43-Issue 1

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https://diglib.eg.org/handle/10.2312/3606942

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Browsing 43-Issue 1 by Subject "methods and applications"

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    Advances in Data‐Driven Analysis and Synthesis of 3D Indoor Scenes
    (© 2024 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd., 2024) Patil, Akshay Gadi; Patil, Supriya Gadi; Li, Manyi; Fisher, Matthew; Savva, Manolis; Zhang, Hao; Alliez, Pierre; Wimmer, Michael
    This report surveys advances in deep learning‐based modelling techniques that address four different 3D indoor scene analysis tasks, as well as synthesis of 3D indoor scenes. We describe different kinds of representations for indoor scenes, various indoor scene datasets available for research in the aforementioned areas, and discuss notable works employing machine learning models for such scene modelling tasks based on these representations. Specifically, we focus on the and of 3D indoor scenes. With respect to analysis, we focus on four basic scene understanding tasks – 3D object detection, 3D scene segmentation, 3D scene reconstruction and 3D scene similarity. And for synthesis, we mainly discuss neural scene synthesis works, though also highlighting model‐driven methods that allow for human‐centric, progressive scene synthesis. We identify the challenges involved in modelling scenes for these tasks and the kind of machinery that needs to be developed to adapt to the data representation, and the task setting in general. For each of these tasks, we provide a comprehensive summary of the state‐of‐the‐art works across different axes such as the choice of data representation, backbone, evaluation metric, input, output and so on, providing an organized review of the literature. Towards the end, we discuss some interesting research directions that have the potential to make a direct impact on the way users interact and engage with these virtual scene models, making them an integral part of the metaverse.
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    Identifying and Visualizing Terrestrial Magnetospheric Topology using Geodesic Level Set Method
    (© 2024 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd., 2024) Xiong, Peikun; Fujita, Shigeru; Watanabe, Masakazu; Tanaka, Takashi; Cai, Dongsheng; Alliez, Pierre; Wimmer, Michael
    This study introduces a novel numerical method for identifying and visualizing the terrestrial magnetic field topology in a large‐scale three‐dimensional global MHD (Magneto‐Hydro‐Dynamic) simulation. The (un)stable two‐dimensional manifolds are generated from critical points (CPs) located north and south of the magnetosphere using an improved geodesic level set method. A boundary value problem is solved numerically using a shooting method to forward a new geodesic level set from the previous set. These sets are generated starting from a small circle whose centre is a CP. The level sets are the sets of mesh points that form the magnetic manifold, which determines the magnetic field topology. In this study, a consistent method is proposed to determine the magnetospheric topology. Using this scheme, we successfully visualize a terrestrial magnetospheric field topology and identify its two neutral lines using the global MHD simulation. Our results present a terrestrial topology that agrees well with the recent magnetospheric physics and can help us understand various nonlinear magnetospheric dynamics and phenomena. Our visualization enables us to fill the gaps between current magnetospheric physics that can be observed via satellites and nonlinear dynamics, particularly, the bifurcation theory, in the future.