Modeling and Enhancement of LiDAR Point Clouds from Natural Scenarios

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dc.contributor.authorCollado, José Antonioen_US
dc.contributor.authorLópez, Alfonsoen_US
dc.contributor.authorJiménez-Pérez, J. Robertoen_US
dc.contributor.authorOrtega, Lidia M.en_US
dc.contributor.authorFeito, Francisco R.en_US
dc.contributor.authorJurado, Juan Manuelen_US
dc.contributor.editorSauvage, Basileen_US
dc.contributor.editorHasic-Telalovic, Jasminkaen_US
dc.date.accessioned2022-04-22T07:54:35Z
dc.date.available2022-04-22T07:54:35Z
dc.date.issued2022
dc.description.abstractThe 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.en_US
dc.description.sectionheadersPosters
dc.description.seriesinformationEurographics 2022 - Posters
dc.identifier.doi10.2312/egp.20221016
dc.identifier.isbn978-3-03868-171-7
dc.identifier.issn1017-4656
dc.identifier.pages35-36
dc.identifier.pages2 pages
dc.identifier.urihttps://doi.org/10.2312/egp.20221016
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/egp20221016
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCCS Concepts: Computing methodologies --> Point-based models; Modeling methodologies
dc.subjectComputing methodologies
dc.subjectPoint
dc.subjectbased models
dc.subjectModeling methodologies
dc.titleModeling and Enhancement of LiDAR Point Clouds from Natural Scenariosen_US
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