G
George Vosselman
Researcher at University of Twente
Publications - 231
Citations - 12623
George Vosselman is an academic researcher from University of Twente. The author has contributed to research in topics: Point cloud & Laser scanning. The author has an hindex of 50, co-authored 219 publications receiving 11244 citations. Previous affiliations of George Vosselman include Delft University of Technology & ITC Enschede.
Papers
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Journal ArticleDOI
Experimental comparison of filter algorithms for bare-Earth extraction from airborne laser scanning point clouds
G. Sithole,George Vosselman +1 more
TL;DR: In general, filters that estimate local surfaces are found to perform best and should be directed towards the usage of additional data sources, segment-based classification, and self-diagnosis of filter algorithms.
Book
Airborne and Terrestrial Laser Scanning
George Vosselman,Hans-Gerd Maas +1 more
TL;DR: Airborne and Terrestrial Laser Scanning has been awarded the Karl Kraus Medal by the ISPRS and written by a team of international experts, this book provides a comprehensive overview of the major applications of airborne and terrestrial laser scanning.
Slope based filtering of laser altimetry data
TL;DR: In this article, a new method is proposed for filtering laser data, which is closely related to the erosion operator used for mathematical grey scale morphology, based on height differences in a representative training dataset, filter functions are derived that either preserve important terrain characteristics or minimise the number of classification errors.
3d building model reconstruction from point clouds and ground plans
George Vosselman,Sander Dijkman +1 more
TL;DR: In this paper, a three-dimensional Hough transform is used for the extraction of planar faces from the irregularly distributed point clouds, and two different strategies are explored to reconstruct building models from the detected face faces and segmented ground plans.
Segmentation of point clouds using smoothness constraints
TL;DR: A method for segmentation of point clouds using smoothness constraint, which finds smoothly connected areas in point clouds by using only local surface normals and point connectivity which can be enforced using either k-nearest or fixed distance neighbours is presented.