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Conference Papers Year : 2011

Methods for Feature Detection in Point Clouds


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.
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hal-00921790 , version 1 (21-12-2013)



Christopher Weber, Stefanie Hahmann, Hans Hagen. Methods for Feature Detection in Point Clouds. Visualization of Large and Unstructured Data Sets - Applications in Geospatial Planning, Modeling and Engineering (IRTG 1131 Workshop), Mar 2010, Bodega Bay, CA, United States. pp.90-99, ⟨10.4230/OASIcs.VLUDS.2010.90⟩. ⟨hal-00921790⟩
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