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        "id": "schindler-2025-ssm",
        "type_id": "masterthesis",
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        "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.",
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        "title": "Smoke Surfaces of 4D Biological Dynamical Systems",
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        "abstract": "To study biological phenomena, mathematical biologists often employ modeling with ordinary differential equations. A system of ordinary differential equations that describes the state of a phenomenon as a moving point in space across time is known as a dynamical system. This moving point emerges from the initial condition of the system and is referred to as a trajectory that “lives” in phase space, i.e., a space that defines all possible states of the system. In our previous work, we proposed ManyLands [AKS∗19]-an approach to explore and analyze typical trajectories of 4D dynamical systems, using smooth, animated transitions to navigate through phase space. However, in ManyLands the comparison of multiple trajectories emerging from different initial conditions does not scale well, due to overdrawing that clutters the view. We extend ManyLands to support the comparative visualization of multiple trajectories of a 4D dynamical system, making use of smoke surfaces. In this way, the sensitivity of the dynamical system to its initialization can be investigated. The 4D smoke surfaces can be further projected onto lower-dimensional subspaces (3D and 2D) with seamless animated transitions. We showcase the capabilities of our approach using two 4D dynamical systems from biology [Gol11, KJS06] and a 4D dynamical system exhibiting chaotic behavior [Bou15].",
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        "title": "Nested Papercrafts for Anatomical and Biological Edutainment",
        "date": "2022-06",
        "abstract": "In this paper, we present a new workflow for the computer-aided generation of physicalizations, addressing Nested configurations in anatomical and biological structures. Physicalizations are an important component of anatomical and biological education and edutainment. However, existing approaches have mainly revolved around creating data sculptures through digital fabrication. Only a few recent works proposed computer-aided pipelines for generating sculptures, such as papercrafts, with affordable and readily available materials. Papercraft generation remains a Challenging topic by itself. Yet, anatomical and biological applications pose additional Challenges, such as reconstruction complexity and insufficiency to account for multiple, Nested structures—often present in anatomical and biological structures. Our workflow comprises the following steps: (i) define the Nested configuration of the model and detect its levels, (ii) calculate the viewpoint that provides optimal, unobstructed views on inner levels, (iii) perform cuts on the outer levels to reveal the inner ones based on the viewpoint selection, (iv) estimate the stability of the cut papercraft to ensure a reliable outcome, (v) generate textures at each level, as a smart visibility mechanism that provides additional information on the inner structures, and (vi) unfold each textured mesh guaranteeing reconstruction. Our novel approach exploits the interactivity of Nested papercraft models for edutainment purposes.",
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        "doi": "10.1111/cgf.14561",
        "event": "EuroVis 2022 - 24th Eurographics Conference on Visualization",
        "journal": "Computer Graphics Forum",
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        "location": "Rom",
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        "publisher": "Wiley & Sons Ltd",
        "volume": "41,3",
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        "title": "The Anatomical Edutainer",
        "date": "2020-10",
        "abstract": "Physical visualizations (i.e., data representations by means of physical objects) have been used for many centuries in medical and anatomical education. Recently, 3D printing techniques started also to emerge. Still, other medical physicalizations that rely on affordable and easy-to-find materials are limited, while smart strategies that take advantage of the optical properties of our physical world have not been thoroughly investigated. We propose the Anatomical Edutainer, a workflow to guide the easy, accessible, and affordable generation of physicalizations for tangible, interactive anatomical edutainment. The Anatomical Edutainer supports 2D printable and 3D foldable physicalizations that change their visual properties (i.e., hues of the visible spectrum) under colored lenses or colored lights, to reveal distinct anatomical structures through user interaction.",
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        "title": "Anatomical Entertainer: Physical Visualization in a Medical Context",
        "date": "2020-04-24",
        "abstract": "Visualizations are essential for anatomical education of the general public. Traditional\nvisualization methods focus on 2D and 3D information representations, either digital\nor printed, but visualizations also have a physical form. Physical visualization is a\nsubdomain of the traditional visualization domain, where the data is represented by\nmeans of a physical object. Physical visualizations have been reported to lead to greater information insights for the interacting user, but a lot of the fabrication methods to create physical visualizations of the anatomy are not accessible for the general public. In\nthis thesis, we present a workflow to ease the process of creating physical visualizations, made out of paper. The proposed workflow can be used to create two different types of anatomical visualizations. First, we generate 2D visualizations, examinable with color\nfilters that enhance the interactivity of the visualization. To encode multiple channels of information from the anatomical structures, a specific method of color blending is used, which enables the users to access the different anatomical structures selectively, without occlusion. That way the users explore the single layers of the printed visualizations using color filters. Second, 3D papercrafts are generated, which are also examinable with color filters. The anatomical model is unfolded on the paper sheet, can be printed and the user can assemble it and examine it under the color lenses, similarly to the 2D case. The papercrafts may be used as an educational toy in school teaching or for entertainment, since they are very easy to produce and to distribute. We present several 2D and 3D examples of the workflow of the Anatomical Entertainer on models for anatomical education.",
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