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Nicolas Brodu
Researcher at French Institute for Research in Computer Science and Automation
Publications - 56
Citations - 2621
Nicolas Brodu is an academic researcher from French Institute for Research in Computer Science and Automation. The author has contributed to research in topics: Granular material & Point cloud. The author has an hindex of 18, co-authored 50 publications receiving 2170 citations. Previous affiliations of Nicolas Brodu include Duke University & University of Rennes.
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Accurate 3D comparison of complex topography with terrestrial laser scanner: Application to the Rangitikei canyon (N-Z)
TL;DR: In this article, a 3D point cloud comparison method is proposed to measure surface changes via 3D surface estimation and orientation in 3D at a scale consistent with the local surface roughness.
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3D terrestrial lidar data classification of complex natural scenes using a multi-scale dimensionality criterion: Applications in geomorphology
Nicolas Brodu,Dimitri Lague +1 more
TL;DR: A multi-scale measure of the point cloud dimensionality around each point, which characterizes the local 3D organization is defined and its efficiency in separating riparian vegetation from ground and classifying a mountain stream as vegetation, rock, gravel or water surface is illustrated.
Posted Content
3D Terrestrial lidar data classification of complex natural scenes using a multi-scale dimensionality criterion: applications in geomorphology
Nicolas Brodu,Dimitri Lague +1 more
TL;DR: In this article, a multi-scale measure of the point cloud dimensionality around each point is defined, which characterizes the local 3D organization, and a probabilistic confidence is given at each point, allowing the user to remove the points for which the classification is uncertain.
Journal ArticleDOI
Spanning the scales of granular materials through microscopic force imaging
TL;DR: This calculation explains how the combination of packing structure and contact deformations produce the observed nontrivial mechanical response of the packing, revealing a surprising microscopic particle deformation enhancement mechanism.
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Super-Resolving Multiresolution Images With Band-Independent Geometry of Multispectral Pixels
TL;DR: A new resolution enhancement method is presented for multispectral and multiresolution images, such as those provided by the Sentinel-2 satellites, where band-dependent information is separated from information that is common to all bands, to preserve the subpixel details.