Journal: Abstracts of the ICA

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Abbreviation

Publisher

Copernicus

Journal Volumes

ISSN

2570-2106

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Publications 1 - 10 of 35
  • Zuo, Chenyu; Grübel, Jascha (2023)
    Abstracts of the ICA
  • Hurni, Lorenz; Gkonos, Charalampos; Bär, Hans Rudolf (2019)
    Abstracts of the ICA
  • The reading strategies of a map-based dashboard
    Item type: Other Conference Item
    Zuo, Chenyu; Ding, Linfang; Meng, Liqiu (2021)
    Abstracts of the ICA ~ 30th International Cartographic Conference (ICC 2021)
  • Zimmermann, Wenke; Hurni, Lorenz (2019)
    Abstracts of the ICA
  • Schnürer, Raimund; Cengiz Öztireli, A.; Heitzler, Magnus; et al. (2021)
    Abstracts of the ICA
    Human figures frequently occur on pictorial maps besides other illustrative entities. In this work, we present how to automatically derive 3D depictions from these 2D human figures. Previous research has shown that silhouettes, body parts, and joints of 2D human figures in common poses can be detected on pictorial maps by artificial neural networks (Schnürer et al., 2019). Architectures for these networks have been also developed to reconstruct 3D models of real persons from photos in good accuracy (Varol et al., 2018). Single-view methods are particularly suited for our use case since pictorial figures are usually drawn from one perspective only. Furthermore, a trend can be observed to represent the recovered 3D models by implicit surfaces, expressed by level sets of functions (Saito et al., 2019) or signed distance functions (Wang et al., 2019). Compared to other 3D structures, implicit geometries are memory-efficient, but they require special ray tracing algorithms like marching cubes or sphere tracing to be rendered. We examine two approaches: (1) A convolutional neural network, consisting of a feature extractor and a head network, shall learn to directly predict body parts and joints of a 3D model from a 2D image. For this approach, a large amount of training data is essential, for instance, body scans from real persons (e.g. Human3.6M1) or synthetically created persons (e.g. SURREAL2). For our case, these 3D models may be additionally distorted or enriched by rigged human characters from computer games. After converting the geometries from explicit into implicit forms (e.g. mesh-to-sdf3), the network is trained to estimate the resulting values of sample points. (2) Implicit function parameters can be stepwise optimized, for example by Stochastic Gradient Descent, to reduce differences between the target image and its approximation. The latter is a projection of 3D primitives which are combined, transformed, morphed, or deformed by mathematical operations (Pasko et al., 1995). This approach facilitates to formulate constraints such as the connectivity of body parts or rotation angles of joints, but it requires more iterations and eventually ends in a local minimum. The following challenges exist for both approaches: Due to occlusions, multiple reconstruction outputs are plausible. Perhaps, a generative model such as a variational autoencoder or generative adversarial network needs to be introduced to reflect the variety of poses by latent codes. Moreover, a certain strategy may be pursued to sample equally points near the surface, within the body, and in the surrounding space so that local details and thin parts (e.g. fingers) can be preserved (Paschalidou et al., 2020). To speed up the training or optimization process, possibly a meta-learning algorithm may help to find good initialization parameters (Sitzmann et al., 2020). Since human figures on maps are mostly hand-drawn or manually created with graphic software, the camera perspective or lighting conditions may not be fully consistent. It is not clear yet whether this has an impact on differentiable rendering methods (Niemeyer et al., 2020), which may be applied in our networks. Lastly, the texture needs to be mapped to the 3D model and estimated for the hidden parts, which can be achieved by a subnetwork (Saito et al., 2019). We will evaluate the two approaches according to their effectiveness and efficiency. Based on the outcomes of related works and the proposed methods to overcome the challenges, we are optimistic to create meaningful representations. When being successful, the inferred 3D figures could emerge from the original map by augmented reality devices. The figures could then be animated and act as guides on touristic maps or storytellers on historic maps in museums. Due to their attractiveness, the generated 3D figures may raise the interest of people, especially children, in maps and may also serve educative purposes.
  • Kaleidoscope of Swiss Cartography
    Item type: Other Conference Item
    Räber, Stefan; Hurni, Lorenz (2019)
    Abstracts of the ICA
  • Sieber, René; Eichenberger, Remo; Hurni, Lorenz (2019)
    Abstracts of the ICA
  • Hurni, Lorenz (2024)
    Abstracts of the ICA
    Cartography deals with the interference-free transfer of spatial information from the real world to the map user by means of graphic visualisation methods. The article begins by looking at cartographic modelling and the associated methods, challenges and possible misuses. The Institute of Cartography and Geoinformation (IKG) at ETH Zurich which will celebrate its 100th anniversary in 2025, deals with such questions for a long time, even in its predecessor chairs before the institute was founded by Professor Eduard Imhof in 1925. In the second part, many examples of the institute’s map projects which underpin this search for the ideal map will be presented. The history of the institute is currently being researched by a group of members of the institute. A commemorative volume will be published in 2025, and a scientific colloquium will be held in Zurich in June 2025 to present the results and current work. This summary therefore also provides a brief overview of the history, key people and projects of ETH Cartography. Cartography is concerned with the symbolic, graphic representation of spatial data and information on suitable output media such as paper or electronic devices. The starting point is our real environment, which is initially recorded using surveying equipment, sensors and the like. This can result in direct images such as satellite images, but these are not yet interpreted. As a rule, geo-objects are defined into which the initial image (or, if surveying equipment is used, directly in the field) is then segmented, either automatically or manually. This results in modelling; not every detail is reproduced on a map, but only that which is relevant for the purpose of the map and is also adapted to the selected scale. When modelling, the content of the real world is deliberately selected and simplified, and the geo-objects are represented by clear graphic symbols. With further cartographic generalisation, these effects and measures become even more obvious. Modelling therefore means simplification, but also alienation of the original content in the final representation. Eduard Imhof commented on this in 1981: “...maps are artificially produced worlds and therefore actually illusory worlds.” The reason for this alienation in cartography lies in the endeavour to convey the geographical situation as vividly and userfriendly as possible, while avoiding disturbing or confusing details or irrelevant content. The greatest possible objectivity should still be maintained in the presentation of spatial information. The first part of this article will therefore use examples to illustrate how this is done in cartography. However, examples of fictional maps that have nothing to do with the real world and misuse of these visualisation methods will also be shown.
  • Zuo, Chenyu; Balac, Milos; Grübel, Jascha; et al. (2024)
    Abstracts of the ICA
  • Schnürer, Raimund; Dind, Cédric; Schalcher, Stefan; et al. (2020)
    Abstracts of the ICA ~ Central European Cartographic Conference and 68th German Cartography Congress – EuroCarto 2020
    Digitalization in schools requires a rethinking of teaching materials and methods in all subjects. This upheaval also concerns traditional print media, like school atlases used in geography classes. In this work, we examine the cartographic technological feasibility of extending a printed school atlas with digital content by augmented reality (AR). While previous research rather focused on topographic three-dimensional (3D) maps, our prototypical application for Android tablets complements map sheets of the Swiss World Atlas with thematically related data. We follow a natural marker approach using the AR engine Vuforia and the game engine Unity. We compare two workflows to insert geo-data, being correctly aligned with the map images, into the game engine. Next, the imported data are transformed into partly animated 3D visualizations, such as a dot distribution map, curved lines, pie chart billboards, stacked cuboids, extruded bars, and polygons. Additionally, we implemented legends, elements for temporal and thematic navigation, a screen capture function, and a touch-based feature query for the user interface. We evaluated our prototype in a usability experiment, which showed that secondary school students are as effective, interested, and sustainable with printed as with augmented maps when solving geographic tasks.
Publications 1 - 10 of 35