Methods for Feature Detection in Point Clouds

Authors Christopher Weber, Stefanie Hahmann, Hans Hagen

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Christopher Weber
Stefanie Hahmann
Hans Hagen

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Christopher Weber, Stefanie Hahmann, and Hans Hagen. Methods for Feature Detection in Point Clouds. In Visualization of Large and Unstructured Data Sets - Applications in Geospatial Planning, Modeling and Engineering (IRTG 1131 Workshop). Open Access Series in Informatics (OASIcs), Volume 19, pp. 90-99, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2011)


This paper gives an overview over several techniques for detection of features, and in particular sharp features, on point-sampled geometry. In addition, a new technique using the Gauss map is shown. Given an unstructured point cloud, this method computes a Gauss map clustering on local neighborhoods in order to discard all points that are unlikely to belong to a sharp feature. A single parameter is used in this stage to control the sensitivity of the feature detection.
  • point cloud
  • sharp features
  • reconstruction
  • Gaussmap
  • clustering


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