabilities. This article addresses these questions by reinterpreting existing visualization systems with semiautomated or fully automatic AI components through an agentic lens. Based on this analysis, we extract a collection of design patterns for agentic visualization, including agentic roles, communication, and coordination. These patterns provide a foundation for future agentic visualization systems that effectively harness AI agents while maintaining human insight and control.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": "abstract,projects", "repositum_presentation_id": null, "authors": [ 1892, 5534, 5535, 5536, 5434 ], "doi": "10.1109/MCG.2025.3607741", "issn": "1558-1756", "journal": "IEEE Computer Graphics and Applications", "number": "6", "pages": "12", "pages_from": "89", "pages_to": "100", "publisher": "IEEE COMPUTER SOC", "volume": "45", "research_areas": [], "keywords": [ "agents", "visualization", "design patterns" ], "weblinks": [], "files": [], "projects_workgroups": [ "d10027" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/dhanoa-2025-ave/", "__class": "Publication" }, { "id": "north-2025-aog", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/221703", "title": "Analysis of the GPU Acceleration Potential of the FFT-Based Pressure Solver in the PALM-4U Model System", "date": "2025-11", "abstract": "Due to climate change, the frequency and severity of extreme weather events is increasing, which endangers human livelihoods and key infrastructures. Decision support tools can guide the development of climate-resilient cities by providing information on the potential effectiveness of specific measures during the planning process. In urban environments,decision support tools that incorporate accurate micro-climate models are particularly effective. PALM-4U, a state-of-the-art, scientifically validated microclimate model, could offer this functionality, however it remains largely inaccessible outside the scientific community as it is optimised to run on HPC clusters. However, with the rise of high-performance GPUs, a shift towards single workstations is possible.This study investigates the potential for performance increase of the PALM-4U’s pressuresolver, by utilising the GPU’s acceleration potential in combination with a change intarget architecture. Performance increase is measured using three parameters: speed up,validity (via NMSE, R, and FB), and memory efficiency. Also the effect on the runtime of the full simulation is measured and possible bottlenecks identified. Finally, the fullmodel is analysed to assess the overall feasibility of GPU optimisation, providing insights to guide future development.The pressure solver transforms the 3D Poisson equation using Fast Fourier Transform and solves the resulting 1D system via the Thomas algorithm. The code structure is optimised, CUDA-optimised kernels are implemented and the cuFFT library is integrated.In addition a mixed-precision approach is tested to evaluate its impact on performance and accuracy.The single core GPU implementation achieves a speed up of up to 65.5 times in single precision and up to 49.3 times for double precision for large domain sizes. The stability of the system remains unaffected by the mixed-precision approach, and no significant variation is observed between FP32 and FP64 runs. After 45 × 103 simulation steps, NMSE (0.02), FB (-0.017) and R (0.96), demonstrate a stable and accurate performance consistent across precisions. Additionally, the memory requirement is reduced up to 68% compared to the baseline CPU solver. The optimisations leads to a runtime reduction ofthe full model by 15%, demonstrating the potential for accessible, scientifically validated microclimate models.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": "date,projects", "repositum_presentation_id": null, "authors": [ 5514 ], "ac_number": "AC17718798", "date_end": "2025-11", "date_start": "2025-04", "diploma_examina": "2025-11-24", "doi": "10.34726/hss.2025.133062", "matrikelnr": "51803598", "open_access": "yes", "pages": "86", "supervisor": [ 193 ], "research_areas": [], "keywords": [ "GPU Acceleration", "Computational Fluid Dynamics", "CUDA", "Urban Microclimate Modeling", "Poisson Equation Solver", "Fast Fourier Transform", "Mixed-Precision Methods", "Climate-Resilient Urban Planning" ], "weblinks": [], "files": [ { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "north-2025-aog-thesis.pdf", "type": "application/pdf", "size": 2124368, "path": "Publication:north-2025-aog", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/north-2025-aog/north-2025-aog-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/north-2025-aog/north-2025-aog-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "VRVis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/north-2025-aog/", "__class": "Publication" }, { "id": "weydemann-2025-noo", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/221804", "title": "Non-uniform offsetting of surfaces", "date": "2025-11", "abstract": "Offset surfaces are fundamental in computer graphics applications, such as computer-aided design or tool-path generation. However, generating them while preserving geometric details and handling self-intersections remains challenging, particularly for surfaces with sharp features. This thesis presents a robust method for non-uniform offset surface generation, extending volumetric, feature-preserving uniform offset approaches to allow per-vertex control over offset distances. This enables greater flexibility in handling complex geometries and user-defined specifications.To achieve a smooth distribution of offsets across the input mesh, the method introduces a Radial Basis Function interpolation combined with Dijkstra-based distance propagation. The method supports the extraction of both inner and outer offset components through an octree data structure and a modified Dual Contouring algorithm adapted for non-uniform distances, ensuring accurate and manifold surface generation. This approach's adaptability and robustness are demonstrated across diverse input models with varying offset assignments. They showcase successful extraction of inner and outer components and the ability to capture localized asymmetries while preserving geometric integrity.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1211, "image_height": 494, "name": "weydemann-2025-noo-teaser.png", "type": "image/png", "size": 321957, "path": "Publication:weydemann-2025-noo", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/weydemann-2025-noo/weydemann-2025-noo-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/weydemann-2025-noo/weydemann-2025-noo-teaser:thumb{{size}}.png" }, "sync_repositum_override": "date,projects", "repositum_presentation_id": null, "authors": [ 5531 ], "ac_number": "AC17720179", "date_end": "2025-11-24", "date_start": "2016-08-11", "diploma_examina": "2025-11-24", "doi": "10.34726/hss.2025.40588", "matrikelnr": "00925369", "open_access": "yes", "pages": "92", "supervisor": [ 193 ], "research_areas": [ "Geometry" ], "keywords": [ "Offset Surfaces", "Non-Uniform Offset", "Volumetric Method", "Octree", "Dual Contouring", "Radial Basis Function", "Per-Vertex Control", "k-d Tree", "Signed Distance Field", "Computer Graphics" ], "weblinks": [], "files": [ { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1211, "image_height": 494, "name": "weydemann-2025-noo-teaser.png", "type": "image/png", "size": 321957, "path": "Publication:weydemann-2025-noo", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/weydemann-2025-noo/weydemann-2025-noo-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/weydemann-2025-noo/weydemann-2025-noo-teaser:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "weydemann-2025-noo-thesis.pdf", "type": "application/pdf", "size": 1778290, "path": "Publication:weydemann-2025-noo", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/weydemann-2025-noo/weydemann-2025-noo-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/weydemann-2025-noo/weydemann-2025-noo-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "rend" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/weydemann-2025-noo/", "__class": "Publication" }, { "id": "oda-2025-artevoviewer", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/225534", "title": "ArtEvoViewer: A System for Visualizing Interpersonal Influence Among Painters", "date": "2025-10-31", "abstract": "Large-scale and objective painting analyses have recently gained attention. In particular, analyzing influence between individual painters requires substantial effort and is hard to reproduce due to subjectivity. Despite increasing demand for automatic estimation, this remains unresolved because such influence is complex and often directional, making it difficult to model. In this paper, we develop an interactive system that visualizes, manipulates, and analyses chains of painterly influence as a network. Using 32,401 paintings, the system infers directional links from color and brushstroke features. The resulting network based on color style features captures stylistic lineages such as landscape-focused and portrait-focused streams, while a multifaceted analysis of Picasso shows that Cézanne's impact appears in brushwork rather than color. Our contributions are twofold: (1) the use of an evolutionary model to assign explicit direction to painter influence and support art historical interpretation, and (2) providing a visualization system that allows dynamic comparison of influence networks based on multiple image features.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5544, 5545, 1813, 1850, 166, 1410, 1754 ], "booktitle": "2025 29th International Conference Information Visualisation (IV)", "date_from": "2025-08-05", "date_to": "2025-08-08", "doi": "10.1109/IV68685.2025.00041", "event": "29th International Conference Information Visualisation (IV)", "isbn": "979-8-3315-7741-4", "lecturer": [ 5544 ], "location": "Darmstadt", "pages": "6", "pages_from": "171", "pages_to": "176", "publisher": "IEEE", "research_areas": [], "keywords": [ "artist influence estimation", "cultural evolution", "digital humanities", "paintings", "system", "visualization" ], "weblinks": [], "files": [], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/oda-2025-artevoviewer/", "__class": "Publication" }, { "id": "tekaya-2025-amo", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/221607", "title": "A Matter of Time: Revealing the Structure of Time in Vision-Language Models", "date": "2025-10-27", "abstract": "Large-scale vision-language models (VLMs) such as CLIP have gained popularity for their generalizable and expressive multimodal representations. By leveraging large-scale training data with diverse textual metadata, VLMs acquire open-vocabulary capabilities, solving tasks beyond their training scope. This paper investigates the temporal awareness of VLMs, assessing their ability to position visual content in time. We introduce TIME10k, a benchmark dataset of over 10,000 images with temporal ground truth, and evaluate the time-awareness of 37 VLMs by a novel methodology. Our investigation reveals that temporal information is structured along a low-dimensional, non-linear manifold in the VLM embedding space. Based on this insight, we propose methods to derive an explicit ''timeline'' representation from the embedding space. These representations model time and its chronological progression and thereby facilitate temporal reasoning tasks. Our timeline approaches achieve competitive to superior accuracy compared to a prompt-based baseline while being computationally efficient. All code and data are available at https://tekayanidham.github.io/timeline-page/.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1536, "image_height": 458, "name": "tekaya-2025-amo-teaser.png", "type": "image/png", "size": 4646052, "path": "Publication:tekaya-2025-amo", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/tekaya-2025-amo/tekaya-2025-amo-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/tekaya-2025-amo/tekaya-2025-amo-teaser:thumb{{size}}.png" }, "sync_repositum_override": "date,keywords,projects", "repositum_presentation_id": null, "authors": [ 5330, 1110, 5370 ], "booktitle": "MM '25: Proceedings of the 33rd ACM International Conference on Multimedia", "date_from": "2025-10-27", "date_to": "2025-10-31", "doi": "10.1145/3746027.3758163", "event": "ACM International Conference on Multimedia 2025", "isbn": "979-8-4007-2035-2", "lecturer": [ 5330 ], "location": "Dublin", "open_access": "yes", "pages": "10", "pages_from": "12371", "pages_to": "12380", "research_areas": [ "InfoVis" ], "keywords": [ "Multimodal representations", "Vision-language models", "Time modeling", "Time estimation", "Benchmark dataset" ], "weblinks": [ { "href": "https://tekayanidham.github.io/timeline-page/", "caption": null, "description": null, "main_file": 1 } ], "files": [ { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1536, "image_height": 458, "name": "tekaya-2025-amo-teaser.png", "type": "image/png", "size": 4646052, "path": "Publication:tekaya-2025-amo", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/tekaya-2025-amo/tekaya-2025-amo-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/tekaya-2025-amo/tekaya-2025-amo-teaser:thumb{{size}}.png" } ], "projects_workgroups": [ "d9522", "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/tekaya-2025-amo/", "__class": "Publication" }, { "id": "kazda-tmd", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Design and Implementation of an AI-Based Edge Device for Automated Traffic Counting", "date": "2025-10-27", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 239, "image_height": 137, "name": "kazda-tmd-image.png", "type": "image/png", "size": 53206, "path": "Publication:kazda-tmd", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/kazda-tmd/kazda-tmd-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/kazda-tmd/kazda-tmd-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5474 ], "co_supervisor": [ 948 ], "date_end": "2025-10-27", "date_start": "2025-02-28", "matrikelnr": "11909468", "supervisor": [ 193 ], "research_areas": [ "Geometry" ], "keywords": [ "traffic supervision", "object detection", "vehicle classification" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 239, "image_height": 137, "name": "kazda-tmd-image.png", "type": "image/png", "size": 53206, "path": "Publication:kazda-tmd", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/kazda-tmd/kazda-tmd-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/kazda-tmd/kazda-tmd-image:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "kazda-tmd-thesis.pdf", "type": "application/pdf", "size": 1131160, "path": "Publication:kazda-tmd", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/kazda-tmd/kazda-tmd-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/kazda-tmd/kazda-tmd-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "WorldScale" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/kazda-tmd/", "__class": "Publication" }, { "id": "hofmann_julia-2025", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Visualization of Points of Interest in 3D Digital Maps", "date": "2025-10-21", "abstract": "Landmarks are central to spatial orientation, yet the design of landmarks in rural environments has not been investigated so far. This thesis investigates how landmark visualization modes should be designed to support spatial exploration and landmark comprehension on rural 3D maps. A modular, web-based prototype integrates Points of Interest (PoIs) from OpenStreetMap in an asynchronous preprocessing pipeline that cleans, categorizes, and partitions data for client-side use. A quadtree-based data management approach provides dynamic level-of-detail (LoD) to regulate density and maintain legibility across scales. Within this framework, interchangeable visualization modes (text labels, abstract symbols, pictorial icons, 3D models, and heatmaps) are implemented on a 3D terrain map of Austria, complemented by category-based filtering and details-on-demand interactions.\nThe thesis combines system design with a literature-grounded analysis to articulate the trade-offs among these modes. The resulting guidance emphasizes scale-dependent staging of encodings, control of density before the introduction of detail, and a task-and scale-sensitive balance between abstraction and realism, with semantics exposed\nthrough lightweight interaction rather than persistent annotation. The contributions are twofold: a functional technical framework that operationalizes landmark visualization for rural 3D terrain, and a structured synthesis that clarifies when and why particular visualization methods are advantageous. Evaluation proceeds theoretically rather than through user studies, and the thesis outlines implications and hypotheses for future empirical validation.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 792, "image_height": 585, "name": "hofmann_julia-2025-teaser.png", "type": "image/png", "size": 892799, "path": "Publication:hofmann_julia-2025", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/hofmann_julia-2025/hofmann_julia-2025-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/hofmann_julia-2025/hofmann_julia-2025-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5499 ], "date_end": "2025-10-04", "date_start": "2024-10-23", "matrikelnr": "11827004", "supervisor": [ 1110, 1937 ], "research_areas": [], "keywords": [], "weblinks": [ { "href": "https://github.com/JulesC99/landmark-visualization", "caption": "GitHub", "description": null, "main_file": 1 } ], "files": [ { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 792, "image_height": 585, "name": "hofmann_julia-2025-teaser.png", "type": "image/png", "size": 892799, "path": "Publication:hofmann_julia-2025", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/hofmann_julia-2025/hofmann_julia-2025-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/hofmann_julia-2025/hofmann_julia-2025-teaser:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "hofmann_julia-2025-thesis.pdf", "type": "application/pdf", "size": 113508424, "path": "Publication:hofmann_julia-2025", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/hofmann_julia-2025/hofmann_julia-2025-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/hofmann_julia-2025/hofmann_julia-2025-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "abteilung" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/hofmann_julia-2025/", "__class": "Publication" }, { "id": "harisch-mvs", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Measuring vehicle speed with video", "date": "2025-10-14", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 458, "image_height": 255, "name": "harisch-mvs-image.png", "type": "image/png", "size": 186667, "path": "Publication:harisch-mvs", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/harisch-mvs/harisch-mvs-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/harisch-mvs/harisch-mvs-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5472 ], "co_supervisor": [ 948 ], "date_end": "2025-10-14", "date_start": "2025-03-14", "matrikelnr": "11705361", "supervisor": [ 193 ], "research_areas": [ "Geometry" ], "keywords": [ "speed measurement", "traffic supervision", "vehicle detection" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 458, "image_height": 255, "name": "harisch-mvs-image.png", "type": "image/png", "size": 186667, "path": "Publication:harisch-mvs", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/harisch-mvs/harisch-mvs-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/harisch-mvs/harisch-mvs-image:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "harisch-mvs-thesis.pdf", "type": "application/pdf", "size": 801019, "path": "Publication:harisch-mvs", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/harisch-mvs/harisch-mvs-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/harisch-mvs/harisch-mvs-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "WorldScale" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/harisch-mvs/", "__class": "Publication" }, { "id": "ott-rgi", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Real-Time Global Illumination for Voxel Worlds", "date": "2025-10-13", "abstract": "Achieving realistic real-time rendering of 3D worlds using path tracing remains a significant challenge due to the high sample count required for noise-free images. With voxel-worlds there are some opportunities for optimizations from its unique geometric structure. Typically, real-time applications are constrained to only a few samples per pixel, requiring additional processing to result in a noise-free image. Traditional solutions attempt to address this issue through spatial and temporal reuse of samples or other image data, but implementations frequently introduce undesirable artifacts such as blurring, ghosting, or flickering. In voxel worlds this is especially undesireable because of its sharp geometric features.\nIn this work, we explore a specialized rendering pipeline for voxel-based worlds. We adapt existing techniques to voxel geometry and use a different approach for temporal reuse in order to minimize image artifacts. We begin by generating a low-sample image using path tracing, which is then refined using temporal and spatial resampling. A simple denoiser optimized for preserving details is then applied to remove most of the noise. As a last step, our specialized approach to Temporal Anti-Aliasing (TAA) is applied, which is a central contribution of our pipeline as it removes almost all common artifacts.\nTo evaluate our approach, we conduct a series of qualitative and quantitative experiments. Visual comparisons against standard techniques show an improvement in image clarity. Performance benchmarks demonstrate that our pipeline operates within real-time constraints on modern GPUs, validating its practical applicability for interactive voxel-based applications such as video games.\nBy combining sample refinement adapted to voxel words with lightweight denoising and a data-driven TAA strategy, our method achieves realistic real-time rendering of voxel environments using path tracing with minimal artifacts.", "authors_et_al": false, "substitute": null, "main_image": { "description": "rendering of a voxel world", "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 2398, "image_height": 1219, "name": "ott-rgi-image.png", "type": "image/png", "size": 4981831, "path": "Publication:ott-rgi", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/ott-rgi/ott-rgi-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/ott-rgi/ott-rgi-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5405 ], "co_supervisor": [ 1954 ], "date_end": "2025-10-13", "date_start": "2024-11-18", "matrikelnr": "12121278", "supervisor": [ 193 ], "research_areas": [ "Rendering" ], "keywords": [ "Real-Time Rendering", "Voxels", "Global Illumination", "Ray Tracing" ], "weblinks": [], "files": [ { "description": "rendering of a voxel world", "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 2398, "image_height": 1219, "name": "ott-rgi-image.png", "type": "image/png", "size": 4981831, "path": "Publication:ott-rgi", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/ott-rgi/ott-rgi-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/ott-rgi/ott-rgi-image:thumb{{size}}.png" } ], "projects_workgroups": [ "rend" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/ott-rgi/", "__class": "Publication" }, { "id": "macho_jonas-2024-baa", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Ray traversal with omnidirectional distance fields in voxel worlds", "date": "2025-10-10", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1137, "image_height": 667, "name": "macho_jonas-2024-baa-image.jpg", "type": "image/jpeg", "size": 201809, "path": "Publication:macho_jonas-2024-baa", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/macho_jonas-2024-baa/macho_jonas-2024-baa-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/macho_jonas-2024-baa/macho_jonas-2024-baa-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5441 ], "co_supervisor": [ 948 ], "date_end": "2025-10-10", "date_start": "2024-06-28", "matrikelnr": "12122403", "supervisor": [ 193, 948 ], "research_areas": [ "Geometry", "Modeling" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1137, "image_height": 667, "name": "macho_jonas-2024-baa-image.jpg", "type": "image/jpeg", "size": 201809, "path": "Publication:macho_jonas-2024-baa", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/macho_jonas-2024-baa/macho_jonas-2024-baa-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/macho_jonas-2024-baa/macho_jonas-2024-baa-image:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "macho_jonas-2024-baa-thesis.pdf", "type": "application/pdf", "size": 1938594, "path": "Publication:macho_jonas-2024-baa", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/macho_jonas-2024-baa/macho_jonas-2024-baa-thesis.pdf", "thumb_image_sizes": [] } ], "projects_workgroups": [ "WorldScale" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/macho_jonas-2024-baa/", "__class": "Publication" }, { "id": "schrammel_sebastian_baa", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Meshing Sparse SDFs", "date": "2025-10-06", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 503, "image_height": 405, "name": "schrammel_sebastian_baa-image.png", "type": "image/png", "size": 134613, "path": "Publication:schrammel_sebastian_baa", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/schrammel_sebastian_baa/schrammel_sebastian_baa-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/schrammel_sebastian_baa/schrammel_sebastian_baa-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5385 ], "co_supervisor": [ 948 ], "date_end": "2025-10-06", "date_start": "2024-10-14", "matrikelnr": "1526197", "supervisor": [ 193 ], "research_areas": [ "Geometry" ], "keywords": [ "signed distance functions", "meshing", "sparse data structures" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 503, "image_height": 405, "name": "schrammel_sebastian_baa-image.png", "type": "image/png", "size": 134613, "path": "Publication:schrammel_sebastian_baa", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/schrammel_sebastian_baa/schrammel_sebastian_baa-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/schrammel_sebastian_baa/schrammel_sebastian_baa-image:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "schrammel_sebastian_baa-thesis.pdf", "type": "application/pdf", "size": 1326879, "path": "Publication:schrammel_sebastian_baa", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/schrammel_sebastian_baa/schrammel_sebastian_baa-thesis.pdf", "thumb_image_sizes": [] } ], "projects_workgroups": [ "WorldScale" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/schrammel_sebastian_baa/", "__class": "Publication" }, { "id": "ehlers-2025-www", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/217489", "title": "Wiggle! Wiggle! Wiggle! Visualizing uncertainty in node attributes in straight-line node-link diagrams using animated wiggliness", "date": "2025-10", "abstract": "Uncertainty is common to most types of data, from meteorology to the biomedical sciences. Here, we are interested in the visualization of uncertainty within the context of multivariate graphs, specifically the visualization of uncertainty attached to node attributes. Many visual channels offer themselves up for the visualization of node attributes and their uncertainty. One controversial and relatively under-explored channel, however, is animation, despite its conceptual advantages. In this paper, we investigate node “wiggliness”, i.e. uncertainty-dependent pseudo-random motion of nodes, as a potential new visual channel with which to communicate node attribute uncertainty. To study wiggliness’ effectiveness, we compare it against three other visual channels identified from a thorough review of uncertainty visualization literature—namely node enclosure, node fuzziness, and node color saturation. In a larger-scale, mixed method, Prolific-crowd-sourced, online user study of 160 participants, we quantitatively and qualitatively compare these four uncertainty encodings across eight low-level graph analysis tasks that probe participants’ abilities to parse the presented networks both on an attribute and topological level. We ultimately conclude that all four uncertainty encodings appear comparably useful—as opposed to previous findings. Wiggliness may be a suitable and effective visual channel with which to communicate node attribute uncertainty, at least for the kinds of data and tasks considered in our study.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1850, 1813, 5488, 5417, 1464, 1410 ], "articleno": "104290", "doi": "10.1016/j.cag.2025.104290", "issn": "1873-7684", "journal": "COMPUTERS & GRAPHICS-UK", "publisher": "PERGAMON-ELSEVIER SCIENCE LTD", "volume": "131", "research_areas": [], "keywords": [ "Network Visualization", "Uncertainty Visualization", "Animation", "Fuzziness", "Enclosure", "Saturation" ], "weblinks": [], "files": [], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/ehlers-2025-www/", "__class": "Publication" }, { "id": "komon-2025-webigeo", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/221523", "title": "weBIGeo: Interaktive Lawinensimulation im Web", "date": "2025-10", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 2556, "image_height": 1303, "name": "komon-2025-webigeo-teaser.png", "type": "image/png", "size": 5204641, "path": "Publication:komon-2025-webigeo", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/komon-2025-webigeo/komon-2025-webigeo-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/komon-2025-webigeo/komon-2025-webigeo-teaser:thumb{{size}}.png" }, "sync_repositum_override": "date,projects", "repositum_presentation_id": null, "authors": [ 1859, 1869, 5510, 5511, 5512, 5513, 1013, 1110 ], "ac_number": "AC17717665", "booktitle": "Tagungsband des 6. internationalen Lawinensymposiums", "date_from": "2025-10-18", "date_to": "2025-10-18", "doi": "10.34726/11439", "event": "6. Lawinen Symposium Graz 2025", "lecturer": [ 1859, 1110 ], "location": "Graz", "open_access": "yes", "pages": "4", "pages_from": "150", "pages_to": "153", "research_areas": [ "InfoVis", "Modeling" ], "keywords": [ "Visualisierung", "Lawinen", "3D Karten" ], "weblinks": [ { "href": "https://webigeo.alpinemaps.org/", "caption": "demo", "description": "weBIGeo demo: requires WebGPU-ready browser! ", "main_file": 1 }, { "href": "https://lawinensymposium.naturfreunde.at/", "caption": "Lawinensymposium", "description": "Lawinensymposium", "main_file": 0 } ], "files": [ { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "komon-2025-webigeo-paper.pdf", "type": "application/pdf", "size": 1611394, "path": "Publication:komon-2025-webigeo", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/komon-2025-webigeo/komon-2025-webigeo-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/komon-2025-webigeo/komon-2025-webigeo-paper:thumb{{size}}.png" }, { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 2556, "image_height": 1303, "name": "komon-2025-webigeo-teaser.png", "type": "image/png", "size": 5204641, "path": "Publication:komon-2025-webigeo", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/komon-2025-webigeo/komon-2025-webigeo-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/komon-2025-webigeo/komon-2025-webigeo-teaser:thumb{{size}}.png" } ], "projects_workgroups": [ "d9555", "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/komon-2025-webigeo/", "__class": "Publication" }, { "id": "casares-magaz-2025-rog", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/221525", "title": "Risk of genitourinary late effects after radiotherapy for prostate cancer associated with early changes in bladder shape", "date": "2025-10", "abstract": "Background and purpose: The risk of genitourinary late effects is a major dose-limiting factor in radiotherapy for prostate cancer. By using shape analysis and machine learning, the aim of this study was to evaluate whether bladder shape descriptors from the first week of treatment could identify patients experiencing genitourinary late effects.\r\nMaterial and methods: From a cohort of 258 prostate cancer patients treated with daily cone-beam computed tomography (CBCT)-guided radiotherapy (prescription doses of 77.4–81.0 Gy), 7 pre-treatment asymptomatic cases experiencing RTOG genitourinary late effects ≥Grade 2 and 21 matched controls were selected. The bladder was manually contoured on each CBCT, and a 17-D vector comprising shape descriptors was used for patient clustering, focusing on bladder contours from the first week of treatment. ANOVA was used to test statistical significance of descriptors across and within clusters.\r\nResults: Of the contours from the first week of treatment, 84 % could be classified in two main clusters with distinct bladder shape characteristics. This cluster stratification remained identical when bladder contours from the entire course of treatment were used. Convexity, elliptic variance and compactness were significantly different between patients with vs. without genitourinary late effects ≥Grade 2 (p < 0.05). Dice Coefficients between predictive models using descriptors of the first week and the voxels’ probability of belonging to the bladder were above 93 ± 6 % (median ± interquartile range).\r\nConclusion: Bladder shape descriptors in the first week of treatment showed potential to predict the risk of developing genitourinary late effects after radiotherapy for prostate cancer.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1444, 1410, 5406, 5505, 1568, 5506, 5507, 5508, 5509 ], "articleno": "100855", "doi": "10.1016/j.phro.2025.100855", "issn": "2405-6316", "journal": "Physics and Imaging in Radiation Oncology", "open_access": "yes", "pages": "5", "publisher": "Elsevier Inc.", "volume": "36", "research_areas": [], "keywords": [ "Adaptive radiotherapy", "Machine learning", "Prostate cancer radiotherapy", "Radiation-induced late effects" ], "weblinks": [], "files": [ { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "casares-magaz-2025-rog-paper.pdf", "type": "application/pdf", "size": 3013928, "path": "Publication:casares-magaz-2025-rog", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/casares-magaz-2025-rog/casares-magaz-2025-rog-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/casares-magaz-2025-rog/casares-magaz-2025-rog-paper:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/casares-magaz-2025-rog/", "__class": "Publication" }, { "id": "trenovatz-lpd", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "License Plate detection with video", "date": "2025-09-30", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 499, "image_height": 446, "name": "trenovatz-lpd-image.png", "type": "image/png", "size": 157000, "path": "Publication:trenovatz-lpd", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/trenovatz-lpd/trenovatz-lpd-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/trenovatz-lpd/trenovatz-lpd-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5473 ], "co_supervisor": [ 948 ], "date_end": "2025-09-30", "date_start": "2025-02-28", "matrikelnr": "11924505", "supervisor": [ 193, 948 ], "research_areas": [ "Geometry" ], "keywords": [ "license plate recognition", "traffic supervision", "traffic counting" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 499, "image_height": 446, "name": "trenovatz-lpd-image.png", "type": "image/png", "size": 157000, "path": "Publication:trenovatz-lpd", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/trenovatz-lpd/trenovatz-lpd-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/trenovatz-lpd/trenovatz-lpd-image:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "trenovatz-lpd-thesis.pdf", "type": "application/pdf", "size": 983093, "path": "Publication:trenovatz-lpd", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/trenovatz-lpd/trenovatz-lpd-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/trenovatz-lpd/trenovatz-lpd-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "WorldScale" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/trenovatz-lpd/", "__class": "Publication" }, { "id": "tretyak-2025-tacmedvr", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/225648", "title": "TacMedVR: Immersive VR Training for Tactical Medicine—Evaluating Interaction and Stress Response", "date": "2025-09-25", "abstract": "This paper presents the development and evaluation of a virtual reality (VR) training simulation for tactical emergency medicine, created in Unity and optimized for the Meta Quest 3 headset. The simulation places users in a high-stress scenario inspired by real knife attacks and incorporates natural hand tracking for interaction. Core training elements include triage, bleeding control, and communication with victims and bystanders. A qualitative study with ten participants, all with prior first aid or tactical medical training, explored three key research questions: (1) To what extent does the realistic recreation of real-world events affect trainees' perceived psychological stress and sense of immersion in virtual reality simulations? (2) How do hand tracking and traditional controllers compare in terms of usability? (3) How is VR perceived as a complementary or alternative method to conventional training? Thematic analysis revealed that visual and auditory realism enhanced immersion but did not consistently increase perceived stress. Hand tracking was considered intuitive but occasionally unreliable. Participants generally viewed VR as a valuable complement to traditional training, particularly for practicing workflows and rapid decision-making under pressure. The results underscore VR's potential as a scalable, engaging, and safe tool for preparing responders for high-threat environments.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": "projects", "repositum_presentation_id": null, "authors": [ 5476, 166 ], "booktitle": "2025 11th International Conference on Virtual Reality (ICVR)", "date_from": "2025-07-09", "date_to": "2025-07-11", "doi": "10.1109/ICVR66534.2025.11172647", "event": "11th International Conference on Virtual Reality (ICVR 2025)", "isbn": "979-8-3503-9273-9", "lecturer": [ 5476 ], "location": "Wageningen", "pages": "6", "pages_from": "345", "pages_to": "350", "publisher": "IEEE", "research_areas": [], "keywords": [ "Hand Tracking", "Interaction Design", "Medical Simulation", "Simulation-Based Training", "Virtual Reality in Education" ], "weblinks": [], "files": [], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/tretyak-2025-tacmedvr/", "__class": "Publication" }, { "id": "kummer-2025-fvo", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/219860", "title": "Flattening-based visualization of supine breast MRI", "date": "2025-09-22", "abstract": "We propose two novel visualization methods optimized for supine breast images that “flatten” breast tissue, facilitating examination of larger tissue areas within each coronal slice. Breast cancer is the most frequently diagnosed cancer in women, and early lesion detection is crucial for reducing mortality. Supine breast magnetic resonance imaging (MRI) enables better lesion localization for image-guided interventions; however, traditional axial visualization is suboptimal because the tissue spreads over the chest wall, resulting in numerous fragmented slices that radiologists must scroll through during standard interpretation. Using a human-centered design approach, we incorporated user and expert feedback throughout the co-design and evaluation stages of our flattening methods. Our first proposed method, a surface-cutting approach, generates offset surfaces and flattens them independently using As-Rigid-As-Possible (ARAP) surface mesh parameterization. The second method uses a landmark-based warp to flatten the entire breast volume at once. Expert evaluations revealed that the surface-cutting method provides intuitive overviews and clear vascular detail, with low metric (2–2.5%) and area (3.7–4.4%) distortions. However, independent slice flattening can introduce depth distortions across layers. The landmark warp offers consistent slice alignment and supports direct annotations and measurements, with radiologists favoring it for its anatomical accuracy. Both methods significantly reduced the number of slices needed to review, highlighting their potential for time savings and clinical impact — an essential factor for adopting supine MRI.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5500, 5501, 5502, 1410, 231 ], "ac_number": "AC17670018", "articleno": "104395", "doi": "10.1016/j.cag.2025.104395", "issn": "1873-7684", "journal": "COMPUTERS & GRAPHICS-UK", "open_access": "yes", "pages": "9", "publisher": "PERGAMON-ELSEVIER SCIENCE LTD", "volume": "133", "research_areas": [], "keywords": [ "Image reformation", "Medical visualization", "Breast imaging", "Radiology" ], "weblinks": [], "files": [ { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "kummer-2025-fvo-paper.pdf", "type": "application/pdf", "size": 3063948, "path": "Publication:kummer-2025-fvo", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/kummer-2025-fvo/kummer-2025-fvo-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/kummer-2025-fvo/kummer-2025-fvo-paper:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/kummer-2025-fvo/", "__class": "Publication" }, { "id": "huber-2025-eed", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/220017", "title": "Enhancing Environmental Data Communication Through VR", "date": "2025-09-12", "abstract": "This paper examines how environmental data can be effectively communicated to non-experts in interactive, immersive 3D spaces. Utilizing a use case centered on global spatio-temporal CO2 emissions and population dynamics over the past six decades, we explore techniques for presenting both absolute (country-level) and per capita data within meaningful spatial and temporal contexts. We developed a VR prototype visualizing these data on an interactive 3D globe and conducted a qualitative user study to evaluate its clarity and interpretability for non-expert audiences. Our findings suggest that incorporating clear geographical context, intuitive representations, and user-centered interactions can enhance engagement and certain aspects of understanding. We thereby offer a practical contribution to tackling environmental data visualization and communication in immersive environments. This promotes transparency and mitigates the risk of misinterpretation or misinformation in data communication across emerging digital media platforms.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 3835, "image_height": 1551, "name": "huber-2025-eed-teaser.PNG", "type": "image/png", "size": 4027742, "path": "Publication:huber-2025-eed", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/huber-2025-eed/huber-2025-eed-teaser.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/huber-2025-eed/huber-2025-eed-teaser:thumb{{size}}.png" }, "sync_repositum_override": "date,pages_from,pages_to", "repositum_presentation_id": null, "authors": [ 5456, 1653, 1030, 5485 ], "ac_number": "AC17672916", "booktitle": "Computer Graphics & Visual Computing (CGVC) 2025 : Eurographics UK Chapter Proceedings : Liverpool John Moores University, UK : 11 - 12 September 2025", "date_from": "2025-09-11", "date_to": "2025-09-12", "doi": "10.2312/cgvc.20251220", "event": "Computer Graphics & Visual Computing 2025 (CGVC 2025)", "isbn": "978-3-03868-293-6", "lecturer": [ 5456 ], "location": "Liverpool John Moores University", "open_access": "yes", "pages": "5", "pages_from": "1", "pages_to": "5", "publisher": "The Eurographics Association", "research_areas": [ "InfoVis", "VR" ], "keywords": [ "Human-centered computing", "User studies", "Virtual reality", "Information visualization" ], "weblinks": [], "files": [ { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "huber-2025-eed-paper.pdf", "type": "application/pdf", "size": 4585623, "path": "Publication:huber-2025-eed", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/huber-2025-eed/huber-2025-eed-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/huber-2025-eed/huber-2025-eed-paper:thumb{{size}}.png" }, { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 3835, "image_height": 1551, "name": "huber-2025-eed-teaser.PNG", "type": "image/png", "size": 4027742, "path": "Publication:huber-2025-eed", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/huber-2025-eed/huber-2025-eed-teaser.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/huber-2025-eed/huber-2025-eed-teaser:thumb{{size}}.png" } ], "projects_workgroups": [ "d10164" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/huber-2025-eed/", "__class": "Publication" }, { "id": "mueller-2024-rbt", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Real-time bike-related traffic violation detection of cars", "date": "2025-09-12", "abstract": "Multi-modal object detection offers more significant results than 3D object de-\ntection within a single domain[Shi20]. In the case of autonomous driving, a\n\ncombination of modalities is used to complement other modalities weaknesses.\nWhile LIDAR sensors offer great depth and reflection information precision, the\noutput is a sparsely populated point cloud. RGB images, on the other hand,\noffer great resolution and improve object detection and classification results.\nHowever, to be able to extract precise 3D bounding cuboids, it is often fusioned\nwith point clouds or other depth information.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 742, "image_height": 468, "name": "mueller-2024-rbt-image.png", "type": "image/png", "size": 493687, "path": "Publication:mueller-2024-rbt", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/mueller-2024-rbt/mueller-2024-rbt-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/mueller-2024-rbt/mueller-2024-rbt-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5355 ], "date_end": "2025-09-12", "date_start": "2024-03-07", "matrikelnr": "01417912", "supervisor": [ 948 ], "research_areas": [ "Geometry" ], "keywords": [ "sensors", "bicycle", "traffic rules" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 742, "image_height": 468, "name": "mueller-2024-rbt-image.png", "type": "image/png", "size": 493687, "path": "Publication:mueller-2024-rbt", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/mueller-2024-rbt/mueller-2024-rbt-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/mueller-2024-rbt/mueller-2024-rbt-image:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "mueller-2024-rbt-thesis.pdf", "type": "application/pdf", "size": 1095091, "path": "Publication:mueller-2024-rbt", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/mueller-2024-rbt/mueller-2024-rbt-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/mueller-2024-rbt/mueller-2024-rbt-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "WorldScale" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/mueller-2024-rbt/", "__class": "Publication" }, { "id": "KOEPPEL-2025-Nearfield", "type_id": "studentproject", "tu_id": null, "repositum_id": null, "title": "Nearfield Viewer", "date": "2025-09-11", "abstract": "In lighting design, simulations rely on far-field photometry, which represents a luminaire\nby a point source with 2D angular luminous-intensity distribution. Moreover, lighting tools\nfocus on luminaire’s illumination while neglecting their visual appearance. For luminaires\nwith optically complex fixtures, far-field data is inaccurate. Near-field scans capture the\nrequired detail, but have large memomry requirements and are slow to render using current\napproaches. We present a real-time viewer that displays the luminaire appearance directly\nfrom near-field measurements rather than running a global illumination simulation. For every\nscreen pixel, we find the best measurement point and sample the corresponding data. Through\nour viewer, we showcase that near-field data can be used interactively on consumer hardware\nby using our data packing and sampling approach. Our approach provides a practical baseline\nfor future work on neural compression and using higher resolution scans, aiming to further\nimprove visual quality in lighting design.\n", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "name": "KOEPPEL-2025-Nearfield-image.png", "type": "image/png", "size": 146541, "path": "Publication:KOEPPEL-2025-Nearfield", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/KOEPPEL-2025-Nearfield/KOEPPEL-2025-Nearfield-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/KOEPPEL-2025-Nearfield/KOEPPEL-2025-Nearfield-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5237 ], "date_end": "2025-09-11", "date_start": "2025-02-18", "matrikelnr": "12022493", "supervisor": [ 193, 659 ], "research_areas": [ "Rendering" ], "keywords": [ "near-field illumination", "luminaire design" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "name": "KOEPPEL-2025-Nearfield-image.png", "type": "image/png", "size": 146541, "path": "Publication:KOEPPEL-2025-Nearfield", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/KOEPPEL-2025-Nearfield/KOEPPEL-2025-Nearfield-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/KOEPPEL-2025-Nearfield/KOEPPEL-2025-Nearfield-image:thumb{{size}}.png" }, { "description": null, "filetitle": "report", "main_file": true, "use_in_gallery": false, "access": "public", "name": "KOEPPEL-2025-Nearfield-report.pdf", "type": "application/pdf", "size": 5630442, "path": "Publication:KOEPPEL-2025-Nearfield", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/KOEPPEL-2025-Nearfield/KOEPPEL-2025-Nearfield-report.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/KOEPPEL-2025-Nearfield/KOEPPEL-2025-Nearfield-report:thumb{{size}}.png" } ], "projects_workgroups": [ "VRVis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/KOEPPEL-2025-Nearfield/", "__class": "Publication" }, { "id": "proelss-bdp", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Building a drone platform for autonomous scanning", "date": "2025-09-08", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1050, "image_height": 740, "name": "proelss-bdp-image.png", "type": "image/png", "size": 729020, "path": "Publication:proelss-bdp", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/proelss-bdp/proelss-bdp-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/proelss-bdp/proelss-bdp-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5471 ], "co_supervisor": [ 948 ], "date_end": "2025-08-09", "date_start": "2025-03-20", "matrikelnr": "11912403", "supervisor": [ 193, 948 ], "research_areas": [ "Geometry" ], "keywords": [ "drone", "autonomous scanning", "lidar" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1050, "image_height": 740, "name": "proelss-bdp-image.png", "type": "image/png", "size": 729020, "path": "Publication:proelss-bdp", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/proelss-bdp/proelss-bdp-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/proelss-bdp/proelss-bdp-image:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "proelss-bdp-thesis.pdf", "type": "application/pdf", "size": 879923, "path": "Publication:proelss-bdp", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/proelss-bdp/proelss-bdp-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/proelss-bdp/proelss-bdp-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "WorldScale" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/proelss-bdp/", "__class": "Publication" }, { "id": "ellhotka-2025-ipo", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Improving the Performance of Edge-Path Bundling With WebGPU", "date": "2025-09", "abstract": "Visualizing large graphs is often challenging due to visual clutter, which obscures important patterns. While Spanner-based Edge-Path Bundling (S-EPB) is an effective technique\nfor mitigating this issue, its CPU-based implementation is too slow for interactive use, particularly in web environments. This thesis presents a Parallel Edge-Path Bundling (P-EPB) algorithm that addresses this performance limitation by utilizing the massively parallel processing capabilities of modern Graphics Processing Unit (GPU)s through the WebGPU API.\n\nThe proposed algorithm reengineers the S-EPB technique for parallel execution, with a focus on finding and then optimizing the most computationally demanding tasks: spanner construction and shortest-path calculations. A parallelized Floyd–Warshall algorithm, together with different spanner construction methods (greedy and theta-graph), is employed in implementing the P-EPB algorithm as an interactive web application. \n\nA detailed evaluation compares the WebGPU-based P-EPB algorithm to the CPU-based S-EPB implementation. Results show that the P-EPB approach, particularly when using a theta-spanner, delivers substantial speedups on dense graphs. This work highlights the potential of WebGPU to enable high-performance, interactive graph visualization and analysis in web-based environments.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "name": "ellhotka-2025-ipo-teaser.png", "type": "image/png", "size": 615750, "path": "Publication:ellhotka-2025-ipo", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/ellhotka-2025-ipo/ellhotka-2025-ipo-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/ellhotka-2025-ipo/ellhotka-2025-ipo-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5498 ], "date_end": "2025-09", "date_start": "2025-03", "matrikelnr": "11776184", "supervisor": [ 166, 1110 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [ { "href": "https://github.com/YannicEl/edge_bundling_webgpu", "caption": "GitHub", "description": null, "main_file": 1 }, { "href": "https://bachelor.yannic.at/app?graph=airlines&spannerAlgorithm=theta&renderingMode=quality", "caption": "demo", "description": null, "main_file": 1 } ], "files": [ { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "name": "ellhotka-2025-ipo-teaser.png", "type": "image/png", "size": 615750, "path": "Publication:ellhotka-2025-ipo", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/ellhotka-2025-ipo/ellhotka-2025-ipo-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/ellhotka-2025-ipo/ellhotka-2025-ipo-teaser:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "ellhotka-2025-ipo-thesis.pdf", "type": "application/pdf", "size": 8099963, "path": "Publication:ellhotka-2025-ipo", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/ellhotka-2025-ipo/ellhotka-2025-ipo-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/ellhotka-2025-ipo/ellhotka-2025-ipo-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/ellhotka-2025-ipo/", "__class": "Publication" }, { "id": "KRISTMANN-24-JPG", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/219184", "title": "Real-Time Rendering with JPEG-Compressed Textures", "date": "2025-09", "abstract": "Although variable-rate compressed image formats such as JPEG are widely used to efficiently encode images, they have not found their way into real-time rendering due to special requirements such as random access to individual texels. In this thesis, we investigate the feasibility of variable-rate texture compression on modern GPUs using the JPEG format, and how it compares to the GPU-friendly fixed-rate compression approaches BC1 and ASTC.Using a deferred rendering pipeline and a list of pointers to individually encoded JPEG blocks, we are able to identify the subset of blocks that are needed for a given frame, decode these, and colourise the framebuffer’s pixels. Despite the additional 0.5 bit per texel that we require for our approach, JPEG maintains significantly better quality and compression rates compared to BC1, and is able to compete with ASTC. Although we can not fully compete performance-wise, decoding the required texels of a JPEG texture requires less than 1ms per frame on an RTX 4090, thus demonstrating that variable-rate encoded image formats are feasible for rendering pipelines that are based on deferred rendering or visibility buffers", "authors_et_al": false, "substitute": null, "main_image": { "description": "MCU-Utilisation: Each pixel is coloured by how many of the corresponding\nMCU’s texels are actually used. Red: This pixel’s colour is sourced from an MCU where\nall its texels are used. Blue: Only a single texel of the corresponding MCU made it into\nthe final image.", "filetitle": "Teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1042, "image_height": 763, "name": "KRISTMANN-24-JPG-Teaser.jpg", "type": "image/jpeg", "size": 134818, "path": "Publication:KRISTMANN-24-JPG", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/KRISTMANN-24-JPG/KRISTMANN-24-JPG-Teaser.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/KRISTMANN-24-JPG/KRISTMANN-24-JPG-Teaser:thumb{{size}}.png" }, "sync_repositum_override": "access,title,date", "repositum_presentation_id": null, "authors": [ 1935 ], "ac_number": "AC17639949", "co_supervisor": [ 1116 ], "date_end": "2025-09", "date_start": "2024-12", "diploma_examina": "2025-09-11", "doi": "10.34726/hss.2025.134600", "matrikelnr": "01519693", "open_access": "yes", "pages": "73", "supervisor": [ 193 ], "research_areas": [ "Rendering" ], "keywords": [ "Texture compression", "Real-time rendering", "JPEG", "Image compression", "Cuda", "Variable-rate compression", "Huffman coding", "Parallel computing" ], "weblinks": [], "files": { "1": { "description": "MCU-Utilisation: Each pixel is coloured by how many of the corresponding\nMCU’s texels are actually used. Red: This pixel’s colour is sourced from an MCU where\nall its texels are used. Blue: Only a single texel of the corresponding MCU made it into\nthe final image.", "filetitle": "Teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1042, "image_height": 763, "name": "KRISTMANN-24-JPG-Teaser.jpg", "type": "image/jpeg", "size": 134818, "path": "Publication:KRISTMANN-24-JPG", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/KRISTMANN-24-JPG/KRISTMANN-24-JPG-Teaser.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/KRISTMANN-24-JPG/KRISTMANN-24-JPG-Teaser:thumb{{size}}.png" }, "2": { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "KRISTMANN-24-JPG-thesis.pdf", "type": "application/pdf", "size": 4052635, "path": "Publication:KRISTMANN-24-JPG", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/KRISTMANN-24-JPG/KRISTMANN-24-JPG-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/KRISTMANN-24-JPG/KRISTMANN-24-JPG-thesis:thumb{{size}}.png" } }, "projects_workgroups": [ "rend" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/KRISTMANN-24-JPG/", "__class": "Publication" }, { "id": "gall-2025-marv", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/223667", "title": "MARV: Multiview Augmented Reality Visualisation for Exploring Rich Material Data", "date": "2025-09", "abstract": "Rich material data is complex, large and heterogeneous, integrating primary and secondary non-destructive testing data for spatial, spatio-temporal, as well as high-dimensional data analyses. Currently, materials experts mainly rely on conventional desktop-based systems using 2D visualisation techniques, which render respective analyses a time-consuming and mentally demanding challenge. MARV is a novel immersive visual analytics system, which makes analyses of such data more effective and engaging in an augmented reality setting. For this purpose, MARV includes three newly designed visualisation techniques: MDD Glyphs with a Skewness Kurtosis Mapper, Temporal Evolution Tracker, and Chrono Bins, facilitating interactive exploration and comparison of multidimensional distributions of attribute data from multiple time steps. A qualitative evaluation conducted with materials experts in a real-world case study demonstrates the benefits of the proposed visualisation techniques. This evaluation revealed that combining spatial and abstract data in an immersive environment improves their analytical capabilities and facilitates the identification of patterns, anomalies, as well as changes over time.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": "projects", "repositum_presentation_id": null, "authors": [ 1355, 1354, 166, 611 ], "articleno": "e70150", "doi": "10.1111/cgf.70150", "issn": "1467-8659", "journal": "Computer Graphics Forum", "number": "6", "pages": "15", "publisher": "WILEY", "volume": "44", "research_areas": [ "VisMat", "VR" ], "keywords": [ "virtual environments", "augmented reality", "immersive analytics", "scientific visualisation", "visualization", "visual analytics" ], "weblinks": [], "files": [], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/gall-2025-marv/", "__class": "Publication" }, { "id": "kraehsmaier-dsc", "type_id": "bachelorthesis", "tu_id": 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aktuellen RGB-Bild auf dem Smartphone anzeigen\n- Evaluierung: wie schnell kann die Registrierung, Change Detection und Visualisierung dargestellt werden und wie genau (ausgenommen Change detection) ist sie\n\n\n", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 489, "image_height": 254, "name": "hamzic_ademir-baa-image.png", "type": "image/png", "size": 162798, "path": "Publication:hamzic_ademir-baa", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/hamzic_ademir-baa/hamzic_ademir-baa-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/hamzic_ademir-baa/hamzic_ademir-baa-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5351 ], "date_end": "2025-08-12", "date_start": "2024-03-15", "matrikelnr": 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pipeline", "date": "2025-07-07", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 209, "image_height": 135, "name": "kozonits_marcel-2025-baa-image.png", "type": "image/png", "size": 45093, "path": "Publication:kozonits_marcel-2025-baa", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/kozonits_marcel-2025-baa/kozonits_marcel-2025-baa-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/kozonits_marcel-2025-baa/kozonits_marcel-2025-baa-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5446 ], "co_supervisor": [ 948 ], "date_end": "2025-07-07", "date_start": "2025-02-20", "matrikelnr": "12122382", "supervisor": [ 948 ], "research_areas": [ "Geometry" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "", "main_file": true, "use_in_gallery": false, "access": "public", "name": "kozonits_marcel-2025-baa-.pdf", "type": "application/pdf", "size": 902236, "path": "Publication:kozonits_marcel-2025-baa", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/kozonits_marcel-2025-baa/kozonits_marcel-2025-baa-.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/kozonits_marcel-2025-baa/kozonits_marcel-2025-baa-:thumb{{size}}.png" }, { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 209, "image_height": 135, "name": "kozonits_marcel-2025-baa-image.png", "type": "image/png", "size": 45093, "path": "Publication:kozonits_marcel-2025-baa", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/kozonits_marcel-2025-baa/kozonits_marcel-2025-baa-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/kozonits_marcel-2025-baa/kozonits_marcel-2025-baa-image:thumb{{size}}.png" } ], "projects_workgroups": [ "WorldScale" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/kozonits_marcel-2025-baa/", "__class": "Publication" }, { "id": "2025-v2e", "type_id": "proceedings", "tu_id": null, "repositum_id": "20.500.12708/217350", "title": "VisGames 2025: EuroVis Workshop on Visualization Play, Games, and Activities", "date": "2025-06-02", "abstract": "We are happy to announce that the first Workshop on Visualization, Play, Games, and Activities: VisGames will take place as part of the EuroVis Conference on June 2, 2025, in Luxembourg. VisGames explores how visualization games and playful activities can be used beyond education as tools for communication, co-creation, and collaborative problem-solving. With this workshop, we aim to highlight innovative approaches that foster idea generation, support decision-making, engage stakeholders, and evaluate visualization design through interactive and game-based methods.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [], "editor": "Stoiber, Christina and Boucher, Magdalena and de Jesus Oliveira, Victor Adriel and Schetinger, Victor and Filipov, Velitchko and Raidou, Renata Georgia and Amabili, Lorenzo and Keck, Mandy and Aigner, Wolfgang", "isbn": "978-3-03868-290-5", "publisher": "Eurographics Association", "research_areas": [], "keywords": [ "Visual Analytics", "Visualization", "Games", "Activities" ], "weblinks": [], "files": [], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/2025-v2e/", "__class": "Publication" }, { "id": "steinschorn-2025-parameter", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/216467", "title": "Parameter Optimization for Surface Reconstruction", "date": "2025-06", "abstract": "In this thesis, we compare different parameter-optimization algorithms on the example of Screened Poisson Surface Reconstruction. To do this, we first implemented five state-of-the-art algorithms. GEIST is a graph-based algorithm that splits the parameter space into an `optimal' and a `non-optimal' set to select new configurations. Iterated F-Race places a normal distribution of selection probabilities on the best configurations of the last iteration and uses that to choose the next configurations. ParamILS uses iterative local search to select a better neighbor and find an optimum this way. PostSelection uses a shortened version of an algorithm to find promising candidates and a second, more detailed one to evaluate these. As a simple baseline we also implemented Brute-Force.\n\nFor all of these algorithms, we first conduct several tests to find a good configuration to run them with. After that, we test them on point clouds from two datasets. Each dataset contains each cloud in different qualities, so we are able to test varying input qualities as well as types. We show that each of the implemented algorithms is able to find better parameter configurations than the default Screened Poisson Surface Reconstruction configuration. In most cases, GEIST and PostSelection lead to the best results but also have the longest run times, while ParamILS and Iterated F-Race lead to good results in a far shorter time period. Brute-Force is not competitive when it comes to high-quality configurations, but still leads to an improvement over the default in most cases.\n\nTo summarize the results over different types and qualities, the default configuration yields acceptable but not ideal results for point clouds of smooth meshes with little noise and we suggest an alternative. If the surface is rougher, the importance weight of the points should ideally be set higher. If there is a lot of noise, this weight as well as the Octree depth should be reduced.\n\nWe discuss the advantages and disadvantages of each implemented algorithm and compare their results to recommend which one to use. We describe our implementations of each and quickly mention what work could be done to expand on this thesis. Finally, we give recommendations as to which configurations to use for different types of point clouds. For data with higher accuracy, depth and pointWeight should be higher than for data with lower accuracy. If the topology of the object is very complex, pointWeight is best set very high in comparison to simpler point clouds. We find that for most cases, IF-Race is the best compromise to use between speed and resulting quality of reconstruction. If time is of no concern, GEIST is an alternative that yields high-quality results.", "authors_et_al": false, "substitute": null, "main_image": { "description": "Armadillo input point cloud, reconstruction with default parameters, reconstruction with optimized parameters", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 2444, "image_height": 927, "name": "steinschorn-2025-parameter-teaser.png", "type": "image/png", "size": 935638, "path": "Publication:steinschorn-2025-parameter", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/steinschorn-2025-parameter/steinschorn-2025-parameter-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/steinschorn-2025-parameter/steinschorn-2025-parameter-teaser:thumb{{size}}.png" }, "sync_repositum_override": "abstract,keywords,ac_number", "repositum_presentation_id": null, "authors": [ 1757 ], "ac_number": "AC17567674", "date_end": "2025-06", "date_start": "2020-04-02", "diploma_examina": "2025-06-16", "doi": "10.34726/hss.2025.80083", "matrikelnr": "1227109", "open_access": "yes", "pages": "96", "supervisor": [ 193, 1395 ], "research_areas": [ "InfoVis", "Modeling" ], "keywords": [ "parameter optimization", "deep learning", "surface reconstruction", "Autotuning", "Point Clouds" ], "weblinks": [ { "href": "https://github.com/thefloff/ppsurf_param_opt", "caption": "Repository", "description": null, "main_file": 1 } ], "files": { "1": { "description": "Armadillo input point cloud, reconstruction with default parameters, reconstruction with optimized parameters", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 2444, "image_height": 927, "name": "steinschorn-2025-parameter-teaser.png", "type": "image/png", "size": 935638, "path": "Publication:steinschorn-2025-parameter", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/steinschorn-2025-parameter/steinschorn-2025-parameter-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/steinschorn-2025-parameter/steinschorn-2025-parameter-teaser:thumb{{size}}.png" }, "2": { "description": null, "filetitle": "thesis_large", "main_file": false, "use_in_gallery": false, "access": "public", "name": "steinschorn-2025-parameter-thesis_large.pdf", "type": "application/pdf", "size": 18678215, "path": "Publication:steinschorn-2025-parameter", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/steinschorn-2025-parameter/steinschorn-2025-parameter-thesis_large.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/steinschorn-2025-parameter/steinschorn-2025-parameter-thesis_large:thumb{{size}}.png" }, "3": { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "steinschorn-2025-parameter-thesis.pdf", "type": "application/pdf", "size": 2695388, "path": "Publication:steinschorn-2025-parameter", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/steinschorn-2025-parameter/steinschorn-2025-parameter-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/steinschorn-2025-parameter/steinschorn-2025-parameter-thesis:thumb{{size}}.png" } }, "projects_workgroups": [ "rend" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/steinschorn-2025-parameter/", "__class": "Publication" }, { "id": "Braunsperger-2025_bsc", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Data-Centric Methods for Efficient Deep Assembly Verification: A Case Study in Electronic Lock Manufacturing", "date": "2025-06", "abstract": "This thesis investigates data-efficient deep learning methods for visual assembly ver-\nification in a highly customizable electronic lock production line. We examine three\ndata-centric strategies. First, ROI-based methods leverage the fixed geometry of the\nworkpiece carriers by reformulating object detection as a set of classification or regression\ntasks over predefined regions. Second, pseudo bounding boxes are created by combining\nimage-level labels with known part positions to automatically generate object detection\nannotations without manual labelling. Third, synthetic training data is produced by\ncompositing cropped part images with background scenes, thereby increasing dataset\ndiversity and reducing the need for extensive manual data collection.\nThese methods are evaluated on a real-world dataset collected during regular production\nto assess their effectiveness in reducing manual annotation effort. We provide a compre-\nhensive comparison of data-centric approaches, highlighting their respective strengths\nand limitations. The results demonstrate that leveraging the structured nature of the\nassembly environment enables accurate model performance with substantially reduced\nannotation requirements.", "authors_et_al": false, "substitute": null, "main_image": { "description": "An example from the dataset presented in the thesis showing a Double-sided hybrid Euro cylinder with electronic thumbturn and keyway", "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1012, "image_height": 888, "name": "Braunsperger-2025_bsc-teaser.png", "type": "image/png", "size": 1577249, "path": "Publication:Braunsperger-2025_bsc", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/Braunsperger-2025_bsc/Braunsperger-2025_bsc-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/Braunsperger-2025_bsc/Braunsperger-2025_bsc-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5475 ], "date_end": "2025-06", "date_start": "2024-09", "matrikelnr": "11909911", "supervisor": [ 1813, 166 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": "An example from the dataset presented in the thesis showing a Double-sided hybrid Euro cylinder with electronic thumbturn and keyway", "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1012, "image_height": 888, "name": "Braunsperger-2025_bsc-teaser.png", "type": "image/png", "size": 1577249, "path": "Publication:Braunsperger-2025_bsc", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/Braunsperger-2025_bsc/Braunsperger-2025_bsc-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/Braunsperger-2025_bsc/Braunsperger-2025_bsc-teaser:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": false, "use_in_gallery": false, "access": "public", "name": "Braunsperger-2025_bsc-thesis.pdf", "type": "application/pdf", "size": 69351689, "path": "Publication:Braunsperger-2025_bsc", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/Braunsperger-2025_bsc/Braunsperger-2025_bsc-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/Braunsperger-2025_bsc/Braunsperger-2025_bsc-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/Braunsperger-2025_bsc/", "__class": "Publication" }, { "id": "matt-2025-scv", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/216286", "title": "Scalable Class-Centric Visual Interactive Labeling", "date": "2025-06", "abstract": "Large unlabeled datasets demand efficient and scalable data labeling solutions, in particular when the number of instances and classes is large. This leads to significant visual scalability challenges and imposes a high cognitive load on the users. Traditional instance-centric labeling methods, where (single) instances are labeled in each iteration struggle to scale effectively in these scenarios. To address these challenges, we introduce cVIL, a Class-Centric Visual Interactive Labeling methodology designed for interactive visual data labeling. By shifting the paradigm from assigning-classes-to-instances to assigning-instances-to-classes, cVIL reduces labeling effort and enhances efficiency for annotators working with large, complex and class-rich datasets. We propose a novel visual analytics labeling interface built on top of the conceptual cVIL workflow, enabling improved scalability over traditional visual labeling. In a user study, we demonstrate that cVIL can improve labeling efficiency and user satisfaction over instance-centric interfaces. The effectiveness of cVIL is further demonstrated through a usage scenario, showcasing its potential to alleviate cognitive load and support experts in managing extensive labeling tasks efficiently.", "authors_et_al": false, "substitute": null, "main_image": { "description": "class-centric visual interactive labeling workflow", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1667, "image_height": 624, "name": "matt-2025-scv-teaser.png", "type": "image/png", "size": 254694, "path": "Publication:matt-2025-scv", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/matt-2025-scv/matt-2025-scv-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/matt-2025-scv/matt-2025-scv-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5263, 5487, 1851, 5370, 1110 ], "articleno": "104240", "doi": "10.1016/j.cag.2025.104240", "issn": "1873-7684", "journal": "COMPUTERS & GRAPHICS-UK", "pages": "14", "publisher": "PERGAMON-ELSEVIER SCIENCE LTD", "volume": "129", "research_areas": [ "InfoVis" ], "keywords": [ "Class-centric labeling", "Interactive machine learning", "Property measures", "Visual analytics", "Visual-interactive data labeling" ], "weblinks": [], "files": [ { "description": "class-centric visual interactive labeling workflow", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1667, "image_height": 624, "name": "matt-2025-scv-teaser.png", "type": "image/png", "size": 254694, "path": "Publication:matt-2025-scv", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/matt-2025-scv/matt-2025-scv-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/matt-2025-scv/matt-2025-scv-teaser:thumb{{size}}.png" } ], "projects_workgroups": [ "d9282" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/matt-2025-scv/", "__class": "Publication" }, { "id": "schuetz-2025-splatshop", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/216694", "title": "Splatshop: Efficiently Editing Large Gaussian Splat Models", "date": "2025-06", "abstract": "We present Splatshop, a highly optimized toolbox for interactive editing (selection, deletion, painting, transformation, . . . ) of 3D Gaussian Splatting models. Utilizing a comprehensive collection of heuristic approaches, we carefully balance between exact and fast rendering to enable precise editing without sacrificing real-time performance. Our experiments confirm that Splatshop achieves these goals for scenes with up to 100 million primitives. We also show how our proposed pipeline can be extended for use with head-mounted displays. As such, Splatshop is the first VR-capable editor for large-scale 3D Gaussian Splatting models and a step towards a ''Photoshop for Gaussian Splatting.''", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "cover", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1276, "image_height": 691, "name": "schuetz-2025-splatshop-cover.jpg", "type": "image/jpeg", "size": 327472, "path": "Publication:schuetz-2025-splatshop", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/schuetz-2025-splatshop/schuetz-2025-splatshop-cover.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/schuetz-2025-splatshop/schuetz-2025-splatshop-cover:thumb{{size}}.png" }, "sync_repositum_override": "date,projects,articleno", "repositum_presentation_id": null, "authors": [ 1116, 5492, 5493, 823, 842, 193 ], "articleno": "8", "doi": "10.1111/cgf.70214", "issn": "1467-8659", "journal": "Computer Graphics Forum", "note": "https://github.com/m-schuetz/Splatshop", "number": "8", "open_access": "yes", "pages": "12", "publisher": "WILEY", "volume": "44", "research_areas": [ "Rendering" ], "keywords": [ "gaussian splats", "point clouds", "real-time rendering" ], "weblinks": [], "files": [ { "description": null, "filetitle": "cover", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1276, "image_height": 691, "name": "schuetz-2025-splatshop-cover.jpg", "type": "image/jpeg", "size": 327472, "path": "Publication:schuetz-2025-splatshop", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/schuetz-2025-splatshop/schuetz-2025-splatshop-cover.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/schuetz-2025-splatshop/schuetz-2025-splatshop-cover:thumb{{size}}.png" } ], "projects_workgroups": [ "d9275", "rend" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/schuetz-2025-splatshop/", "__class": "Publication" }, { "id": "eschner-2025-ide", "type_id": "journalpaper", "tu_id": null, "repositum_id": "20.500.12708/216865", "title": "Interactive Discovery and Exploration of Visual Bias in Generative Text‐to‐Image Models", "date": "2025-06", "abstract": "Bias in generative Text-to-Image (T2I) models is a known issue, yet systematically analyzing such models' outputs to uncover it remains challenging. We introduce the Visual Bias Explorer (ViBEx) to interactively explore the output space of T2I models to support the discovery of visual bias. ViBEx introduces a novel flexible prompting tree interface in combination with zero-shot bias probing using CLIP for quick and approximate bias exploration. It additionally supports in-depth confirmatory bias analysis through visual inspection of forward, intersectional, and inverse bias queries. ViBEx is model-agnostic and publicly available. In four case study interviews, experts in AI and ethics were able to discover visual biases that have so far not been described in literature.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 2578, "image_height": 1292, "name": "eschner-2025-ide-image.png", "type": "image/png", "size": 1659146, "path": "Publication:eschner-2025-ide", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/eschner-2025-ide/eschner-2025-ide-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/eschner-2025-ide/eschner-2025-ide-image:thumb{{size}}.png" }, "sync_repositum_override": "title,date,projects,event,lecturer,location,number,volume", "repositum_presentation_id": null, "authors": [ 1653, 5490, 5370, 1110 ], "ac_number": "AC17579673", "articleno": "e70135", "doi": "10.1111/cgf.70135", "event": "EuroVis 2025", "issn": "1467-8659", "journal": "Computer Graphics Forum", "lecturer": [ 1653 ], "location": "Luxembourg", "number": "3", "open_access": "yes", "pages": "20", "publisher": "WILEY", "volume": "44", "research_areas": [ "InfoVis" ], "keywords": [ "Visualization", "Bias", "Artificial Intelligence" ], "weblinks": [ { "href": "https://vibex.jde.cg.tuwien.ac.at", "caption": "live demo", "description": "Live demo of the ViBEx application", "main_file": 1 } ], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 2578, "image_height": 1292, "name": "eschner-2025-ide-image.png", "type": "image/png", "size": 1659146, "path": "Publication:eschner-2025-ide", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/eschner-2025-ide/eschner-2025-ide-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/eschner-2025-ide/eschner-2025-ide-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "eschner-2025-ide-paper.pdf", "type": "application/pdf", "size": 46238959, "path": "Publication:eschner-2025-ide", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/eschner-2025-ide/eschner-2025-ide-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/eschner-2025-ide/eschner-2025-ide-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "d9282" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/eschner-2025-ide/", "__class": "Publication" }, { "id": "erler-2025-lidarscout", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/216864", "title": "LidarScout: Direct Out-of-Core Rendering of Massive Point Clouds", "date": "2025-06", "abstract": "Large-scale terrain scans are the basis for many important tasks, such as topographic mapping, forestry, agriculture, and infrastructure planning. The resulting point cloud data sets are so massive in size that even basic tasks like viewing take hours to days of pre-processing in order to create level-of-detail structures that allow inspecting the data set in their entirety in real time. In this paper, we propose a method that is capable of instantly visualizing massive country-sized scans with hundreds of billions of points. Upon opening the data set, we first load a sparse subsample of points and initialize an overview of the entire point cloud, immediately followed by a surface reconstruction process to generate higher-quality, hole-free heightmaps. As users start navigating towards a region of interest, we continue to prioritize the heightmap construction process to the user's viewpoint. Once a user zooms in closely, we load the full-resolution point cloud data for that region and update the corresponding height map textures with the full-resolution data. As users navigate elsewhere, full-resolution point data that is no longer needed is unloaded, but the updated heightmap textures are retained as a form of medium level of detail. Overall, our method constitutes a form of direct out-of-core rendering for massive point cloud data sets (terabytes, compressed) that requires no preprocessing and no additional disk space. Source code, executable, pre-trained model, and dataset are available at: https://github.com/cg-tuwien/lidarscout", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 2456, "image_height": 1411, "name": "erler-2025-lidarscout-teaser.jpg", "type": "image/jpeg", "size": 421958, "path": "Publication:erler-2025-lidarscout", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/erler-2025-lidarscout/erler-2025-lidarscout-teaser.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/erler-2025-lidarscout/erler-2025-lidarscout-teaser:thumb{{size}}.png" }, "sync_repositum_override": "date,projects,articleno", "repositum_presentation_id": null, "authors": [ 1395, 1857, 193, 1116 ], "articleno": "10.2312/hpg.20251170", "booktitle": "High-Performance Graphics 2025 - Symposium Papers", "date_from": "2025-06-23", "date_to": "2025-06-25", "doi": "10.2312/hpg.20251170", "event": "High-Performance Graphics 2025", "isbn": "978-3-03868-291-2", "lecturer": [ 1395 ], "location": "Koppenhagen", "pages": "11", "publisher": "the Eurographics Association", "research_areas": [ "Geometry", "Modeling" ], "keywords": [ "Point-based models", "Mesh models", "Neural networks", "Reconstruction", "Aerial LIDAR" ], "weblinks": [ { "href": "https://github.com/cg-tuwien/lidarscout", "caption": "Repository of Viewer Source", "description": null, "main_file": 1 }, { "href": "https://github.com/cg-tuwien/lidarscout_training", "caption": "Repository of Training Source", "description": null, "main_file": 1 }, { "href": "https://www.youtube.com/watch?v=q7Ap-FHZufY&list=PLD5wBo3-8n8LVGp6BDOFuPgGANdoYg_uk&index=8", "caption": "Presentation from HPG 2025", "description": null, "main_file": 1 }, { "href": "https://doi.org/10.48436/443tr-j4096", "caption": "TUW Research Data Repository", "description": "Datasets, models, more results", "main_file": 0 } ], "files": [ { "description": "Datasets for training and testing, containing chunk points and GT patches", "filetitle": "Datasets", "main_file": false, "use_in_gallery": false, "access": "public", "name": "erler-2025-lidarscout-Datasets.zip", "type": "application/x-zip-compressed", "size": 3201189460, "path": "Publication:erler-2025-lidarscout", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/erler-2025-lidarscout/erler-2025-lidarscout-Datasets.zip", "thumb_image_sizes": [] }, { "description": "Models with checkpoints, training logs, hyperparameters and TorchScript", "filetitle": "Models", "main_file": false, "use_in_gallery": false, "access": "public", "name": "erler-2025-lidarscout-Models.zip", "type": "application/x-zip-compressed", "size": 185148024, "path": "Publication:erler-2025-lidarscout", "url": 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"https://www.cg.tuwien.ac.at/research/publications/2025/erler-2025-lidarscout/erler-2025-lidarscout-teaser_large.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/erler-2025-lidarscout/erler-2025-lidarscout-teaser_large:thumb{{size}}.png" }, { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 2456, "image_height": 1411, "name": "erler-2025-lidarscout-teaser.jpg", "type": "image/jpeg", "size": 421958, "path": "Publication:erler-2025-lidarscout", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/erler-2025-lidarscout/erler-2025-lidarscout-teaser.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/erler-2025-lidarscout/erler-2025-lidarscout-teaser:thumb{{size}}.png" }, { "description": "A screen capture of the viewer", "filetitle": "video", "main_file": true, "use_in_gallery": false, "access": "public", "name": "erler-2025-lidarscout-video.mp4", "type": "video/mp4", "size": 122979998, "path": "Publication:erler-2025-lidarscout", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/erler-2025-lidarscout/erler-2025-lidarscout-video.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/erler-2025-lidarscout/erler-2025-lidarscout-video:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2025/erler-2025-lidarscout/erler-2025-lidarscout-video:video.mp4" }, { "description": "LidarScout Executable for Windows", "filetitle": "Viewer", "main_file": true, "use_in_gallery": false, "access": "public", "name": "erler-2025-lidarscout-Viewer.zip", "type": "application/x-zip-compressed", "size": 2360647751, "path": "Publication:erler-2025-lidarscout", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/erler-2025-lidarscout/erler-2025-lidarscout-Viewer.zip", "thumb_image_sizes": [] } ], "projects_workgroups": [ "d9275", "rend" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/erler-2025-lidarscout/", "__class": "Publication" }, { "id": "vuckovic-2025-pdo", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/216200", "title": "Participatory Design of Visual Analytics Tools for Different Target Groups", "date": "2025-05-19", "abstract": "This paper reflects on the software engineering process behind the development of data visualization and analytics technologies tailored to the needs of diverse user groups. These considerations, introduced in our earlier work, are briefly revisited here. We focused on two use cases: one tailored to the needs and preferences of practitioners (data analysts), and the other directed towards meeting the requirements of nonprofessional, volunteer-based participants engaged in participatory citizen science. In both scenarios, we employed participatory methods, actively involving the target users in conceptualization and implementation phases. We observed diverse requirements and preferences concerning data visualization choices, additional functionalities, and analytical measures. To assess the effectiveness of these tools, in the current paper, we conducted a taskbased evaluation with selected participants, asking them to perform specific tasks such as identifying faults in the data, patterns, or detecting outliers. This was supplemented with qualitative feedback gathered through interviews and surveys, providing insights into user satisfaction, perceived challenges, and suggestions for improvement. The evaluation process revealed several areas for improvement from non-practitioners, particularly in the visual clarity of visualizations and the explanations regarding their usage, while practitioners responded more positively, noting no critical issues in software design and function.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5485, 5486, 950 ], "ac_number": "AC17562707", "doi": "10.24138/jcomss-2025-0009", "issn": "1846-6079", "journal": "Journal of Communications Software and Systems", "number": "2", "open_access": "yes", "pages": "10", "pages_from": "240", "pages_to": "249", "publisher": "Croatian Communications and Information Society", "volume": "21", "research_areas": [], "keywords": [ "Participatory Design", "Visualization design and evaluation methods", "Visual Analytics", "Data Quality" ], "weblinks": [], "files": [ { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "vuckovic-2025-pdo-paper.pdf", "type": "application/pdf", "size": 3015120, "path": "Publication:vuckovic-2025-pdo", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/vuckovic-2025-pdo/vuckovic-2025-pdo-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/vuckovic-2025-pdo/vuckovic-2025-pdo-paper:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/vuckovic-2025-pdo/", "__class": "Publication" }, { "id": "aigner-2025-vhv", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/225207", "title": "Visual Heritage: Visual Analytics and Computer Vision Meet Cultural Heritage (doc.funds.connect)", "date": "2025-05-07", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5540, 966, 5541, 1511, 5542, 1110, 5370 ], "booktitle": "Abstractband: 18. Forschungsforum der österreichischen Fachhochschulen", "date_from": "2025-05-07", "date_to": "2025-05-08", "event": "18. 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Neural Radiance Fields (NeRFs), which preceded 3DGS, are based on a principled ray-marching approach for volumetric rendering. In contrast, while sharing a similar image formation model with NeRF, 3DGS uses a hybrid rendering solution that builds on the strengths of volume rendering and primitive rasterization. A crucial benefit of 3DGS is its performance, achieved through a set of approximations, in many cases with respect to volumetric rendering theory. A naturally arising question is whether replacing these approximations with more principled volumetric rendering solutions can improve the quality of 3DGS. In this paper, we present an in-depth analysis of the various approximations and assumptions used by the original 3DGS solution. We demonstrate that, while more accurate volumetric rendering can help for low numbers of primitives, the power of efficient optimization and the large number of Gaussians allows 3DGS to outperform volumetric rendering despite its approximations.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1013, 5372, 5503, 193, 1650 ], "articleno": "e70032", "doi": "10.1111/cgf.70032", "issn": "1467-8659", "journal": "Computer Graphics Forum", "number": "2", "pages": "12", "publisher": "WILEY", "volume": "44", "research_areas": [], "keywords": [ "CCS Concepts", "Rasterization", "Ray tracing", "Volumetric models", "• Computing methodologies → Image-based rendering" ], "weblinks": [], "files": [], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/celarek-2025-d3g/", "__class": "Publication" }, { "id": "grammatikaki-2025-htr", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/215590", "title": "How to represent landmark trees in digital 3D maps? An automated workflow and user study", "date": "2025-05", "abstract": "Digital 3D maps created from digital elevation models (DEMs) cannot properly capture trees due to the 2.5D nature of the DEMs. Leveraging publicly available DEMs and orthophotos as the only input data sources, we present a fully automatic pipeline that models landmark trees. We conducted two crowdsourced user studies to evaluate visual appeal and scene recognizability using two different levels of detail of tree representations generated using our pipeline. Users found highly detailed trees much more appealing, and also easier and more trustworthy to recognize, with open-ended responses revealing key factors like realism, coherence, and tree shape influencing their preferences. However, the ability to recognize a location seems to depend more on the surrounding environment than the representation of the landmark tree in focus. We discuss the implications of these results for digital 3D outdoor maps.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 2200, "image_height": 370, "name": "grammatikaki-2025-htr-image.jpg", "type": "image/jpeg", "size": 181956, "path": "Publication:grammatikaki-2025-htr", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/grammatikaki-2025-htr/grammatikaki-2025-htr-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/grammatikaki-2025-htr/grammatikaki-2025-htr-image:thumb{{size}}.png" }, "sync_repositum_override": "date,projects,pages_from,pages_to,volume", "repositum_presentation_id": null, "authors": [ 1937, 1653, 5463, 5462, 1110 ], "doi": "10.1080/15230406.2025.2489543", "issn": "1545-0465", "journal": "Cartography and Geographic Information Science", "open_access": "yes", "pages": "18", "pages_from": "1", "pages_to": "18", "publisher": "TAYLOR & FRANCIS INC", "volume": "Number 0", "research_areas": [], "keywords": [ "Digital 3D maps", "landmarks", "trees", "user study", "modeling", "rendering" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 2200, "image_height": 370, "name": "grammatikaki-2025-htr-image.jpg", "type": "image/jpeg", "size": 181956, "path": "Publication:grammatikaki-2025-htr", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/grammatikaki-2025-htr/grammatikaki-2025-htr-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/grammatikaki-2025-htr/grammatikaki-2025-htr-image:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/grammatikaki-2025-htr/", "__class": "Publication" }, { "id": "freude-2025-ras", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/216171", "title": "Revisiting Analog Stereoscopic Film", "date": "2025-05", "abstract": "We present approaches for the simulation of an analog autostereoscopic (glasses-free) display and the visualization of analog color film at micro scales. These techniques were developed during an artistic research project and the creation of an accompanying art installation, which exhibits an analog stereo short film projected on a re-creation of a cyclostéréoscope, a historic device developed around 1952. We describe how computer graphics helped to understand the cyclostéréoscope, supported its physical re-creation, and enabled the visualization of the projection and material structure of analog film using physically based Monte Carlo light simulation.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1500, "image_height": 1000, "name": "freude-2025-ras-image.png", "type": "image/png", "size": 3727580, "path": "Publication:freude-2025-ras", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/freude-2025-ras/freude-2025-ras-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/freude-2025-ras/freude-2025-ras-image:thumb{{size}}.png" }, "sync_repositum_override": "date,articleno,open_access", "repositum_presentation_id": null, "authors": [ 1128, 5481, 5482, 5483, 193 ], "articleno": "N/A", "booktitle": "EPRESSIVE+WICED 2025 : The 9th ACM/EG Expressive Symposium : Eurographics Workshop on Intelligent Cinematography and Editing", "date_from": "2025-05-11", "date_to": "2025-05-12", "doi": "10.2312/exw.20251061", "event": "The 9th ACM/EG Expressive Symposium Eurographics Workshop on Intelligent Cinematography and Editing", "isbn": "978-3-03868-271-4", "lecturer": [ 1128 ], "location": "London", "open_access": "yes", "pages": "3", "publisher": "The Eurographics Association", "research_areas": [ "Rendering" ], "keywords": [ "Media arts", "Animation", "Rendering", "Visualization systems and tools", "Displays and imagers" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1500, "image_height": 1000, "name": "freude-2025-ras-image.png", "type": "image/png", "size": 3727580, "path": "Publication:freude-2025-ras", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/freude-2025-ras/freude-2025-ras-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/freude-2025-ras/freude-2025-ras-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "freude-2025-ras-paper.pdf", "type": "application/pdf", "size": 52013444, "path": "Publication:freude-2025-ras", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/freude-2025-ras/freude-2025-ras-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/freude-2025-ras/freude-2025-ras-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "d4729" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/freude-2025-ras/", "__class": "Publication" }, { "id": "medeiros-2025-iaa", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/216052", "title": "Immersive Analytics as a Support Medium for Data-Driven Monitoring in Hydropower", "date": "2025-05", "abstract": "Hydropower turbines are large-scale equipment essential to sustainable energy supply chains, and engineers have few opportunities to examine their internal structure. Our Immersive Analytics (IA) application is part of a research project that combines and compares simulated water turbine flows and sensor-measured data, looking for data-driven predictions of the lifetime of the mechanical parts of hydroelectric power plants. Our prototype combines spatial and abstract data in an immersive environment in which the user can navigate through a full-scale model of a water turbine, view simulated water flows of three different energy supply conditions, and visualize and interact with sensor-collected data situated at the reference position of the sensors in the actual turbine. In this paper, we detail our design process, which resulted from consultations with domain experts and a literature review, give an overview of our prototype, and present its evaluation, resulting from semi-structured interviews with experts and qualitative thematic analysis. Our findings confirm the current literature that IA applications add value to the presentation and analysis of situated data, as they show that we advance in the design directions for IA applications for domain experts that combine abstract and spatial data, with conclusions on how to avoid skepticism from such professionals.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5484, 378, 950 ], "doi": "10.1109/TVCG.2025.3549157", "issn": "1941-0506", "journal": "IEEE Transactions on Visualization and Computer Graphics", "number": "5", "pages": "11", "pages_from": "3536", "pages_to": "3546", "publisher": "IEEE COMPUTER SOC", "volume": "31", "research_areas": [], "keywords": [ "Immersive Analytics", "Data Visualization", "Digitalization", "Egocentric navigation", "Spatial Data", "User Evaluation" ], "weblinks": [], "files": [], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/medeiros-2025-iaa/", "__class": "Publication" }, { "id": "musleh-2025-trustme", "type_id": "journalpaper", "tu_id": null, "repositum_id": "20.500.12708/215604", "title": "TrustME: A Context-Aware Explainability Model to Promote User Trust in Guidance", "date": "2025-04-21", "abstract": "Guidance-enhanced approaches are used to support users in making sense of their data and overcoming challenging analytical scenarios. While recent literature underscores the value of guidance, a lack of clear explanations to motivate system interventions may still negatively impact guidance effectiveness. Hence, guidance-enhanced VA approaches require meticulous design, demanding contextual adjustments for developing appropriate explanations. Our paper discusses the concept of explainable guidance and how it impacts the user-system relationship-specifically, a user's trust in guidance within the VA process. We subsequently propose a model that supports the design of explainability strategies for guidance in VA. The model builds upon flourishing literature in explainable AI, available guidelines for developing effective guidance in VA systems, and accrued knowledge on user-system trust dynamics. Our model responds to challenges concerning guidance adoption and context-effectiveness by fostering trust through appropriately designed explanations. To demonstrate the model's value, we employ it in designing explanations within two existing VA scenarios. We also describe a design walk-through with a guidance expert to showcase how our model supports designers in clarifying the rationale behind system interventions and designing explainable guidance.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 703, "image_height": 706, "name": "musleh-2025-trustme-.png", "type": "image/png", "size": 75894, "path": "Publication:musleh-2025-trustme", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/musleh-2025-trustme/musleh-2025-trustme-.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/musleh-2025-trustme/musleh-2025-trustme-:thumb{{size}}.png" }, "sync_repositum_override": "event,number,pages_from,pages_to,volume", "repositum_presentation_id": null, "authors": [ 1867, 1410, 5418 ], "doi": "10.1109/TVCG.2025.3562929", "event": "IEEE Vis 2025", "issn": "1941-0506", "journal": "IEEE Transactions on Visualization and Computer Graphics", "number": "10", "open_access": "yes", "pages": "17", "pages_from": "8040", "pages_to": "8056", "publisher": "IEEE COMPUTER SOC", "volume": "31", "research_areas": [ "InfoVis" ], "keywords": [ "Explainability", "Explainable Guidance", "User Trust", "Visual Analytics" ], "weblinks": [], "files": [ { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 703, "image_height": 706, "name": "musleh-2025-trustme-.png", "type": "image/png", "size": 75894, "path": "Publication:musleh-2025-trustme", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/musleh-2025-trustme/musleh-2025-trustme-.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/musleh-2025-trustme/musleh-2025-trustme-:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/musleh-2025-trustme/", "__class": "Publication" }, { "id": "freude-2025-iso", "type_id": "journalpaper", "tu_id": null, "repositum_id": "20.500.12708/216172", "title": "Inverse Simulation of Radiative Thermal Transport", "date": "2025-04-17", "abstract": "The early phase of urban planning and architectural design has a great impact on the thermal loads and characteristics of constructed buildings. It is, therefore, important to efficiently simulate thermal effects early on and rectify possible problems. In this paper, we present an inverse simulation of radiative heat transport and a differentiable photon-tracing approach. Our method utilizes GPU-accelerated ray tracing to speed up both the forward and adjoint simulation. Moreover, we incorporate matrix compression to further increase the efficiency of our thermal solver and support larger scenes. In addition to our differentiable photon-tracing approach, we introduce a novel approximate edge sampling scheme that re-uses primary samples instead of relying on explicit edge samples or auxiliary rays to resolve visibility discontinuities. Our inverse simulation system enables designers to not only predict the temperature distribution, but also automatically optimize the design to improve thermal comfort and avoid problematic configurations. We showcase our approach using several examples in which we optimize the placement of buildings or their facade geometry. Our approach can be used to optimize arbitrary geometric parameterizations and supports steady-state, as well as transient simulations.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 960, "image_height": 540, "name": "freude-2025-iso-image.png", "type": "image/png", "size": 743750, "path": "Publication:freude-2025-iso", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/freude-2025-iso/freude-2025-iso-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/freude-2025-iso/freude-2025-iso-image:thumb{{size}}.png" }, "sync_repositum_override": "date_from,date_to,event,lecturer,number,open_access,volume", "repositum_presentation_id": null, "authors": [ 1128, 1525, 5257, 1063, 193, 1946 ], "articleno": "e70048", "date_from": "2025", "date_to": "2025", "doi": "10.1111/cgf.70048", "event": "Eurographics 2025", "first_published": "2025", "issn": "1467-8659", "journal": "Computer Graphics Forum", "lecturer": [ 1128 ], "number": "2", "open_access": "yes", "pages": "14", "publisher": "WILEY", "volume": "44", "research_areas": [ "Rendering" ], "keywords": [ "Ray tracing", "Physical simulation", "Computer-aided design" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 960, "image_height": 540, "name": "freude-2025-iso-image.png", "type": "image/png", "size": 743750, "path": "Publication:freude-2025-iso", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/freude-2025-iso/freude-2025-iso-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/freude-2025-iso/freude-2025-iso-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "freude-2025-iso-paper.pdf", "type": "application/pdf", "size": 13713470, "path": "Publication:freude-2025-iso", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/freude-2025-iso/freude-2025-iso-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/freude-2025-iso/freude-2025-iso-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "d4314", "d9259" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/freude-2025-iso/", "__class": "Publication" }, { "id": "brandmair-2025-rub", "type_id": "studentproject", "tu_id": null, "repositum_id": null, "title": "Rust-based WebGPU Rendering Backend for a Parametric Modeling Tool", "date": "2025-04", "abstract": "A WebGPU rendering backend has been implemented for the parametric modeling tool Math2Model in Rust. Having the rendering backend written in Rust (instead of TypeScript) allows using profiling tools, Rust libraries, and a strongly typed and safe programming language---for developing a web application.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "name": "brandmair-2025-rub-image.png", "type": "image/png", "size": 305857, "path": "Publication:brandmair-2025-rub", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/brandmair-2025-rub/brandmair-2025-rub-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/brandmair-2025-rub/brandmair-2025-rub-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5377 ], "date_end": "2025-04-30", "date_start": "2024-05-01", "matrikelnr": "12024754", "supervisor": [ 848, 193 ], "research_areas": [ "Rendering" ], "keywords": [], "weblinks": [ { "href": "https://github.com/cg-tuwien/Math2Model/blob/main/CHANGELOG.md", "caption": "Release Notes", "description": "Activity log for this student project", "main_file": 0 }, { "href": "https://cg-tuwien.github.io/Math2Model", "caption": "Math2Model: Build Objects with Math", "description": "Online parametric modeling tool", "main_file": 1 }, { "href": "https://github.com/cg-tuwien/Math2Model", "caption": "Source Code", "description": "Source code on GitHub, for Rust rendering backend see /parametric-renderer-core", "main_file": 0 } ], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "name": "brandmair-2025-rub-image.png", "type": "image/png", "size": 305857, "path": "Publication:brandmair-2025-rub", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/brandmair-2025-rub/brandmair-2025-rub-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/brandmair-2025-rub/brandmair-2025-rub-image:thumb{{size}}.png" } ], "projects_workgroups": [ "rend" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/brandmair-2025-rub/", "__class": "Publication" }, { "id": "wiesinger_2025-baa", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Using a drone for automated 3D Scanning", "date": "2025-03-28", "abstract": "Drones have been widely adopted over the past decades, aiding in critical tasks such as\nsearch and rescue, inspection, and mapping. Autonomous drone scanning could further\nsupport such missions, but remains a significant challenge in indoor environments. This\nthesis explores the feasibility of using a consumer drone for such autonomous indoor 3D\nscanning. Our approach combines a DJI Spark drone, a lightweight Pico Flexx depth\nsensor, and a Raspberry Pi to capture depth data, which is streamed to an external\nserver for real-time processing. The system leverages ROS 2 and InfiniTAM for SLAM\nand map reconstruction, while navigation commands are issued via a smartphone using\nDJI’s Mobile SDK.\nAlthough the system successfully completed a limited autonomous scan, various con-\nstraints—including the drone’s payload capacity, limited sensor range, and hardware\ninstabilities—posed significant challenges. Despite these limitations, a modular software\narchitecture was developed that integrates sensing, mapping, and navigation. This\nframework provides a solid foundation for future work toward fully autonomous indoor\nscanning with more capable hardware. However, generating the next best view and\nfinding a feasible path toward it remain open challenges.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5296 ], "date_end": "2025-03-28", "date_start": "2023-07-13", "matrikelnr": "11938253", "supervisor": [ 193, 948 ], "research_areas": [ "Geometry" ], "keywords": [ "drone", "scanning", "automation" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "name": "wiesinger_2025-baa-image.png", "type": "image/png", "size": 351129, "path": "Publication:wiesinger_2025-baa", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/wiesinger_2025-baa/wiesinger_2025-baa-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/wiesinger_2025-baa/wiesinger_2025-baa-image:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "wiesinger_2025-baa-thesis.pdf", "type": "application/pdf", "size": 87944075, "path": "Publication:wiesinger_2025-baa", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/wiesinger_2025-baa/wiesinger_2025-baa-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/wiesinger_2025-baa/wiesinger_2025-baa-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "WorldScale" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/wiesinger_2025-baa/", "__class": "Publication" }, { "id": "winklmueller-2025-ims", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Inverse Material Synthesis via Sub-Shader Extraction", "date": "2025-03-15", "abstract": "I explore the possibility of generating procedural Blender shaders of self-similar semiregular\nsurfaces from an input image derived from photograph or digital render. The\nresulting Blender shader should produce a Material with a look similar to the input\nimage.\nThis would be useful because procedural materials give 3D artists flexibility and creative\ncontrol over the materials look, that image based materials cannot, while inheriting all\nthe benefits of said image based materials, like availability and ease of use.\nThis shader generation is done by a neural parameter predictor and subsequent extraction\nof a sub-shader from a given, pre-built, general shader graph (the super-shader). The\nparameters are predicted by a MLP neural network using statistical texture descriptors\nas its input. Those descriptors are extracted from a pre-trained image classification\nCNN, which uses the original photograph/render as its input. Using this pipeline a\nlarge learning dataset for the MLP can be easily artificially generated with Blender by\nrendering the super-shader with randomized parameters.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "name": "winklmueller-2025-ims-image.png", "type": "image/png", "size": 1737834, "path": "Publication:winklmueller-2025-ims", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/winklmueller-2025-ims/winklmueller-2025-ims-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/winklmueller-2025-ims/winklmueller-2025-ims-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5292 ], "date_end": "2025-03-01", "date_start": "2024-09-01", "matrikelnr": "01429490", "supervisor": [ 1303 ], "research_areas": [ "Rendering" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "bachelor-thesis", "main_file": false, "use_in_gallery": false, "access": "public", "name": "winklmueller-2025-ims-bachelor-thesis.pdf", "type": "application/pdf", "size": 11718265, "path": "Publication:winklmueller-2025-ims", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/winklmueller-2025-ims/winklmueller-2025-ims-bachelor-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/winklmueller-2025-ims/winklmueller-2025-ims-bachelor-thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "name": "winklmueller-2025-ims-image.png", "type": "image/png", "size": 1737834, "path": "Publication:winklmueller-2025-ims", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/winklmueller-2025-ims/winklmueller-2025-ims-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/winklmueller-2025-ims/winklmueller-2025-ims-image:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/winklmueller-2025-ims/", "__class": "Publication" }, { "id": "walchhofer_ar_flowmaps", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "AR Visualization of Migration Flows in Europe", "date": "2025-03", "abstract": "Origin-Destination (OD) flow maps are a tool for visualizing movement patterns in domains such as transportation, trade, or migration. OD flow maps visualize movement using a network of directional and weighted curves. Traditional 2D OD flow maps often suffer from visual clutter and occlusion, limiting their ffectiveness in conveying complex spatial relationships. This thesis explores the use of Augmented Reality (AR) for OD flow map visualization of migration data to enhance interactivity, data comprehensibility, and spatial awareness. By extending OD flow maps to the third dimension of time, users can interact with the data dynamically and view OD connections from multiple perspectives across a span of years. This thesis develops an approach to visualize and encode the time component using a Space-Time Cube (STC), which encodes the time as\nan additional spatial dimension. The research involves the implementation of a force-directed layout algorithm based on work by Jenny et al. and the development of a marker-based AR phone application prototype capable of visualizing migration data for EU countries spanning from 2008-2022. This thesis contributes to the fields of data visualization, computer graphics, and human-computer interaction, providing insights into how immersive technologies can enhance spatio-temporal data visualization", "authors_et_al": false, "substitute": null, "main_image": { "description": "A 3D migration flow map of Central Europe with stacked flow lines representing individual years.", "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1318, "image_height": 977, "name": "walchhofer_ar_flowmaps-teaser.png", "type": "image/png", "size": 584452, "path": "Publication:walchhofer_ar_flowmaps", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/walchhofer_ar_flowmaps/walchhofer_ar_flowmaps-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/walchhofer_ar_flowmaps/walchhofer_ar_flowmaps-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5452 ], "date_end": "2025-03", "date_start": "2024-09", "matrikelnr": "12024752", "supervisor": [ 1813, 1410 ], "research_areas": [ "InfoVis", "VR" ], "keywords": [], "weblinks": [], "files": [ { "description": "A 3D migration flow map of Central Europe with stacked flow lines representing individual years.", "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1318, "image_height": 977, "name": "walchhofer_ar_flowmaps-teaser.png", "type": "image/png", "size": 584452, "path": "Publication:walchhofer_ar_flowmaps", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/walchhofer_ar_flowmaps/walchhofer_ar_flowmaps-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/walchhofer_ar_flowmaps/walchhofer_ar_flowmaps-teaser:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 1318, "preview_image_height": 977, "name": "walchhofer_ar_flowmaps-thesis.pdf", "type": "application/pdf", "size": 26253749, "path": "Publication:walchhofer_ar_flowmaps", "preview_name": "walchhofer_ar_flowmaps-thesis:preview.png", "preview_type": "image/png", "preview_size": 584452, "url": "https://www.cg.tuwien.ac.at/research/publications/2025/walchhofer_ar_flowmaps/walchhofer_ar_flowmaps-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/walchhofer_ar_flowmaps/walchhofer_ar_flowmaps-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/walchhofer_ar_flowmaps/", "__class": "Publication" }, { "id": "bramberger-3pv", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "3D Physicalization of Migration Flows in Europe", "date": "2025-03", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 2367, "preview_image_height": 1870, "name": "bramberger-3pv-.pdf", "type": "application/pdf", "size": 58525187, "path": "Publication:bramberger-3pv", "preview_name": "bramberger-3pv-:preview.jpg", "preview_type": "image/jpeg", "preview_size": 1647504, "url": "https://www.cg.tuwien.ac.at/research/publications/2025/bramberger-3pv/bramberger-3pv-.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/bramberger-3pv/bramberger-3pv-:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5449 ], "date_end": "2025-03", "date_start": "2024-09", "matrikelnr": "11913098", "supervisor": [ 1813, 1410 ], "research_areas": [], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 2367, "preview_image_height": 1870, "name": "bramberger-3pv-.pdf", "type": "application/pdf", "size": 58525187, "path": "Publication:bramberger-3pv", "preview_name": "bramberger-3pv-:preview.jpg", "preview_type": "image/jpeg", "preview_size": 1647504, "url": "https://www.cg.tuwien.ac.at/research/publications/2025/bramberger-3pv/bramberger-3pv-.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/bramberger-3pv/bramberger-3pv-:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/bramberger-3pv/", "__class": "Publication" }, { "id": "komon-kimmersdorfer-2025-weBIGeo", "type_id": "studentproject", "tu_id": null, "repositum_id": null, "title": "weBIGeo: real-time avalanche simulation and visualization using WebGPU", "date": "2025-03", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": { "description": "Possible avalanche traces on Schneeberg", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "name": "komon-kimmersdorfer-2025-weBIGeo-teaser.png", "type": "image/png", "size": 6536942, "path": "Publication:komon-kimmersdorfer-2025-weBIGeo", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/komon-kimmersdorfer-2025-weBIGeo/komon-kimmersdorfer-2025-weBIGeo-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/komon-kimmersdorfer-2025-weBIGeo/komon-kimmersdorfer-2025-weBIGeo-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1859, 1869 ], "date_end": "2025-03", "date_start": "2024-02", "matrikelnr": "11808210, 01326608", "supervisor": [ 1110, 1013 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [ { "href": "https://webigeo.alpinemaps.org/", "caption": "weBIGeo", "description": "weBIGeo avalanche simulation demo", "main_file": 1 }, { "href": "https://www.netidee.at/webigeo", "caption": "project page", "description": "NetIdee project page, including end report and blog posts", "main_file": 1 }, { "href": "https://github.com/weBIGeo/webigeo/tree/release/netidee6745", "caption": "GitHub", "description": "Code and documentation", "main_file": 0 } ], "files": [ { "description": "Possible avalanche traces on Schneeberg", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "name": "komon-kimmersdorfer-2025-weBIGeo-teaser.png", "type": "image/png", "size": 6536942, "path": "Publication:komon-kimmersdorfer-2025-weBIGeo", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/komon-kimmersdorfer-2025-weBIGeo/komon-kimmersdorfer-2025-weBIGeo-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/komon-kimmersdorfer-2025-weBIGeo/komon-kimmersdorfer-2025-weBIGeo-teaser:thumb{{size}}.png" } ], "projects_workgroups": [ "d9555" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/komon-kimmersdorfer-2025-weBIGeo/", "__class": "Publication" }, { "id": "fuchs_peter-2024-baa", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Efficient User Guidance to Next-Best-View Scan Positions", "date": "2025-02-28", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 149, "image_height": 100, "name": "fuchs_peter-2024-baa-image.png", "type": "image/png", "size": 26907, "path": "Publication:fuchs_peter-2024-baa", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/fuchs_peter-2024-baa/fuchs_peter-2024-baa-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/fuchs_peter-2024-baa/fuchs_peter-2024-baa-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5381 ], "co_supervisor": [ 948 ], "date_end": "2025-02-28", "date_start": "2024-09-01", "matrikelnr": "12125442", "supervisor": [ 193 ], "research_areas": [ "Geometry" ], "keywords": [ "next-best-view", "user guidance", "scanning" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 149, "image_height": 100, "name": "fuchs_peter-2024-baa-image.png", "type": "image/png", "size": 26907, "path": "Publication:fuchs_peter-2024-baa", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/fuchs_peter-2024-baa/fuchs_peter-2024-baa-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/fuchs_peter-2024-baa/fuchs_peter-2024-baa-image:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "fuchs_peter-2024-baa-thesis.pdf", "type": "application/pdf", "size": 10633086, "path": "Publication:fuchs_peter-2024-baa", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/fuchs_peter-2024-baa/fuchs_peter-2024-baa-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/fuchs_peter-2024-baa/fuchs_peter-2024-baa-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "WorldScale" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/fuchs_peter-2024-baa/", "__class": "Publication" }, { "id": "steinheber-2024-oto", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Observation and Tracking of Plant Health using Computer Vision", "date": "2025-02-19", "abstract": "- select neural network for classification of diseases, dryness of soil etc. with multispectral analysis, with open source, input should be image of plant bed (with several diverse plants), pipeline with segmentation (in same paper, or find segmentation paper)\n- optional: classify and segment plants\n- optional: growth analysis: blueten, wie schnell waechst die pflanze\n- search for data sets for training for generic plants (as many plants as possible), possibly combine several\n- evaluation with cheap IP RGB camera, and multispectral camera, e.g., RGB+IR or more\n- optional: evaluate soil dryness from images with dryness sensor\n \nresearch question: how well does such a system work with a commodity setup - for indoor and outdoor\nablation studies for indoor (more controlled environment) and outdoor, as well as RGB or RGB+IR++", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 332, "image_height": 332, "name": "steinheber-2024-oto-image.png", "type": "image/png", "size": 212356, "path": "Publication:steinheber-2024-oto", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/steinheber-2024-oto/steinheber-2024-oto-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/steinheber-2024-oto/steinheber-2024-oto-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5354 ], "date_end": "2025-02-19", "date_start": "2024-04-19", "matrikelnr": "12022506", "note": "1", "supervisor": [ 948 ], "research_areas": [ "Geometry" ], "keywords": [ "plants", "health monitoring", "computer vision" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 332, "image_height": 332, "name": "steinheber-2024-oto-image.png", "type": "image/png", "size": 212356, "path": "Publication:steinheber-2024-oto", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/steinheber-2024-oto/steinheber-2024-oto-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/steinheber-2024-oto/steinheber-2024-oto-image:thumb{{size}}.png" } ], "projects_workgroups": [ "WorldScale" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/steinheber-2024-oto/", "__class": "Publication" }, { "id": "elagabani-2025-ieh", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Implementierung eines Hybrid Renderers in Rust unter Verwendung einer Forward+ Pipeline", "date": "2025-02-03", "abstract": "In this thesis, we explore the topic of hybrid rendering, which combines rasterization and\nray tracing to produce high-fidelity images. While rasterization has been the primary\nrendering technique for real-time applications for decades, it struggles with producing\naccurate lighting effects because of its nature of processing each primitive in isolation.\nRay tracing has gained in popularity in recent years due to its ability to produce\naccurate lighting effects, which is one of the primary contributors to perceived visual\nfidelity. Achieving real-time performance with an entirely ray tracing-based renderer is\nchallenging because of the high number of rays required to produce images. This has\nmotivated the development of renderers that use rasterization as the primary rendering\ntechnique and ray tracing for producing lighting effects.\nThe goal of this thesis is to showcase the usage of a forward+ pipeline to build a hybrid\nrenderer utilizing the hardware acceleration of the graphics card for ray tracing tasks.\nTo this end, we build a rendering engine that implements ray-traced hard shadows and\nexplore methods that reduce the number of shadow rays. Shadow ray culling based on\nthe angle of the surface normal with the ray direction and tile-based light culling are the\ntwo methods implemented in this work. The results have shown a performance uplift of\n39% with the improvements presented in this thesis.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": false, "access": "public", "image_width": 1103, "image_height": 1072, "name": "elagabani-2025-ieh-image.PNG", "type": "image/png", "size": 446531, "path": "Publication:elagabani-2025-ieh", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/elagabani-2025-ieh/elagabani-2025-ieh-image.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/elagabani-2025-ieh/elagabani-2025-ieh-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5440 ], "date_end": "2025-02", "date_start": "2024-02", "matrikelnr": "12022518", "supervisor": [ 193 ], "research_areas": [ "Rendering" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "bachelor-thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "elagabani-2025-ieh-bachelor-thesis.pdf", "type": "application/pdf", "size": 8354283, "path": "Publication:elagabani-2025-ieh", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/elagabani-2025-ieh/elagabani-2025-ieh-bachelor-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/elagabani-2025-ieh/elagabani-2025-ieh-bachelor-thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": false, "access": "public", "image_width": 1103, "image_height": 1072, "name": "elagabani-2025-ieh-image.PNG", "type": "image/png", "size": 446531, "path": "Publication:elagabani-2025-ieh", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/elagabani-2025-ieh/elagabani-2025-ieh-image.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/elagabani-2025-ieh/elagabani-2025-ieh-image:thumb{{size}}.png" } ], "projects_workgroups": [ "abteilung" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/elagabani-2025-ieh/", "__class": "Publication" }, { "id": "ehlers-2025-ait", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/208050", "title": "An introduction to and survey of biological network visualization", "date": "2025-02", "abstract": "Biological networks describe complex relationships in biological systems, which represent biological entities as vertices and their underlying connectivity as edges. Ideally, for a complete analysis of such systems, domain experts need to visually integrate multiple sources of heterogeneous data, and visually, as well as numerically, probe said data in order to explore or validate (mechanistic) hypotheses. Such visual analyses require the coming together of biological domain experts, bioinformaticians, as well as network scientists to create useful visualization tools. Owing to the underlying graph data becoming ever larger and more complex, the visual representation of such biological networks has become challenging in its own right. This introduction and survey aims to describe the current state of biological network visualization in order to identify scientific gaps for visualization experts, network scientists, bioinformaticians, and domain experts, such as biologists, or biochemists, alike. Specifically, we revisit the classic visualization pipeline, upon which we base this paper’s taxonomy and structure, which in turn forms the basis of our literature classification. This pipeline describes the process of visualizing data, starting with the raw data itself, through the construction of data tables, to the actual creation of visual structures and views, as a function of task-driven user interaction. Literature was systematically surveyed using API-driven querying where possible, and the collected papers were manually read and categorized based on the identified sub-components of this visualization pipeline’s individual steps. From this survey, we highlight a number of exemplary visualization tools from multiple biological sub-domains in order to explore how they adapt these discussed techniques and why. Additionally, this taxonomic classification of the collected set of papers allows us to identify existing gaps in biological network visualization practices. We finally conclude this report with a list of open challenges and potential research directions. Examples of such gaps include (i) the overabundance of visualization tools using schematic or straight-line node-link diagrams, despite the availability of powerful alternatives, or (ii) the lack of visualization tools that also integrate more advanced network analysis techniques beyond basic graph descriptive statistics.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": "projects", "repositum_presentation_id": null, "authors": [ 1850, 5426, 1249, 1579, 5427, 5428, 5251, 1464 ], "articleno": "104115", "doi": "10.1016/j.cag.2024.104115", "issn": "1873-7684", "journal": "COMPUTERS & GRAPHICS-UK", "pages": "31", "publisher": "PERGAMON-ELSEVIER SCIENCE LTD", "volume": "126", "research_areas": [ "BioVis", "NetVis" ], "keywords": [ "Network visualization", "Visualization pipeline", "Sensemaking loop", "Visual analytics", "Network analysis", "Biological networks", "State-of-the-art-report" ], "weblinks": [], "files": [], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/ehlers-2025-ait/", "__class": "Publication" }, { "id": "peischl-2025-ipo", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/213937", "title": "Investigating the Propagation of CT Acquisition Artifacts along the Medical Imaging Pipeline", "date": "2025-02", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5454, 1410 ], "booktitle": "Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - (Volume 1)", "date_from": "2025-02-26", "date_to": "2025-03-28", "doi": "10.5220/0013254200003912", "event": "IVAPP 2025 - Part of VISIGRAPP, the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications.", "isbn": "978-989-758-728-3", "lecturer": [ 5454 ], "location": "Porto", "pages": "13", "pages_from": "752", "pages_to": "764", "research_areas": [], "keywords": [ "Biomedical Visualization and Applications", "Uncertainty Visualization", "Visual Analytics" ], "weblinks": [], "files": [], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/peischl-2025-ipo/", "__class": "Publication" }, { "id": "ohrhallinger-2025-tsd", "type_id": "talk", "tu_id": null, "repositum_id": "20.500.12708/213240", "title": "The Sampling-Reconstruction Dual", "date": "2025-02", "abstract": "Reconstructing surfaces of the real world from scans is an important and challenging problem. Its feasibility is limited by the number of the acquired points and their geometric configuration. The question of how many points exactly are required for the faithful reconstruction of the features leads to its inverse problem, sampling a known surface with the least possible number of points.\r\n \r\nThis talk is about reconstruction algorithms and attempts to prove their theoretical bounds in the number of points required and its dual, sampling curves (as their simpler 2D equivalent) and surfaces with specified bounds from different representations such as meshes, smooth higher-order boundaries, subdivision limit surfaces, and signed distance functions, depending on the application, e.g., lossless reduction of scanned data size, measuring scan error, handling scan artifacts such as noise, outliers, and holes, or secondary goals such as accelerating simulations.\r\n \r\nThe underlying assumption is that the smooth surface (reconstructed, or sampled) is richer than the sparse discrete set of geometric primitives (points + connectivity) it is represented with, leading to the goal of representing object boundaries, e.g., from the physical world, with the least amount of geometry.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 948 ], "date_from": "2025-01-13", "date_to": "2025-02-14", "event": "Infinite-dimensional Geometry: Theory and Applications", "lecturer": [ 948 ], "research_areas": [], "keywords": [ "surface reconstruction", "sampling" ], "weblinks": [], "files": [], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/ohrhallinger-2025-tsd/", "__class": "Publication" }, { "id": "musleh-2024-conan", "type_id": "journalpaper", "tu_id": null, "repositum_id": "20.500.12708/205807", "title": "ConAn: Measuring and Evaluating User Confidence in Visual Data Analysis Under Uncertainty", "date": "2025-02", "abstract": "User confidence plays an important role in guided visual data analysis scenarios, especially when uncertainty is involved in the analytical process. However, measuring confidence in practical scenarios remains an open challenge, as previous work relies primarily on self-reporting methods. In this work, we propose a quantitative approach to measure user confidence—as opposed to trust—in an analytical scenario. We do so by exploiting the respective user interaction provenance graph and examining the impact of guidance using a set of network metrics. We assess the usefulness of our proposed metrics through a user study that correlates results obtained from self-reported confidence assessments and our metrics—both with and without guidance. The results suggest that our metrics improve the evaluation of user confidence compared to available approaches. In particular, we found a correlation between self-reported confidence and some of the proposed provenance network metrics. The quantitative results, though, do not show a statistically significant impact of the guidance on user confidence. An additional descriptive analysis suggests that guidance could impact users' confidence and that the qualitative analysis of the provenance network topology can provide a comprehensive view of changes in user confidence. Our results indicate that our proposed metrics and the provenance network graph representation support the evaluation of user confidence and, subsequently, the effective development of guidance in VA.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 8170, "image_height": 5961, "name": "musleh-2024-conan-.png", "type": "image/png", "size": 9874701, "path": "Publication:musleh-2024-conan", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/musleh-2024-conan/musleh-2024-conan-.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/musleh-2024-conan/musleh-2024-conan-:thumb{{size}}.png" }, "sync_repositum_override": "date,projects,articleno,event,number,volume", "repositum_presentation_id": null, "authors": [ 1867, 5418, 1850, 1410 ], "articleno": "e15272", "doi": "10.1111/cgf.15272", "event": "EuroVis 2025", "issn": "1467-8659", "journal": "Computer Graphics Forum", "number": "1", "open_access": "yes", "pages": "18", "publisher": "WILEY", "volume": "44", "research_areas": [], "keywords": [ "decision making", "uncertainty", "user confidence", "visual analytics", "guided visual data analysis" ], "weblinks": [], "files": [ { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 8170, "image_height": 5961, "name": "musleh-2024-conan-.png", "type": "image/png", "size": 9874701, "path": "Publication:musleh-2024-conan", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/musleh-2024-conan/musleh-2024-conan-.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/musleh-2024-conan/musleh-2024-conan-:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/musleh-2024-conan/", "__class": "Publication" }, { "id": "marin-thesis", "type_id": "phdthesis", "tu_id": null, "repositum_id": "20.500.12708/215385", "title": "Proximity-Based Point Cloud Reconstruction", "date": "2025-02", "abstract": "Extrapolating information from incomplete data is a key human skill, enabling us to inferpatterns and make predictions from limited observations. A prime example is our ability to perceive coherent shapes from seemingly random point sets, a key aspect of cognition.However, data reconstruction becomes challenging when no predefined rules exist, as it is unclear how to connect the data or infer patterns. In computer graphics, a major goal isto replicate this human ability by developing algorithms that can accurately reconstruct original structures or extract meaningful information from raw, disconnected data.The contributions of this thesis deal with point cloud reconstruction, leveraging proximity-based methods, with a particular focus on a specific proximity-encoding data structure -the spheres-of-influence graph (SIG). We discuss curve reconstruction, where we automate the game of connecting the dots to create contours, providing theoretical guarantees for our method. We obtain the best results compared to similar methods for manifold curves. We extend our curve reconstruction to manifolds, overcoming the challenges of moving to different domains, and extending our theoreticalguarantees. We are able to reconstruct curves from sparser inputs compared to the state-of-the-art, and we explorevarious settings in which these curves can live. We investigate the properties of the SIGas a parameter-free proximity encoding structure of three-dimensional point clouds. We introduce new spatial bounds for the SIG neighbors as a theoretical contribution. We analyze how close the encoding is to the ground truth surface compared to the commonly used kNN graphs, and we evaluate our performance in the context of normal estimationas an application. Lastly, we introduce SING – a stability-incorporated neighborhood graph, a useful tool with various applications, such as clustering, and with a strong theoretical background in topological data analysis.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "Teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 2012, "image_height": 1035, "name": "marin-thesis-Teaser.png", "type": "image/png", "size": 599974, "path": "Publication:marin-thesis", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/marin-thesis/marin-thesis-Teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/marin-thesis/marin-thesis-Teaser:thumb{{size}}.png" }, "sync_repositum_override": "access,date", "repositum_presentation_id": null, "authors": [ 1848 ], "ac_number": "AC17518474", "co_supervisor": [ 948 ], "date_end": "2025-02", "date_start": "2021-09", "doi": "10.34726/hss.2025.128668", "duration": "3 years", "open_access": "yes", "pages": "141", "reviewer_1": [ 1510 ], "reviewer_2": [ 1243 ], "rigorosum": "2025-02-13", "supervisor": [ 193 ], "research_areas": [], "keywords": [ "point clouds", "reconstruction", "proximity graphs", "curve reconstruction", "clustering", "geometry processing" ], "weblinks": [], "files": [ { "description": null, "filetitle": "Curve Examples", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 2080, "image_height": 653, "name": "marin-thesis-Curve Examples.png", "type": "image/png", "size": 170210, "path": "Publication:marin-thesis", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/marin-thesis/marin-thesis-Curve Examples.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/marin-thesis/marin-thesis-Curve Examples:thumb{{size}}.png" }, { "description": null, "filetitle": "Possible Reconstructions", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 2078, "image_height": 678, "name": "marin-thesis-Possible Reconstructions.png", "type": "image/png", "size": 118537, "path": "Publication:marin-thesis", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/marin-thesis/marin-thesis-Possible Reconstructions.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/marin-thesis/marin-thesis-Possible Reconstructions:thumb{{size}}.png" }, { "description": null, "filetitle": "Teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 2012, "image_height": 1035, "name": "marin-thesis-Teaser.png", "type": "image/png", "size": 599974, "path": "Publication:marin-thesis", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/marin-thesis/marin-thesis-Teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/marin-thesis/marin-thesis-Teaser:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "marin-thesis-thesis.pdf", "type": "application/pdf", "size": 39191621, "path": "Publication:marin-thesis", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/marin-thesis/marin-thesis-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/marin-thesis/marin-thesis-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "rend" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/marin-thesis/", "__class": "Publication" }, { "id": "holzer-edo", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Enhancing Dashboard Onboarding via LLMs", "date": "2025-01-03", "abstract": "Data visualization offers powerful insights that drive better decision-making, but its\ninherent complexity can often be challenging. To understand these visualizations, an\neffective onboarding process is essential, providing clear guidance on the purpose and\nfunctionality of visualizations for users of all experience levels. Traditional onboarding\napproaches, such as static tutorials, frequently fall short in addressing the unique needs\nof diverse users, leading to confusion and inefficiency. This thesis presents an innovative\nonboarding solution powered by Large Language Models (LLMs), designed to provide\npersonalized, context-aware assistance that adapts dynamically to each user.\nOur approach harnesses the capabilities of prompt engineering, adaptive sequencing, and\nconversational interactions to create a dynamic, engaging onboarding experience. Key\nfeatures include custom prompts to clarify complex visual elements, adaptive sequencing\nthat responds to user behavior, and tailored narratives that adjust to users’ expertise\nlevels. We implemented these features into a prototype system, powered by Llama 3.1\nand ChatGPT 4o, to provide real-time, responsive assistance.\nBy transforming dashboards into more approachable tools, this work makes data visualization\naccessible to a wider audience, ultimately enhancing the way users interact with\nand extract insights from complex data.\n", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1459, "image_height": 853, "name": "holzer-edo-image.PNG", "type": "image/png", "size": 251472, "path": "Publication:holzer-edo", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/holzer-edo/holzer-edo-image.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/holzer-edo/holzer-edo-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5432 ], "date_end": "2025-01", "date_start": "2024-02", "matrikelnr": "12028208", "supervisor": [ 1892 ], "research_areas": [ "InfoVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1459, "image_height": 853, "name": "holzer-edo-image.PNG", "type": "image/png", "size": 251472, "path": "Publication:holzer-edo", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/holzer-edo/holzer-edo-image.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/holzer-edo/holzer-edo-image:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis-bachelor", "main_file": false, "use_in_gallery": false, "access": "public", "name": "holzer-edo-thesis-bachelor.pdf", "type": "application/pdf", "size": 3829629, "path": "Publication:holzer-edo", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/holzer-edo/holzer-edo-thesis-bachelor.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/holzer-edo/holzer-edo-thesis-bachelor:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/holzer-edo/", "__class": "Publication" }, { "id": "dhanoa-2025-dsg", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/209410", "title": "D-Tour: semi-automatic generation of interactive guided tours for visualization dashboard onboarding", "date": "2025-01", "abstract": "Onboarding a user to a visualization dashboard entails explaining its various components, including the chart types used, the data loaded, and the interactions available. Authoring such an onboarding experience is time-consuming and requires significant knowledge and little guidance on how best to complete this task. Depending on their levels of expertise, end users being onboarded to a new dashboard can be either confused and overwhelmed or disinterested and disengaged. We propose interactive dashboard tours (D-Tours) as semi-automated onboarding experiences that preserve the agency of users with various levels of expertise to keep them interested and engaged. Our interactive tours concept draws from open-world game design to give the user freedom in choosing their path through onboarding. We have implemented the concept in a tool called D-TOUR PROTOTYPE, which allows authors to craft custom interactive dashboard tours from scratch or using automatic templates. Automatically generated tours can still be customized to use different media (e.g., video, audio, and highlighting) or new narratives to produce an onboarding experience tailored to an individual user. We demonstrate the usefulness of interactive dashboard tours through use cases and expert interviews. Our evaluation shows that authors found the automation in the D-Tour Prototype helpful and time-saving, and users found the created tours engaging and intuitive. This paper and all supplemental materials are available at https://osf.io/6fbjp/.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1892, 1895, 5433, 5434, 166, 1896 ], "doi": "10.1109/TVCG.2024.3456347", "issn": "1941-0506", "journal": "IEEE Transactions on Visualization and Computer Graphics", "number": "1", "open_access": "yes", "pages": "11", "pages_from": "721", "pages_to": "731", "publisher": "IEEE COMPUTER SOC", "volume": "31", "research_areas": [], "keywords": [ "Dashboards", "interactive tours", "onboarding", "open-world games", "storytelling", "tutorial" ], "weblinks": [], "files": [ { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "dhanoa-2025-dsg-paper.pdf", "type": "application/pdf", "size": 685599, "path": "Publication:dhanoa-2025-dsg", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/dhanoa-2025-dsg/dhanoa-2025-dsg-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/dhanoa-2025-dsg/dhanoa-2025-dsg-paper:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/dhanoa-2025-dsg/", "__class": "Publication" }, { "id": "walch-2025-bemtrace", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/210140", "title": "BEMTrace: Visualization-driven approach for deriving Building Energy Models from BIM", "date": "2025-01", "abstract": "Building Information Modeling (BIM) describes a central data pool covering the entire life cycle of a construction project. Similarly, Building Energy Modeling (BEM) describes the process of using a 3D representation of a building as a basis for thermal simulations to assess the building's energy performance. This paper explores the intersection of BIM and BEM, focusing on the challenges and methodologies in converting BIM data into BEM representations for energy performance analysis. BEMTrace integrates 3D data wrangling techniques with visualization methodologies to enhance the accuracy and traceability of the BIM-to-BEM conversion process. Through parsing, error detection, and algorithmic correction of BIM data, our methods generate valid BEM models suitable for energy simulation. Visualization techniques provide transparent insights into the conversion process, aiding error identifcation, validation, and user comprehension. We introduce context-adaptive selections to facilitate user interaction and to show that the BEMTrace workfow helps users understand complex 3D data wrangling processes.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1494, 1002, 1387, 1277, 166, 950 ], "doi": "10.1109/TVCG.2024.3456315", "issn": "1941-0506", "journal": "IEEE Transactions on Visualization and Computer Graphics", "number": "1", "pages": "11", "pages_from": "240", "pages_to": "250", "publisher": "IEEE COMPUTER SOC", "volume": "31", "research_areas": [], "keywords": [ "Solid modeling", "Data visualization", "Three-dimensional displays", "Data models", "Buildings", "Computational modeling", "Object oriented modeling", "BIM", "BEM", "BIM-to-BEM", "3D Data Wrangling", "3D selections", "Visualization for trust building" ], "weblinks": [], "files": [], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/walch-2025-bemtrace/", "__class": "Publication" }, { "id": "steinschorn-2025-par", "type_id": "studentproject", "tu_id": null, "repositum_id": null, "title": "SPSR Parameter determined by Neural Network", "date": "2025-01", "abstract": "In ’Parameter Optimization for Surface Reconstruction’ we tested different parameter optimization methods to find the most accurate and fast way to find optimal parameters for longer-running tasks that cannot be exhaustively tested. One strategy that we did not test is using machine learning to solve this problem. If it is possible to train a neural network to determine close-to-optimal parameters for a given task, then that would certainly be faster than all the other tested solutions. For this report, we generated training data for the problem of reconstructing meshes from point clouds using Screened Poisson Surface Reconstruction. We used ParamILS for this, and then tested two different networks to see if this is achievable. We describe our strategy for this, present our results, and discuss the encountered problems.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1757 ], "date_end": "2025-01", "date_start": "2023-10", "matrikelnr": "1227109", "supervisor": [ 1395 ], "research_areas": [ "Geometry", "Modeling" ], "keywords": [ "Deep Learning", "Surface Reconstruction", "Parameter Optimization", "Screened Poisson Surface Reconstruction" ], "weblinks": [ { "href": "https://github.com/thefloff/ppsurf_param_opt", "caption": "Repo", "description": null, "main_file": 1 } ], "files": [ { "description": null, "filetitle": "report", "main_file": true, "use_in_gallery": false, "access": "public", "name": "steinschorn-2025-par-report.pdf", "type": "application/pdf", "size": 461075, "path": "Publication:steinschorn-2025-par", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/steinschorn-2025-par/steinschorn-2025-par-report.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/steinschorn-2025-par/steinschorn-2025-par-report:thumb{{size}}.png" } ], "projects_workgroups": [ "rend" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/steinschorn-2025-par/", "__class": "Publication" }, { "id": "ehlers-2025-penta", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/216534", "title": "Penta: Towards Visualizing Compound Graphs as Set-Typed Data", "date": "2025", "abstract": "Compound graphs are graphs whose nodes, in addition to topological connections, share group-level relationships. The need to incorporate both topological and group-level relationships makes them inherently challenging to visualize, especially for large data. We present Penta, a prototypical dashboard that, by combining elements of compound graph and set visualization, provides a complete view of both types of relationships. To this end, we employ five linked views that provide insight into a compound graph’s i) global and set local topology using both hypernode and traditional node-link diagrams, respectively, ii) set and entity-level relationship and identity using similarity matrices linked by a bipartite node-link diagram, as well as iii) node-centric topology across sets visualized as a layered node-link diagram. We demonstrate the workflow and advantages of Penta in three small-scale case studies, using character co-occurrence networks as well as biochemical pathway data. While still a prototype, the proposed dashboard shows promise in facilitating a complete visual exploration of the topology and group-level relationships present in compound graphs, simultaneously.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1850, 5479, 1410 ], "booktitle": "Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1 GRAPP, HUCAPP and IVAPP: IVAPP,", "date_from": "2025-02-26", "date_to": "2025-02-28", "doi": "10.5220/0013242300003912", "event": "20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP , GRAPP, HUCAPP and IVAPP 2025)", "isbn": "978-989-758-728-3", "lecturer": [ 5479 ], "location": "Porto", "pages": "9", "pages_from": "913", "pages_to": "921", "volume": "1", "research_areas": [], "keywords": [ "Compound Graph", "Ego Network", "Network Visualization", "Set Visualization" ], "weblinks": [], "files": [], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/ehlers-2025-penta/", "__class": "Publication" }, { "id": "grexova-2025-dva", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/220303", "title": "Designing a visual analysis pipeline for exploring TMS effects on heart rate", "date": "2025", "abstract": "We designed a highly flexible notebook-based visual analysis pipeline to explore Transcranial Magnetic Stimulation (TMS) and heart rate (HR) in different subjects’ cognitive states. TMS is a promising treatment of major depressive disorder not responsive to pharmacological treatment. However, the mechanism of action is not yet fully understood. The research in the best acquiring settings, such as stimulation intensities and target sites, is emerging. Multimodal analysis pipeline integrating TMS, Functional Magnetic Resonance Imaging (fMRI), and HR could shed light on both understanding the neural pathways and increasing the efficiency of TMS. To extend the already available concurrent TMS-fMRI analysis pipeline towards multimodal concurrent TMS-fMRI-HR, exploring the effect of TMS on HR is the next step. To design the visual analysis pipeline, we introduce and apply an extension of Data–Users–Tasks design triangle [Miksch and Aigner, 2014] by integrating the previous data workflow approach in the designing process. When the data processing workflow in the domain is only evolving, integrating the previous workflow approach into the design process benefits by respecting the data legacy, supports users’ adaptability, and ensures tasks’ compatibility. We refer to this framework as the Data–Users–Workflow-Tasks design pyramid. We subsequently provide a visual analysis pipeline to support data exploration in the early stages of research. The interactive preprocessing pipeline involves extracting data, handling missing data, and reducing noise. To compare time series of HR with different properties, we visualize Dynamic Time Warping (DTW) similarity measurement, and heart rate variability (HRV) metric clustering. We quantitatively evaluate the preprocessing steps using simulated ECG data. The key result is that linear and polynomial interpolation with root mean squared error (RMSE) values as low as to the power of -3 and -5, respectively, are especially effective as imputation methods for ECG with 400 Hz sampling frequency. To further assess the values of the usage scenarios for TMS and ECG data exploration, we employ Qualitative Result Inspection (QRI). Our proposed visual analysis pipeline assembles the first steps towards integrating TMS-HR analysis into a trimodal concurrent TMS-fMRI-HR approach.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5575 ], "ac_number": "AC17679434", "doi": "10.34726/hss.2025.126782", "open_access": "yes", "pages": "87", "supervisor": [ 1410 ], "research_areas": [], "keywords": [ "Visual Analysis Pipeline", "NCG-TMS", "Data-Users-Tasks Design Triangle", "Data-Users-Workflow-Tasks Design Pyramid" ], "weblinks": [], "files": [ { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "grexova-2025-dva-thesis.pdf", "type": "application/pdf", "size": 4489654, "path": "Publication:grexova-2025-dva", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/grexova-2025-dva/grexova-2025-dva-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/grexova-2025-dva/grexova-2025-dva-thesis:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/grexova-2025-dva/", "__class": "Publication" }, { "id": "amabili-2025-lpb", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/216591", "title": "Leveraging Popular Board Games to Teach Data Visualization", "date": "2025", "abstract": "To address the challenges in visualization education—particularly in motivating and engaging students—we propose the conceptual adaptation of popular board games into educational data visualization games. We present five unique adaptations ofwell-known board games, integrating their mechanics and materials into a data visualization learning process. For each game, we outline specific learning objectives and suggest strategies to extend the game-based approach to broader data visualization education. By combining familiar, engaging game mechanics with visualization content, we aim to foster critical engagement with the learning material while providing students with a foundational understanding of data visualization concepts. Early qualitative results from one of the games indicate a positive impact on players’ learning, boosting engagement and enjoyment.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1861, 166, 1410 ], "booktitle": "Visgames 2025: EuroVis Workshop on Visualization Play, Games, and Activities", "date_from": "2025-06-02", "date_to": "2025-06-06", "doi": "10.2312/visgames.20251165", "editor": "Stoiber, C. and Boucher, M. and de Jesus Oliveira, V. A. and Schetinger, V. and Filipov, V. and Raidou, R. G. and Amabili, L. and Keck, M.", "event": "VisGames 2025 colocated with EuroVis 2025 - 27th EG Conference on Visualization", "lecturer": [ 1861 ], "location": "Luxembourg City", "open_access": "yes", "pages": "6", "publisher": "The Eurographics Association", "research_areas": [], "keywords": [ "Human-centered computing", "visualization theory", "concepts and paradigms", "Information visualization" ], "weblinks": [], "files": [ { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "amabili-2025-lpb-paper.pdf", "type": "application/pdf", "size": 525621, "path": "Publication:amabili-2025-lpb", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/amabili-2025-lpb/amabili-2025-lpb-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/amabili-2025-lpb/amabili-2025-lpb-paper:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/amabili-2025-lpb/", "__class": "Publication" }, { "id": "haeusle-2025-uup", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/220329", "title": "Unraveling uncertainty propagation in the medical visualization pipeline", "date": "2025", "abstract": "Quantifying, raising awareness, and visualizing uncertainty stand as challenges in data visualization, especially in critical application domains such as medicine. Medical diagnosis and following treatment are always based on human decision-making, which itself is prone to uncertainty due to subjectivity or perception. Furthermore, decisions are often taken by analyzing measurements or images, which themselves are affected by uncertainty, caused by effects such as noise or resolution limitations. Thus, the whole process of diagnosis in clinical environments is concerned with interwoven uncertainties that accumulate and may change a pipeline's result substantially, potentially with detrimental effects on the patient's health, if uncertainties are not considered. This work aims to contribute to unraveling the complex interplay of uncertainties within the medical visualization pipeline. We do so by investigating the complex phenomena of uncertainty propagation in the medical visualization pipeline, in combination with extracting and analyzing provenance information from the pipeline encapsulated in an interactive framework. As a consequence, we utilize the provenance information, which can be seen as a complete history of the pipeline, to compare uncertainty propagation results of distinct pipeline states and thus gain insights into the behavior of uncertainty. In order to demonstrate the conceptual effectiveness of the framework, meaningful usage scenarios are presented. Those lay out simple and more complex scenarios to analyze the behavior and impact of different sorts of parameters present in the pipeline. Furthermore, we present ways in which a user can express their uncertainty for certain image regions or parameters and thereby gain insights into the impact of the specified uncertainties. The usage scenarios emphasize both positive and negative aspects of the framework and thus provide users with the means to assess the underlying work independently.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5574 ], "ac_number": "AC17679808", "doi": "10.34726/hss.2025.129144", "open_access": "yes", "pages": "128", "supervisor": [ 1410 ], "research_areas": [], "keywords": [ "Uncertainty Propagation", "Uncertainty", "Visualization Pipeline", "Medical Visualization Pipeline", "Provenance", "Parameter Sensitivity Analysis", "Monte Carlo Methods" ], "weblinks": [], "files": [ { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "haeusle-2025-uup-thesis.pdf", "type": "application/pdf", "size": 10648509, "path": "Publication:haeusle-2025-uup", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/haeusle-2025-uup/haeusle-2025-uup-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/haeusle-2025-uup/haeusle-2025-uup-thesis:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/haeusle-2025-uup/", "__class": "Publication" }, { "id": "beinder-2025-vao", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/213421", "title": "Visualization and analysis of 3D-connectivity at cell resolution", "date": "2025", "abstract": "With the advancement of imaging technologies, the mapping of the human body at continually increasing resolution becomes possible. Multiple research programs have achieved the imaging of various functional tissue units at cell resolution and even the imaging of single-cells in a combined effort to map out the human body and its disease states. Novel contributions to these programs open up a multitude of avenues to explore the functional complexity and disease progression of organs in even more detail. A vital part of this exploration is the analysis of connectivity between the functional tissue units or single-cells, as they are believed to communicate through diverse channels. This thesis presents two independent tools that empower researchers to improve their connectivity analysis workflows. Firstly, an installable Python tool that generates surface meshes and a connectivity abstraction in the form of a network from segmented volumetric data. In the course of this, a method for suggesting the connectivity of incomplete tubular meshes is proposed. Secondly, an interactive web-based visualization tool that improves connectivity analysis by synchronizing a three-dimensional spatial view with two network views that incorporate the connectivity abstraction. The applicability of both tools is tested and showcased with data from three distinct fields by analyzing the connectivity between glomeruli and nerves in the kidney, the connectivity of intraepitheliel lesions in pancreatic ducts with the surrounding nervous system, and the connectivity between single-cells of a melanoma.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5573 ], "ac_number": "AC17473350", "doi": "10.34726/hss.2025.124059", "open_access": "yes", "pages": "123", "supervisor": [ 1410 ], "research_areas": [], "keywords": [ "Visualization", "3D Reconstruction", "Connectivity", "Cellular Neighborhoods", "Functional Tissue Units", "Glomeruli", "Nerves", "PanIN", "Melanoma" ], "weblinks": [], "files": [ { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "beinder-2025-vao-thesis.pdf", "type": "application/pdf", "size": 6160074, "path": "Publication:beinder-2025-vao", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/beinder-2025-vao/beinder-2025-vao-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/beinder-2025-vao/beinder-2025-vao-thesis:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/beinder-2025-vao/", "__class": "Publication" }, { "id": "huber-2025-esl", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/213932", "title": "Exploring Seated Locomotion Techniques in Virtual Reality for People with Limited Mobility", "date": "2025", "abstract": "Virtual reality (VR) is often designed as a standing experience, excluding individuals with limited mobility. Given that a significant portion of the population experiences lower-body mobility restrictions, accessible VR locomotion must accommodate users without requiring lower-body movement. To build a comprehensive understanding of suitable locomotion techniques (LTs) for this demographic, it is crucial to evaluate the feasibility of various approaches in virtual environments (VEs). As a starting point, we present our evaluation approach and a user study on the feasibility and potential of selected LTs for accessible seated locomotion in VR. Our findings indicate that common LTs can be adapted for seated stationary VR. Teleportation-based techniques, in particular, stand out as viable options for accessible locomotion. Although our simulated wheelchair was less popular with non-disabled participants, it was well-received by wheelchair users and shows promise as an intuitive LT for (More)", "authors_et_al": false, "substitute": null, "main_image": { "description": "Different locomotion paths", "filetitle": "image", "main_file": true, "use_in_gallery": false, "access": "public", "image_width": 1041, "image_height": 571, "name": "huber-2025-esl-image.png", "type": "image/png", "size": 823835, "path": "Publication:huber-2025-esl", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/huber-2025-esl/huber-2025-esl-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/huber-2025-esl/huber-2025-esl-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5456, 5457, 1954, 5458, 5459, 378, 1030 ], "booktitle": "Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - GRAPP", "date_from": "2025-02-26", "date_to": "2025-02-28", "event": "20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications", "isbn": "978-989-758-728-3", "lecturer": [ 5456 ], "location": "Porto", "pages": "13", "pages_from": "161", "pages_to": "173", "publisher": "SciTePress", "volume": "1", "research_areas": [ "Rendering", "VR" ], "keywords": [ "Virtual Reality", "Accessibility", "Locomotion", "User Study" ], "weblinks": [], "files": [ { "description": "Different locomotion paths", "filetitle": "image", "main_file": true, "use_in_gallery": false, "access": "public", "image_width": 1041, "image_height": 571, "name": "huber-2025-esl-image.png", "type": "image/png", "size": 823835, "path": "Publication:huber-2025-esl", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/huber-2025-esl/huber-2025-esl-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/huber-2025-esl/huber-2025-esl-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "huber-2025-esl-paper.pdf", "type": "application/pdf", "size": 7212099, "path": "Publication:huber-2025-esl", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/huber-2025-esl/huber-2025-esl-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/huber-2025-esl/huber-2025-esl-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "d4314" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/huber-2025-esl/", "__class": "Publication" }, { "id": "kummer-2025-fvo-1", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/216906", "title": "Flattening-based visualization of supine breast MRI", "date": "2025", "abstract": "We propose two novel visualization methods optimized for supine breast images that “flatten” breast tissue, facilitating examination of larger tissue areas within each coronal slice. Breast cancer is the most frequently diagnosed cancer in women, and early lesion detection is crucial for reducing mortality. Supine breast magnetic resonance imaging (MRI) enables better lesion localization for image-guided interventions; however, traditional axial visualization is suboptimal because the tissue spreads over the chest wall, resulting in numerous fragmented slices that radiologists must scroll through during standard interpretation. Using a human-centered design approach, we incorporated user and expert feedback throughout the co-design and evaluation stages of our flattening methods. Our first proposed method, a surface-cutting approach, generates offset surfaces and flattens them independently using As-Rigid-As-Possible (ARAP) surface mesh parameterization. The second method uses a landmark-based warp to flatten the entire breast volume at once. While the surface-cutting approach is based on the parameterization of individual surfaces, the second method uses control points to realize a coherent, global deformation.Expert evaluations revealed that the surface-cutting method provides intuitive overviews and clear vascular detail, with low metric (2.1-3.5%) and area (3.7-5.8%) distortions. However, independent slice flattening can introduce depth distortions across layers. The landmark warp offers consistent slice alignment and supports direct annotations and measurements, with radiologists favoring it for its anatomical accuracy. Both methods significantly reduced the number of slices needed to review, highlighting their potential for time savings and clinical impact - an essential factor for adopting supine breast MRI.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5500 ], "ac_number": "AC17579320", "doi": "10.34726/hss.2025.122940", "open_access": "yes", "pages": "97", "supervisor": [ 1410 ], "research_areas": [], "keywords": [ "Image reformation", "volumetric parameterization", "medical visualization", "breast MRI", "radiology" ], "weblinks": [], "files": [ { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "kummer-2025-fvo-1-thesis.pdf", "type": "application/pdf", "size": 3422153, "path": "Publication:kummer-2025-fvo-1", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/kummer-2025-fvo-1/kummer-2025-fvo-1-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/kummer-2025-fvo-1/kummer-2025-fvo-1-thesis:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/kummer-2025-fvo-1/", "__class": "Publication" }, { "id": "unterguggenberger-phdthesis", "type_id": "phdthesis", "tu_id": null, "repositum_id": "20.500.12708/215967", "title": "Schnelles Rendern hochdetailierter Geometrie in Echtzeit mit modernen GPUs", "date": "2025", "abstract": "Rasterization-based graphics pipelines are still essential for rendering today’s real-time rendering applications and games. We generally see high demand for efficient rasterization-based rendering techniques. With alternative approaches, such as hardware-accelerated ray tracing, it remains challenging to render more than 60 frames per second (FPS) for many real-time applications across different GPU models, or more than 90 FPS in stereo as often demanded for a smooth experience in Virtual Reality (VR) applications.In recent years, some trends emerged which put pressure on rasterization-based graphics pipelines with high geometry loads. One of these trends is VR rendering, which sometimes not only requires rendering a given scene faster and two times in every frame but some applications or settings require even more than two views to be rendered for the creation of one single frame. Another trend was mainly initiated by Epic Games’ Nanite technology, which enables the rendering of static meshes with sub-pixel geometric detail in real time. As a consequence, skinned models and other scene objects might well be expected to be rendered in similar geometric detail, increasing the geometry load even further.With this dissertation, we contribute fundamental methods and evaluations to high geometry-load scenarios in the context of real-time rendering using rasterization-based graphics pipelines to help reach the performance or quality requirements of modern real-time rendering applications and games:We contribute an in-depth analysis of the state of the art in multi-view rendering and introduce geometry shader-based pipeline variants that can help to improve compatibility and performance in challenging multi-view rendering scenarios. We describe a fundamental approach for artifact-free culling when rendering animated 3D models divided into clusters for ultra-detailed geometry scenarios. With our approach, also parts of skinned models can be culled in a fine-grained manner to match Nanite’s fine-grained culling of static clusters. In contrast to static meshes, finding conservative bounds for clusters of animated meshes is non-trivial, but is achieved with our approach. Finally, in order to render other scene objects—such as, e.g., items or generally shapes which can be described with a parametric function—in similar geometric detail, we describe a method to generate ultra-detailed geometry on the fly: After compute shader-based level of detail (LOD) determination, the resulting parametrically defined shapes are either rendered point-wise or geometry is generated on-chip using the hardware tessellator.In our research, we regard new technological developments such as hardware-accelerated multi-view rendering, new task and mesh shader stages, efficient usage of classical shader stages (such as tessellation shaders), and generally efficient usage of the vast set of features, stages, and peculiarities of modern GPUs, with the goal to accelerate real-time rendering of ultra-detailed geometry.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": "date", "repositum_presentation_id": null, "authors": [ 848 ], "ac_number": "AC17547083", "date_end": "2025-04", "date_start": "2017-01", "doi": "10.34726/hss.2025.132181", "open_access": "yes", "pages": "135", "reviewer_1": [ 1327 ], "reviewer_2": [ 198 ], "rigorosum": "2025-04-10", "supervisor": [ 193 ], "research_areas": [], "keywords": [ "real-time rendering", "GPUs", "levels of detail" ], "weblinks": [], "files": [ { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "unterguggenberger-phdthesis-thesis.pdf", "type": "application/pdf", "size": 3031338, "path": "Publication:unterguggenberger-phdthesis", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/unterguggenberger-phdthesis/unterguggenberger-phdthesis-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/unterguggenberger-phdthesis/unterguggenberger-phdthesis-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "rend" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/unterguggenberger-phdthesis/", "__class": "Publication" }, { "id": "ulschmid-2025-apc", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/215609", "title": "Automated Prioritization for Context-Aware Re-rendering in Editing", "date": "2025", "abstract": "Real-time Monte Carlo path tracing has become a feasible option for interactive 3D scene editing due to recent advancements in GPU ray tracing performance, as well as (AI-accelerated) denoising techniques. While it is thus gaining increasing support in popular modeling software, even minor edits such as adjusting materials or moving small objects typically require current solutions to discard previous samples and restart the image formation process from scratch. A recent solution introduced two adaptive, priority-based re-rendering techniques implementing incremental updates while focusing first on reconstructing regions of high importance and gradually addressing less critical areas. An extensive user study compared these prioritized renderings with conventional same-time re-rendering to evaluate their effectiveness for interactive scene editing. Results indicate a significant preference for incremental rendering techniques for editing small objects over traditional full-screen re-rendering with denoising, even with basic priority policies. Building upon these results, we revisit the underlying design choices and derive more sophisticated priority policies that respect global illumination effects (shadows and reflections) as well as employing attention-based techniques (based either on eye tracking to prioritize areas in the user’s gaze or, alternatively, using the cursor position).", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1501, "image_height": 930, "name": "ulschmid-2025-apc-image.webp", "type": "image/webp", "size": 91268, "path": "Publication:ulschmid-2025-apc", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/ulschmid-2025-apc/ulschmid-2025-apc-image.webp", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/ulschmid-2025-apc/ulschmid-2025-apc-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1954, 1030, 193, 1650 ], "ac_number": "AC17528723", "articleno": "353", "doi": "10.1007/s42979-025-03863-z", "issn": "2661-8907", "journal": "SN Computer Science", "number": "2025", "open_access": "yes", "pages": "14", "publisher": "Springer Nature", "volume": "6", "research_areas": [ "Rendering" ], "keywords": [ "Path Tracing", "Scene editing", "Adaptive rendering", "empirical studies" ], "weblinks": [ { "href": "https://github.com/cg-tuwien/Prioritized-ReRendering", "caption": "GitHub", "description": "GitHub", "main_file": 1 } ], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1501, "image_height": 930, "name": "ulschmid-2025-apc-image.webp", "type": "image/webp", "size": 91268, "path": "Publication:ulschmid-2025-apc", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/ulschmid-2025-apc/ulschmid-2025-apc-image.webp", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/ulschmid-2025-apc/ulschmid-2025-apc-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "ulschmid-2025-apc-paper.pdf", "type": "application/pdf", "size": 1866148, "path": "Publication:ulschmid-2025-apc", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/ulschmid-2025-apc/ulschmid-2025-apc-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/ulschmid-2025-apc/ulschmid-2025-apc-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "d4314", "d9275" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/ulschmid-2025-apc/", "__class": "Publication" }, { "id": "tretyak-2025-tmv", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/216548", "title": "Tactical Medicine VR Training", "date": "2025", "abstract": "This thesis presents the design, implementation, and evaluation of a virtual reality (VR) training simulation for tactical medicine, developed using Unity and optimized for the Meta Quest 3 headset. The system recreates a high-stress scenario inspired by realworld knife attack incidents and integrates hand tracking for natural interaction. The training focuses on triage, bleeding control, and communication with injured patients and bystanders. A qualitative user study involving ten participants with prior first aid or tactical medical experience was conducted to evaluate three research questions: (1) whether realistic scenario design affects perceived stress and immersion, (2) how different interaction methods (hand tracking vs. controllers) impact usability, and (3) whether users view VR as a complement or replacement for traditional training. Thematic analysis of the interviews revealed that realistic audio-visual cues increase immersion, but do not necessarily heighten stress. Hand tracking was perceived as more intuitive, though limited by technical constraints. Participants overwhelmingly saw VR as a valuable supplement to—but not a substitute for—physical training. The findings highlight VR’s potential for scalable, immersive, and safe training solutions in emergency medicine.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 5476 ], "ac_number": "AC17569175", "doi": "10.34726/hss.2025.127193", "open_access": "yes", "pages": "93", "supervisor": [ 166 ], "research_areas": [], "keywords": [ "Virtual Reality", "Tactical Medicine", "Training" ], "weblinks": [], "files": [ { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "tretyak-2025-tmv-thesis.pdf", "type": "application/pdf", "size": 5183792, "path": "Publication:tretyak-2025-tmv", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/tretyak-2025-tmv/tretyak-2025-tmv-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/tretyak-2025-tmv/tretyak-2025-tmv-thesis:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/tretyak-2025-tmv/", "__class": "Publication" }, { "id": "Machegger2018DTI", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/215536", "title": "Evaluating the impact of parameter tuning on glioblastoma segmentation using deep learning", "date": "2025", "abstract": "Background: Glioblastoma multiforme (GBM) is the most aggressive form of brain cancer, characterized by rapid growth and infiltration into surrounding brain tissue. Precise segmentation of GBM, particularly the contrast-enhancing region and necrotic (non-contrast-enhaning) core, is critical for surgical planning and treatment. Manual segmentation methods are time-consuming and subject to high interrater variability, necessitating automated approaches for greater consistency.Objective: This thesis aims to optimize key parameters in deep learning-based segmentation of glioblastomas, focusing on the impact of Batch size, data augmentation strategies, and the number of training cases on model performance, along with tuning the Focal Weight Factor in the Combined Loss Function. The goal is to improve the accuracy of segmenting clinically relevant tumor regions.Methods: In this study, 3D U-Net models were trained using the BraTS Challenge dataset, which includes multimodal MRI scans (T1 post-contrast, FLAIR, and T2) with expert-labeled segmentations reviewed by a neuroradiologist to eliminate interrater variability. The models were evaluated on 108 unseen clinical cases from patients at the University Hospital Salzburg to assess their generalization capability and performance. Segmentation accuracy was measured using Intersection over Union (IoU) and a Custom Weighted Dice Score, focusing on Dice coefficients for the contrast-enhancing and non-contrast-enhancing tumor. Four Case Groups (80, 160, 240, and 314) were used to examine the effect of Case Group size on performance.Results: Models trained with Batch size of four consistently ranked among the top performers, with 80% making it into the top 10, suggesting that larger Batch sizes contribute to better generalization and stability as number of training cases increase. However, augmentations generally resulted in worse performance, except for one outlier—the best performing model—trained with a 1:1 ratio of augmentations to originals, Case Group 314, and a Batch size of one, which performed exceptionally well.Conclusion: Augmentations with a ratio of 1:3 performed poorly, particularly when three variants of one original were included in a Batch size of four, leading to overfitting. This suggests a lack of diversity within the batches caused the model to overfit, whereas a strategy mixing different augmentations within each batch led to better generalization. Case Group 314 models performed best, highlighting the importance of more training data for improved performance.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": "access,title,abstract,date,keywords,supervisor", "repositum_presentation_id": null, "authors": [ 1485 ], "ac_number": "AC17524558", "co_supervisor": [ 1410 ], "date_end": "2018-01-31", "date_start": "2017-03-24", "doi": "10.34726/hss.2025.44861", "matrikelnr": "9900294", "open_access": "yes", "pages": "194", "supervisor": [ 166 ], "research_areas": [ "MedVis" ], "keywords": [ "medical visualization", "diffusion tensor imaging" ], "weblinks": [], "files": [ { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Machegger2018DTI-thesis.pdf", "type": "application/pdf", "size": 6647846, "path": "Publication:Machegger2018DTI", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/Machegger2018DTI/Machegger2018DTI-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/Machegger2018DTI/Machegger2018DTI-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/Machegger2018DTI/", "__class": "Publication" }, { "id": "pahr-2025-nodkant", "type_id": "journalpaper", "tu_id": null, "repositum_id": "20.500.12708/216536", "title": "NODKANT: exploring constructive network physicalization", "date": "2025", "abstract": "Physicalizations, which combine perceptual and sensorimotor interactions, offer an immersive way to comprehend complex data visualizations by stimulating active construction and manipulation. This study investigates the impact of personal construction on the comprehension of physicalized networks. We propose a physicalization toolkit—NODKANT—for constructing modular node-link diagrams consisting of a magnetic surface, 3D printable and stackable node labels, and edges of adjustable length. In a mixed-methods between-subject lab study with 27 participants, three groups of people used NODKANT to complete a series of low-level analysis tasks in the context of an animal contact network. The first group was tasked with freely constructing their network using a sorted edge list, the second group received step-by-step instructions to create a predefined layout, and the third group received a pre-constructed representation. While free construction proved on average more time-consuming, we show that users extract more insights from the data during construction and interact with their representation more frequently, compared to those presented with step-by-step instructions. Interestingly, the increased time demand cannot be measured in users' subjective task load. Finally, our findings indicate that participants who constructed their own representations were able to recall more detailed insights after a period of 10–14 days compared to those who were given a pre-constructed network physicalization. All materials, data, code for generating instructions, and 3D printable meshes are available on https://osf.io/tk3g5/.", "authors_et_al": false, "substitute": null, "main_image": { "description": "An IKEA-like illustration of a person looking at a dataset, assembling a graph manually, and being happy with the result", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1280, "image_height": 536, "name": "pahr-2025-nodkant-teaser.jpg", "type": "image/jpeg", "size": 46516, "path": "Publication:pahr-2025-nodkant", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/pahr-2025-nodkant/pahr-2025-nodkant-teaser.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/pahr-2025-nodkant/pahr-2025-nodkant-teaser:thumb{{size}}.png" }, "sync_repositum_override": "authors,projects", "repositum_presentation_id": null, "authors": [ 1813, 5488, 1850, 5417, 5489, 1059, 1464, 1410 ], "ac_number": "AC17571629", "articleno": "e70140", "doi": "10.1111/cgf.70140", "issn": "1467-8659", "journal": "Computer Graphics Forum", "open_access": "yes", "pages": "12", "publisher": "WILEY", "research_areas": [], "keywords": [ "CCS Concepts", "Empirical studies in visualization", "human-centered computing", "Visualization Application Domains" ], "weblinks": [], "files": [ { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "pahr-2025-nodkant-paper.pdf", "type": "application/pdf", "size": 15020616, "path": "Publication:pahr-2025-nodkant", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/pahr-2025-nodkant/pahr-2025-nodkant-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/pahr-2025-nodkant/pahr-2025-nodkant-paper:thumb{{size}}.png" }, { "description": "An IKEA-like illustration of a person looking at a dataset, assembling a graph manually, and being happy with the result", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1280, "image_height": 536, "name": "pahr-2025-nodkant-teaser.jpg", "type": "image/jpeg", "size": 46516, "path": "Publication:pahr-2025-nodkant", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/pahr-2025-nodkant/pahr-2025-nodkant-teaser.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/pahr-2025-nodkant/pahr-2025-nodkant-teaser:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/pahr-2025-nodkant/", "__class": "Publication" }, { "id": "stoff-2025-pvu", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/209541", "title": "Prototypical Visualization: Using Prototypical Networks for Visualizing Large Unstructured Data", "date": "2025", "abstract": "Making sense of data is something that many professionals are required to do on a daily basis. This can be a difficult task if the amount of data is so large that it can not be easily examined. One effective method of quickly getting an overview of data structure is visualization, but this is not always a feasible solution with large data due to the sheer amount of data and also the potentially high dimensionality. Machine learning models can help with with the organization and classification of data, but they often require large quantities of labeled training data, which is frequently not readily available. This is why models that can reliably classify data based on only few examples for each class are an interesting topic of research. One such kind of model are prototypical networks. They utilize few samples to create an embedding space in fewer dimensions, in which similar data points cluster around a single class prototype. In this thesis, we investigate if the embedding space of a prototypical network makes for a good approach for the purpose of visualizing high-dimensional, unstructured data. The goal is to reduce the dimensionality of the data in such a way that the highdimensional relations and structures between data points are preserved, resulting in 2D representations of the data that form coherent class clusters in a scatter plot visualization. This approach is compared with, and evaluated against, other well known supervised and unsupervised dimensionality reduction techniques. Through quantitative experiments relying on statistical measures, as well as a qualitative evaluation of our results, we find that our ProtoNet is capable of producing point embeddings in which the spatial separation of classes is as good or better than the other methods.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": "projects", "repositum_presentation_id": null, "authors": [ 1865 ], "ac_number": "AC17416388", "doi": "10.34726/hss.2025.119321", "open_access": "yes", "pages": "62", "supervisor": [ 1110 ], "research_areas": [ "InfoVis" ], "keywords": [ "Dimensionality Reduction", "Data Visualization", "Prototypical Network", "ProtoNet", "Class Separation", "Scatter Plot" ], "weblinks": [], "files": [ { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "stoff-2025-pvu-thesis.pdf", "type": "application/pdf", "size": 1529952, "path": "Publication:stoff-2025-pvu", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/stoff-2025-pvu/stoff-2025-pvu-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/stoff-2025-pvu/stoff-2025-pvu-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "d9282" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/stoff-2025-pvu/", "__class": "Publication" }, { "id": "ehlers-2025-battlegraphs", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/217464", "title": "BattleGraphs: Forge, Fortify, and Fight in the Network Arena", "date": "2025", "abstract": "Constructive visualization enables users to create personalized data representations and facilitates early insight generation and sensemaking. Based on NODKANT, a toolkit for creating physical network diagrams using 3D printed parts, we define a competitive network physicalization game: BattleGraphs. In BattleGraphs, two players construct networks independently and\ncompete in solving network analysis benchmark tasks. We propose a workshop scenario where we deploy our game, collect strategies for interaction and analysis from our players, and measure the effectiveness of the strategy with the success of the player to discuss in a reflection phase. Printable parts of the game, as well as instructions, are available through the Open Science Framework at -- https://osf.io/x6zv7/ -- All proceedings (including this submission) available on the eurographics digital library: https://diglib.eg.org/collections/d1483cdb-603e-46b6-b315-d9a6e750427e", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1850, 1813, 5488, 5489, 5417 ], "booktitle": "Visgames 2025: EuroVis Workshop on Visualization Play, Games, and Activities", "date_from": "2025-06-02", "date_to": "2025-06-02", "doi": "10.2312/visgames.20251161", "editor": "Stoiber, C. and Boucher, Magdalena and de Jesus Oliveira, V. A. and Schetinger, Victor and Filipov, Velitchko and Raidou, Renata Georgia and Amabili, L. and Keck, M. and Aigner, Wolfgang", "event": "EuroVis 2025 Workshop on Visualization Play, Games, and Activities (VisGames)", "lecturer": [ 1850, 1813, 5488, 5489, 5417 ], "location": "Luxembourg", "pages": "5", "publisher": "The Eurographics Association", "research_areas": [], "keywords": [ "Network Visualization", "Data Physicalization", "Constructivism", "Visualization Games" ], "weblinks": [], "files": [], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/ehlers-2025-battlegraphs/", "__class": "Publication" }, { "id": "Ehlers_PhD", "type_id": "phdthesis", "tu_id": null, "repositum_id": "20.500.12708/222196", "title": "Inspired by Biology: Towards Visualizing Complex Networks", "date": "2025", "abstract": "The term “biological network” comprises a large and multifaceted set of different types of networks. These different network types bring with it unique visualization and visual analysis challenges. We first survey the literature in order to characterize and identify outstanding gaps in the visualization of biological networks. Inspired by these many challenges and difficulties faced by the field. Specifically, we focus on three challenges of particular interest to us: i) improving the visual quality of commonly employed straight-line node-link diagrams, ii) the visualization of uncertainty in networks, and iii) the visualization of group structures in compound graphs. To tackle these three challenges, we conduct five investigations.To tackle challenge 1, we first investigate the principled and algorithmic splitting of vertices to iteratively resolve edge crossings and thereby improve the readability of graphs. As an alternative solution to challenge 1, we investigate the visualization of so-called ego-networks, which allow for the visualization of only node-relative and node-relevant topology, instead of the entirety of a network. Third, within the context of challenge 2, we investigate the visualization of node attribute uncertainty using animated “wiggliness”, i.e., animated node motion. Fourth, in order to tackle challenge 3, we survey the current state of compound graph visualization and, finally, we combine the aforementioned four works together and develop a prototypical dashboard for the visualization of compound graphs.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": "title,abstract,date,keywords,type_id", "repositum_presentation_id": null, "authors": [ 1850 ], "ac_number": "AC17730567", "co_supervisor": [ 1464 ], "date_end": "2024", "date_start": "2021", "doi": "10.34726/hss.2025.137816", "open_access": "yes", "pages": "287", "supervisor": [ 1410 ], "research_areas": [ "BioVis" ], "keywords": [ "Network visualization" ], "weblinks": [], "files": [ { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Ehlers_PhD-thesis.pdf", "type": "application/pdf", "size": 10158013, "path": "Publication:Ehlers_PhD", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/Ehlers_PhD/Ehlers_PhD-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/Ehlers_PhD/Ehlers_PhD-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/Ehlers_PhD/", "__class": "Publication" }, { "id": "schindler-2025-ssm", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/216205", "title": "Shape shifting : a multiscale optimal transport approach to 3D point cloud comparison", "date": "2025", "abstract": "Advances in measurement technologies and 3D vision have significantly enhanced the speed and precision with which real-world objects and landscapes can be captured and reconstructed. These virtual reconstructions are relevant for surveying applications and are often encoded as point clouds, i.e., a set of 3D coordinates, possibly accompanied by additional attributes like colors or normals. Often, reconstructions of objects or landscapes are acquired over time to monitor their changes. Intuitive visualization that allows one to comprehend the shifts over time in such reconstructions could be of help, but the vast size of the data imposes challenges on comparative visualization pipelines. On the other hand, it is simpler than ever to amass numerous reconstructions of real-world objects, even for novice users. Still, outside of computationally intensive algorithms tailored to applications for the medical domain, there is a gap in approaches that allow for comparing differences within ensembles of shapes. Available algorithms outside of medicine are built upon nearest neighbor queries, which do not scale well to complex shapes and lack guidance for the comparison. Extensive ensembles of spatial data need to be delivered in a structured way to avoid time-intensive manual ordering when there is no chronological ordering implied or known. We designed and implemented a framework to support the comparative visualization of ensembles of point clouds. By utilizing the mature mathematical framework of optimal transport, we circumvent shortcomings of commonly employed nearest neighbor-based approaches and allow our method to compare a whole ensemble of reconstructions in a comprehensive representation. If there is no inherent ordering, our method enables the automatic arrangement of individual point clouds, establishing their relationships and simplifying the analysis process. We derive additional metrics about the whole ensemble, which are then used to enrich the visualization and help to detect patterns of variation within the data. By leveraging fast GPU-based implementations, we enable a smooth transition between displayed point clouds in an animation and offer visual aids that highlight the characteristics of each shape and how these change. Our method processes the data fast and provides comprehensive means to browse through a large ensemble of point clouds.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1760 ], "ac_number": "AC17561836", "doi": "10.34726/hss.2025.123620", "open_access": "yes", "pages": "129", "supervisor": [ 1410 ], "research_areas": [], "keywords": [ "Comparative Visualization", "Point Clouds", "Optimal Transport", "Visual Shape Analytics", "Ensemble Visualization", "Shape Space", "Animation", "Rendering", "Earth Mover's Distance" ], "weblinks": [], "files": [ { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "schindler-2025-ssm-thesis.pdf", "type": "application/pdf", "size": 5753321, "path": "Publication:schindler-2025-ssm", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/schindler-2025-ssm/schindler-2025-ssm-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/schindler-2025-ssm/schindler-2025-ssm-thesis:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/schindler-2025-ssm/", "__class": "Publication" }, { "id": "ecormier-nocca-2025-sls", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/213965", "title": "Single-Exemplar Lighting Style Transfer via Emissive Texture Synthesis and Optimization", "date": "2025", "abstract": "Lighting is a key component in how scenes are perceived. However, many interior lighting situations are currently either handcrafted by expert designers, or simply consist of basic regular arrangements of luminaires, such as to reach uniform lighting at a predefined brightness. Our method aims to bring more interesting lighting configurations to various scenes in a semi-automatic manner designed for fast prototyping by non-expert users. Starting from a single photograph of a lighting configuration, we allow users to quickly copy and adapt a lighting style to any 3D scene. Combining image analysis, texture synthesis, and light parameter optimization, we produce a lighting design for the target 3D scene matching the input image. We validate via a user study that our results successfully transfer the desired lighting style more accurately and realistically than state-of-the-art generic style transfer methods. Furthermore, we investigate the behaviour of our method under potential altern ative choices in an ablation study.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 2126, "image_height": 763, "name": "ecormier-nocca-2025-sls-image.png", "type": "image/png", "size": 1223387, "path": "Publication:ecormier-nocca-2025-sls", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/ecormier-nocca-2025-sls/ecormier-nocca-2025-sls-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/ecormier-nocca-2025-sls/ecormier-nocca-2025-sls-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1949, 1525, 1954, 1946, 193 ], "booktitle": "Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - GRAPP", "date_from": "2025-02-26", "date_to": "2025-03-28", "doi": "10.5220/0013193900003912", "event": "IVAPP 2025 - Part of VISIGRAPP, the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications.", "isbn": "978-989-758-728-3", "lecturer": [ 1954 ], "location": "Porto", "pages": "14", "pages_from": "113", "pages_to": "126", "publisher": "SciTePress", "volume": "1", "research_areas": [ "Rendering" ], "keywords": [ "Lighting Design", "Lighting Style Ttransfer", "Texture Synthesis", "Lighting Optimization" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 2126, "image_height": 763, "name": "ecormier-nocca-2025-sls-image.png", "type": "image/png", "size": 1223387, "path": "Publication:ecormier-nocca-2025-sls", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/ecormier-nocca-2025-sls/ecormier-nocca-2025-sls-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/ecormier-nocca-2025-sls/ecormier-nocca-2025-sls-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "ecormier-nocca-2025-sls-paper.pdf", "type": "application/pdf", "size": 58975673, "path": "Publication:ecormier-nocca-2025-sls", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/ecormier-nocca-2025-sls/ecormier-nocca-2025-sls-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/ecormier-nocca-2025-sls/ecormier-nocca-2025-sls-paper:thumb{{size}}.png" } ], "projects_workgroups": [ "d4314" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/ecormier-nocca-2025-sls/", "__class": "Publication" }, { "id": "Pahr_PhD", "type_id": "phdthesis", "tu_id": null, "repositum_id": "20.500.12708/222160", "title": "From Interactions to Integrated Actions: Exploring Active Perception and Inter-Modality in Data Physicalization", "date": "2025", "abstract": "The growing field of data physicalization holds significant potential for integrating user actionsdirectly into the sense making process through physical artifacts. Two promising factors for physical, as opposed to virtual representations, are physical interaction and multimodal perception. Unmediated interaction in the physical space allows users to manipulate and explore dataphysicalizations in a natural way, harnessing a user’s actions to encode and decode information ina different way than purely virtual representations. In this dissertation, I explore the incorporation of user action as a means of manipulation and perception into data physicalizations, moving from representations where perception only happens after physical interactions, to representations where physical interactions directly stimulate the user’s perception. I investigate four distinct types of user interactions with data physicalizations and show how each of them can support human perception in different ways. Firstly, I show how a modular 3D representation of dynamic data can leverage physical embodiment using natural spatial perception.I demonstrate this by creating a simple interactive physical representation of a space-time-cubemetaphor and investigating it in a case study with a domain expert. Secondly, I investigate the influence of construction — an intuitively physical interaction in the physical space — of apre-defined physical representation on human perception. I show this by designing a networkdata physicalization toolkit and conducting a between-subject study, comparing different ways to instruct a user during construction. Thirdly, I introduce tactile perception of the elastic properties of an object in a multi-modal representation of volume data. I showcase this at the hands of a fabrication pipeline that creates elastic artifacts from volume data using consumer-level 3D printing and validate the method through computational, mechanical, and perceptualstudies. Finally, I explore the benefits of manually operating a physical representation of adynamic process, leveraging the tactile feedback to the user for information encoding. By means of a between-subject user study, I show that integrating a user’s actions into a representation significantly increases engagement.Overall, the results show that even a simple physicalization can highlight the perceptual benefits of physically encoding data by ways of natural perception. Abstract representations have to be learned by users but can be supported by physical interactions, while embodied metaphors profit from direct interactivity if the stimulus fits the sensory capabilities.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": "title,abstract,date,keywords,type_id", "repositum_presentation_id": null, "authors": [ 1813 ], "ac_number": "AC17729893", "co_supervisor": [ 1464 ], "date_end": "2024", "date_start": "2021", "doi": "10.34726/hss.2025.137817", "open_access": "yes", "pages": "124", "supervisor": [ 1410 ], "research_areas": [ "MedVis" ], "keywords": [ "Data physicalization", "Interaction", "Embodiment" ], "weblinks": [], "files": [ { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Pahr_PhD-thesis.pdf", "type": "application/pdf", "size": 3694895, "path": "Publication:Pahr_PhD", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/Pahr_PhD/Pahr_PhD-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/Pahr_PhD/Pahr_PhD-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/Pahr_PhD/", "__class": "Publication" }, { "id": "pointner_simon-2022-maa", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/225169", "title": "Cycle Safely", "date": "2025", "abstract": "This thesis presents a design and implementation of an end-to-end collision prediction and detection pipeline tailored to cyclists. The primary goal is to predict potential collisions between the cyclist (ego agent) and other road users, particularly motorised vehicles, which pose a higher risk due to higher momentum and speed. The proposed pipeline integrates conventional techniques for solving the sub-tasks of object detection, object tracking, and trajectory forecasting. Specifically, Super Fast and Accurate 3D Object Detection (SFA3D) is used for the detection, a Kalman filter-based multi-object tracker for temporal association of these detections, and a machine learning-based model (prediction conditioned on goals in visual multi-agent settings) is adapted and trained for the prediction of future trajectories. CARLA driving simulator facilitates the training and development of the prediction model by creating a synthetic dataset of cycling and the interaction with other road users. The system is evaluated on the synthetic dataset and also on the real-world KITTI dataset, and additional ablation studies examine the contribution of each pipeline stage. Experiments demonstrate that the proposed approach is capable of achieving reliable performance in object detection and tracking tasks. This confirms the feasibility of such a pipeline under limited sensing capabilities, such as LIDAR and GPS/IMU measurements. However, trajectory prediction remains a difficult and computationally expensive task, primarily due to the lack of documented and easily deployable open-source models. The implementation comes with a visualisation framework, built from the Rerun tool, for interactive inspection of the pipeline’s intermediate and final results.The contribution of this thesis can be summarised by the implementation of a framework for cyclist collision detection. It offers insights into how conventional and machine learning methods can be combined into a pipeline, and key limitations and points of future work for the creation of better trajectory prediction in adverse traffic contexts are outlined.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1796 ], "ac_number": "AC17754544", "co_supervisor": [ 948 ], "date_start": "2021-11-29", "doi": "10.34726/hss.2025.111224", "matrikelnr": "01612401", "open_access": "yes", "pages": "86", "supervisor": [ 193 ], "research_areas": [ "Geometry" ], "keywords": [ "cycling", "collision detection", "trajectory prediction", "machine learning" ], "weblinks": [], "files": [ { "description": null, "filetitle": "thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "pointner_simon-2022-maa-thesis.pdf", "type": "application/pdf", "size": 6379604, "path": "Publication:pointner_simon-2022-maa", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/pointner_simon-2022-maa/pointner_simon-2022-maa-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/pointner_simon-2022-maa/pointner_simon-2022-maa-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "WorldScale" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/pointner_simon-2022-maa/", "__class": "Publication" }, { "id": "pahr-2025-holographs", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/216593", "title": "HoloGraphs: An Interactive Physicalization for Dynamic Graphs", "date": "2025", "abstract": "We present HoloGraphs, a novel approach for physically representing, explaining, exploring, and interacting with dynamic networks. HoloGraphs addresses the challenges of visualizing and understanding evolving network structures by providing an engaging method of interacting and exploring dynamic network structures using physicalization techniques. In contrast to traditional digital interfaces, our approach leverages tangible artifacts made from transparent materials to provide an intuitive way for people with low visualization literacy to explore network data. The process involves printing network embeddings on transparent media and assembling them to create a 3D representation of dynamic networks, maintaining spatial perception and allowing the examination of each timeslice individually. Interactivity is envisioned using optional Focus+Context layers and overlays for node trajectories and labels. Focus layers highlight nodes of interest, context layers provide an overview of the network structure, and global overlays show node trajectories over time. In this paper, we outline the design principles and implementation of HoloGraphs and present how elementary digital interactions can be mapped to physical interactions to manipulate the elements of a network and temporal dimension in an engaging matter. We demonstrate the capabilities of our concept in a case study. Using a dynamic network of character interactions from a popular book series, we showcase how it represents and supports understanding complex concepts such as dynamic networks.", "authors_et_al": false, "substitute": null, "main_image": { "description": "a 3d visualization of a dynamic network, made from transparent projector slides stacked in parallel", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 6000, "image_height": 4000, "name": "pahr-2025-holographs-teaser.JPG", "type": "image/jpeg", "size": 5834127, "path": "Publication:pahr-2025-holographs", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/pahr-2025-holographs/pahr-2025-holographs-teaser.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/pahr-2025-holographs/pahr-2025-holographs-teaser:thumb{{size}}.png" }, "sync_repositum_override": "projects", "repositum_presentation_id": null, "authors": [ 1813, 1850, 5417 ], "booktitle": "Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1 GRAPP, HUCAPP and IVAPP: IVAPP,", "date_from": "2025-02-26", "date_to": "2025-02-28", "doi": "10.5220/0013116000003912", "event": "20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP , GRAPP, HUCAPP and IVAPP 2025)", "isbn": "978-989-758-728-3", "lecturer": [ 1813 ], "location": "Porto", "pages": "8", "pages_from": "859", "pages_to": "866", "volume": "1", "research_areas": [], "keywords": [ "Dynamic Networks", "Fabrication", "Information Visualization", "Physicalization" ], "weblinks": [], "files": [ { "description": "a 3d visualization of a dynamic network, made from transparent projector slides stacked in parallel", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 6000, "image_height": 4000, "name": "pahr-2025-holographs-teaser.JPG", "type": "image/jpeg", "size": 5834127, "path": "Publication:pahr-2025-holographs", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/pahr-2025-holographs/pahr-2025-holographs-teaser.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/pahr-2025-holographs/pahr-2025-holographs-teaser:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/pahr-2025-holographs/", "__class": "Publication" } ]