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dc.contributor.authorCollado, José Antonioen_US
dc.contributor.authorLópez, Alfonsoen_US
dc.contributor.authorPérez, Juan Roberto Jiménezen_US
dc.contributor.authorOrtega, Lidia M.en_US
dc.contributor.authorJurado, Juan M.en_US
dc.contributor.authorFeito, Francisco
dc.contributor.editorPosada, Jorgeen_US
dc.contributor.editorSerrano, Anaen_US
dc.description.abstractThe generation of realistic natural scenarios is a longstanding and ongoing challenge in Computer Graphics. LiDAR (Laser Imaging Detection and Ranging) point clouds have been gaining interest for the representation and analysis of real-world scenarios. However, the output of these sensors is conditioned by several parameters, including, but not limited to, distance to scanning target, aperture angle, number of laser beams, as well as systematic and random errors for the acquisition process. Hence, LiDAR point clouds may present inaccuracies and low density, thus hardening their visualization. In this work, we propose reconstructing the surveyed environments to enhance the point cloud density and provide a 3D representation of the scenario. To this end, ground and vegetation layers are detected and parameterized to allow their reconstruction. As a result, point clouds of any required density can be modeled, as well as 3D realistic natural scenarios that may lead to procedural generation through their parameterization.en_US
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.subjectCCS Concepts: Computing methodologies --> Point-based models; Modeling methodologies
dc.subjectComputing methodologies
dc.subjectbased models
dc.subjectModeling methodologies
dc.titleGuided Modeling of Natural Scenarios: Vegetation and Terrainen_US
dc.description.seriesinformationSpanish Computer Graphics Conference (CEIG)
dc.identifier.pages5 pages

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Attribution 4.0 International License
Except where otherwise noted, this item's license is described as Attribution 4.0 International License