Eurographics Digital Library
Not a member yet
17121 research outputs found
Sort by
Impact of Non-Player Characters on the Gaming Experience: Simulation Game vs. Competitive Exergame
No full textNon-player characters (NPCs) play a crucial role in the gaming experience and should be designed to suit the characteristics of each game genre. This study examines the impact of AI-driven NPCs on player experience by comparing their impact in a hospital management simulation game and in a competitive exergame called Fitoon. In the simulation game, a needs-based AI system was implemented, where agents autonomously make decisions based on their internal states, such as hunger or stress. In Fitoon, machine learning techniques, including reinforcement and imitation learning, were applied to train agents capable of competing against players in obstacle races. Through user testing utilizing the In-Game version of the Game Experience Questionnaire, this study examines how the presence of these NPCs influences the players' perception of the gaming experience in both contexts. The results indicate that while NPCs in the simulation game have a greater impact on reducing feelings of tedium and boredom, in the exergame, they significantly increase the sense of challenge.Spanish Computer Graphics Conference (CEIG)Full Paper
View-Dependent Visibility Optimization for Monte Carlo Volume Visualization
No full textCompared to classic ray marching-based approaches, Monte Carlo ray tracing for volume visualization can provide faster frame times through progressive rendering, improved image quality, and allows for advanced illumination models more easily. Techniques such as the view-dependent optimization of visibility and illumination of important regions, however, have been formulated for ray marching and rely on stepwise sampling along rays, and are thus incompatible with free-flight distance sampling of state-of-the-art Monte Carlo methods. In this paper we derive such a view-dependent optimization for Monte Carlo ray tracing where the visibility to the camera, the illumination and opacity of important regions is optimized for both single and multiple scattering rendering. For this we define a post-interpolative importance function, introduce an efficient data structure to sample, approximate and optimize the integrated extinction along rays, and devise an efficient Monte Carlo estimator for interactive visualization. Our method enables view-dependent visibility optimization with moderate memory overhead and unbiased, progressive Monte Carlo volume visualization. We demonstrate our method for various volume data sets as well as for data-dependent and spatially-dependent importance functions.Computer Graphics ForumEclipsing the Ordinary in Visualization44
VVRT: Virtual Volume Raycaster
No full textVirtual Ray Tracer (VRT) is an educational tool to provide users with an interactive environment for understanding ray-tracing concepts. Extending VRT, we propose Virtual Volume Raycaster (VVRT), an interactive application that allows to view and explore the volume raycasting process in real-time. The goal is to help users-students of scientific visualization and the general public-to better understand the steps of volume raycasting and their characteristics, for example the effect of early ray termination. VVRT shows a scene containing a camera casting rays which interact with a volume. Learners are able to modify and explore various settings, e.g., concerning the transfer function or ray sampling step size. Our educational tool is built with the cross-platform engine Unity, and we make it fully available to be extended and/or adjusted to fit the requirements of courses at other institutions, educational tutorials, or of enthusiasts from the general public. Two user studies demonstrate the effectiveness of VVRT in supporting the understanding and teaching of volume raycasting.EuroVis 2025 - Education PapersEducation Papers Session
A Divisive Normalization Brightness Model for Tone Mapping
No full textTone mapping operators (TMOs) are essential in digital graphics, enabling the conversion of high-dynamic-range (HDR) scenes to the limited dynamic range reproducible by display devices, while simultaneously preserving the perceived qualities of the scene. An important aspect of perceived scene fidelity is brightness: the perceived luminance at every position in the scene. We introduce DINOS, a neurally inspired brightness model combining the multi-scale architecture of several historical models with a divisive normalization structure suggested by experimental results from recent studies on neural responses in the human visual pathway. We then evaluate the brightness perception predicted by DINOS against several well-known brightness illusions, as well as human preferences from an existing study which quantitatively ranks 14 popular TMOs. Finally, we propose BRONTO: a brightness-optimized TMO that directly leverages DINOS to perform locally varying exposure. We demonstrate BRONTO's efficacy on a variety of HDR scenes and compare its performance against several other contemporary TMOs.Eurographics Symposium on RenderingLight and Brightnes
FairSpace: An Interactive Visualization System for Constructing Fair Consensus from Many Rankings
No full textDecisions involving algorithmic rankings affect our lives in many ways, from product recommendations, receiving scholarships, to securing jobs. While tools have been developed for interactively constructing fair consensus rankings from a handful of rankings, addressing the more complex real-world scenario- where diverse opinions are represented by a larger collection of rankings- remains a challenge. In this paper, we address these challenges by reformulating the exploration of rankings as a dimension reduction problem in a system called FairSpace. FairSpace provides new views, including Fair Divergence View and Cluster Views, by juxtaposing fairness metrics of different local and alternative global consensus rankings to aid ranking analysis tasks.We illustrate the effectiveness of FairSpace through a series of use cases, demonstrating via interactive workflows that users are empowered to create local consensuses by grouping rankings similar in their fairness or utility properties, followed by hierarchically aggregating local consensuses into a global consensus through direct manipulation. We discuss how FairSpace opens the possibility for advances in dimension reduction visualization to benefit the research area of supporting fair decision-making in ranking based decision-making contexts. Code, datasets and demo video available at: osf.io/d7cwkComputer Graphics ForumInclusive Visualizatio
Traffic Flow Reconstruction Using Two-Stage Optimization Based on Microscopic and Macroscopic Features
No full textThis paper presents a two-stage optimization method for traffic reconstruction that considers both microscopic and macroscopic features. The method employs a microscopic driving model and uses the average speeds in the lanes as a macroscopic metric to reconstruct traffic that balances the characteristics of traffic flow and vehicle behaviors. Our results on the NGSIM dataset, conducted primarily on straight road segments, demonstrate that the proposed method effectively balances the preservation of microscopic-level details with the simulation of macroscopic traffic flows. Both stages of our method outperform previous work in their respective domains. Furthermore, animated results rendered in the CARLA simulator highlight the realism of the generated driving behaviors, underscoring the model's ability to accurately reproduce various scenarios observed in real-world traffic. By recovering physical simulation parameters from real data, our framework can be utilized to generate diverse, realistic traffic flows, supporting applications such as traffic animation, data augmentation, system testing, and traffic behavior analysis.Pacific Graphics Conference Papers, Posters, and DemosVehicle Dynamics and Interaction
WotaBeats: Avatar-based Rhythm Interaction Applied Wotagei in Virtual Reality Experience
No full textThis paper presents a novel interactive system that combines Wotagei culture and virtual reality (VR), with the aim of providing an immersive training platform for beginners and experienced dancers. Despite the growing popularity of Wotagei, current training resources are limited. To address this gap, the system integrates intuitive gaming elements from popular rhythm games, motion capture technology, and interactive virtual environments, facilitating effective learning. By leveraging VR's immersive capabilities, the system significantly enhances user engagement, providing a culturally authentic and accessible platform for mastering Wotagei.Pacific Graphics Conference Papers, Posters, and DemosPosters and Demo
Prompting Meaning: Optimizing Prompt Engineering for Architectural Point Cloud Interpretation
No full textThree-dimensional point cloud visualisation is essential for preserving and analysing built heritage by providing detailed insights into architectural forms and spatial configurations. Although human perception naturally integrates visual, spatial and contextual information, AI systems have yet to match this interpretive ability, particularly about 3D point clouds. This gap in interpretation highlights the need for AI approaches that process 3D data not only geometrically but also semantically. To address this challenge, the 3D.LLM project is exploring how combining point clouds with large language models (LLMs) can improve spatial and linguistic understanding. This paper presents a prompt engineering strategy developed as part of the 3D.LLM project to improve the semantic interpretation of architectural point clouds. By linking spatial attributes to language-based reasoning, LLMs are employed to generate richer and more accurate descriptions of cultural heritage environments. Unlike conventional geometric segmentation approaches, which often fail to capture architectural nuances, this system enables a spatially aware and flexible interpretation of 3D data. To refine the AI outputs and ensure spatial precision, domain-specific benchmarks such as ArCH and Objaverse XL have been employed. Preliminary findings suggest that prompt engineering significantly improves interpretability, descriptive accuracy and contextual depth, outperforming traditional automated methods. Beyond improving accessibility to architectural heritage information, this approach encourages interdisciplinary collaboration by making complex 3D structures more accessible and useful to scholars, conservators and a wider audience.Digital HeritageSemantics-driven Interaction with Digitized Heritag
Spherical Harmonic Exponentials for Efficient Glossy Reflections
No full textWe propose a high-performance and compact method for computing glossy specular reflections. Commonly-used prefiltered environment maps have large storage requirements and high error due to constrained treatment of view-dependence. We propose a factorized spherical harmonic exponential representation that exploits new observations of the benefits of log-space reconstruction for reflectance. Our method is compact, properly accounts for view-dependent reflections, and is more accurate than the state-of-the-industry solutions. We achieve higher quality results with an order of magnitude less memory, all with efficient and alias-free reconstruction of glossy reflections from environment lights and continuously-varying material roughness.Computer Graphics ForumReal-Time Rendering44