Browsing by Author "Mammen, Sebastian von"

Now showing 1 - 6 of 6
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    Integrating Julia Code into the Unity Game Engine to Dive into Aquatic Plant Growth
    (The Eurographics Association, 2023) Lewerentz, Anne; Manke, Nico; Schantz, David; Sarmento Cabral, Juliano; Mammen, Sebastian von; Pelechano, Nuria; Liarokapis, Fotis; Rohmer, Damien; Asadipour, Ali
    Ecologists use process-based ecological models to predict biodiversity, but their complex results can be challenging to com- municate. This challenge can be addressed through interactive visual simulations, which are easy to create with sophisticated game engines such as Unity. However, mechanistic models are increasingly written in the Julia programming language and Unity does not support its integration. In this paper, we present a Julia-Unity plugin that allows direct coupling of Julia and Unity codes. It was developed in a user-centred, iterative manner. The given use case of an immersive, interactive simulation of a macrophyte growth model was tailored to public outreach and science communication. The resulting, rather versatile plugin is a novel tool that features immersive visualisations of Julia-coded simulation models, ecological or otherwise. Due to the features of a game engine, they are particularly apt to engage a wider audience, facilitate collaboration and interdisciplinary work, and enable the exploration of complex systems.
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    Investigating Crowdsourced Help Facilities for Enhancing User Guidance
    (The Eurographics Association, 2023) Babu, Sooraj K.; Brandner, Tobias; Truman, Samuel; Mammen, Sebastian von; Pelechano, Nuria; Liarokapis, Fotis; Rohmer, Damien; Asadipour, Ali
    We present two help facilities aimed at addressing the challenges faced by users new to a software. Software documentation should ideally familiarise with the overall functionality, navigate through the concrete workflows, and opportunities for customisation. Large degrees of freedom in the use and vast basic scopes, however, often make it infeasible to convey this information upfront. Rather, it needs to be broken into helpful bits and pieces which are delivered at appropriate times. In order to address this challenge, we have designed two concrete help facilities, i.e. tooltips and tips-of-the-day, to feature crowdsourced information. In this paper, we present the results of a formative study to implement early proofs-of-concept for the open-source game authoring platform Godot. To support further research, we have made the code base publicly available on GitHub.
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    Mitigation of Fear Triggers for Image Viewing in Virtual Reality
    (The Eurographics Association, 2023) Hetterich, Amelie; Mammen, Sebastian von; Pohl, Daniel; Abey Campbell; Claudia Krogmeier; Gareth Young
    Modern VR image viewers combine immersive photos with audio, special effects and haptics to provide a highly immersive experience. However, users with specific phobias may encounter discomfort while browsing through random images, specifically, considering the high presence in VR. We explore strategies to reduce fear triggers and implement tailored mitigation measures in our image viewing app, specifically for 3D and spherical images. We address automating fear reduction in different VR formats, audio, and special effects to improve the accessibility and experience for VR image viewer users with specific phobias.
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    Programmatic Design and Architecture of an Immersive Laser Laboratory
    (The Eurographics Association, 2023) Müller, Andreas; Müller, Stefan; Brixner, Tobias; Mammen, Sebastian von; Pelechano, Nuria; Liarokapis, Fotis; Rohmer, Damien; Asadipour, Ali
    femtoPro provides an immersive laser laboratory experience for training, experimentation and analysis. In this paper, we present its programmatic design and architecture driven by requirements such as: accurate (non-)linear optics calculations, real-time performance on virtual reality (VR) headsets, easy authoring capabilities of pedagogical ''quests'', as well as natural user interactions and effective, multisensory feedback. We elaborate on how we tackle these challenges considering frontend components and the simulation backend. Notable features encompass an incremental, graph-based laser path solver algorithm with caching capabilities, a volumetric pulse shape renderer with accurately mapped color and transparency, an intuitive interaction system that translates coarse hand motions into precise adjustments, a comprehensive interface for configuring, conducting, and analyzing complex experiments with double precision accuracy including time-series measurements with moving platforms, and a generally flexible, modular architecture achieved through event-based communication, dynamic binding, and other state-of-the-art coding principles. Most of our proposed solutions should be directly applicable to similar immersive science laboratories, independently of their concrete domain.
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    Real-Time Music-Driven Movie Design Framework
    (The Eurographics Association, 2022) Hofmann, Sarah; Seeger, Maximilian; Rogge-Pott, Henning; Mammen, Sebastian von; Ronfard, Rémi; Wu, Hui-Yin
    Cutting to music is a widely used stylistic device in film making. The usual process involves an editor manually adjusting the movie's sequences contingent upon beat or other musical features. But with today's movie productions starting to leverage real-time systems, manual effort can be reduced. Automatic cameras can make decisions on their own according to pre-defined rules, even in real time. In this paper, we present an approach to automatically create a music video. We have realised its implementation as a coding framework integrating with the fmod api and Unreal Engine 4. The framework provides the means to analyze a music stream at runtime and to translate the extracted features into an animation story line, supported by cinematic cutting. We demonstrate its workings by means of an instance of an artistic, music-driven movie.
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    User-Centered Engineering of an Interactive Land Use Exploration Tool
    (The Eurographics Association, 2023) Buhl, Tobias; Marcomin, David; Fallert, Stefan; Blechschmidt, Jana; Bönisch, Franziska; Mark, Robert; Cabral, Juliano Sarmento; Mammen, Sebastian von; Dutta, Soumya; Feige, Kathrin; Rink, Karsten; Zeckzer, Dirk
    In this paper we showcase a system for visualizing and predicting land-use data. The time series-based visualization application strives to improve science communication by facilitating the understanding of land-use change and is backed up by a machine learning-based land-use prediction application that imputes historic data and generates predictions of land use in the future. To present the project, we discuss the system's requirements which were developed by means of a User-Centered Engineering approach, elaborate on its current, early state of development and the corresponding results and finally discuss areas of potential improvement.