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dc.contributor.authorMorel, Julesen_US
dc.contributor.authorBac, Alexandraen_US
dc.contributor.authorKanai, Takashien_US
dc.contributor.editorBiasotti, Silvia and Pintus, Ruggero and Berretti, Stefanoen_US
dc.date.accessioned2020-11-12T05:42:04Z
dc.date.available2020-11-12T05:42:04Z
dc.date.issued2020
dc.identifier.isbn978-3-03868-124-3
dc.identifier.issn2617-4855
dc.identifier.urihttps://doi.org/10.2312/stag.20201242
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/stag20201242
dc.description.abstractThis paper presents a method designed to finely approximate ground surfaces from UAV photogrammetric point clouds by relying on statistical filters to separate vegetation from potential ground points, dividing the whole plot in similar complexity sub-plots through an optimized tilling, and filling holes by blending multiple local approximations through the partition of unity principle. Experiments on very different terrain topology show that our approach leads to significant improvement over the state-of-the-art method.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectComputing methodologies ? Point
dc.subjectbased models
dc.subjectMesh models
dc.subjectModeling methodologies
dc.titleDigital Terrain Model From UAV Photogrammetric Dataen_US
dc.description.seriesinformationSmart Tools and Apps for Graphics - Eurographics Italian Chapter Conference
dc.description.sectionheadersAcquisition and Modelling
dc.identifier.doi10.2312/stag.20201242
dc.identifier.pages77-87


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