EG 2022 - Posters

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https://diglib.eg.org/handle/10.2312/2633166

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Browsing EG 2022 - Posters by Subject "based models"

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    Modeling and Enhancement of LiDAR Point Clouds from Natural Scenarios
    (The Eurographics Association, 2022) Collado, José Antonio; López, Alfonso; Jiménez-Pérez, J. Roberto; Ortega, Lidia M.; Feito, Francisco R.; Jurado, Juan Manuel; Sauvage, Basile; Hasic-Telalovic, Jasminka
    The generation of realistic natural scenarios is a longstanding and ongoing challenge in Computer Graphics. A common source of real-environmental scenarios is open point cloud datasets acquired by LiDAR (Laser Imaging Detection and Ranging) devices. However, these data have low density and are not able to provide sufficiently detailed environments. In this study, we propose a method to reconstruct real-world environments based on data acquired from LiDAR devices that overcome this limitation and generate rich environments, including ground and high vegetation. Additionally, our proposal segments the original data to distinguish among different kinds of trees. The results show that the method is capable of generating realistic environments with the chosen density and including specimens of each of the identified tree types.
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    SIG-based Curve Reconstruction
    (The Eurographics Association, 2022) Marin, Diana; Ohrhallinger, Stefan; Wimmer, Michael; Sauvage, Basile; Hasic-Telalovic, Jasminka
    We introduce a new method to compute the shape of an unstructured set of two-dimensional points. The algorithm exploits the to-date rarely used proximity-based graph called spheres-of-influence graph (SIG). We filter edges from the Delaunay triangulation belonging to the SIG as an initial graph and apply some additional processing plus elements from the Connect2D algorithm. This combination already shows improvements in curve reconstruction, yielding the best reconstruction accuracy compared to state-of-the-art algorithms from a recent comprehensive benchmark, and offers potential of further improvements.