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Clement Jamin 2014-11-04 22:51:10 +01:00
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Point_set_processing_3/doc/Point_set_processing_3/Point_set_processing_3.txt
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@ -143,10 +143,9 @@ one arbitrarily chosen point. This algorithm is slower than
Function `wlop_simplify_and_regularize_point_set()` not only simplifies,
but also regularizes downsampled points. This is an implementation of
the WLOP (Weighted Locally Optimal Projection) algorithm
<a href="http://web.siat.ac.cn/~huihuang/WLOP/WLOP_page.html">[Huang et al. 2009]</a>.
the Weighted Locally Optimal Projection (WLOP) algorithm \cgalCite{wlop-2009}.
\subsection Point_set_processing_3Example_3 Grid simplification example
The following example reads a point set and simplifies it by clustering.
@ -194,7 +193,8 @@ projecting each point onto a smooth parametric surface patch
Function `bilateral_smooth_point_set()` smooths the input point set by
iteratively projecting each point onto the implicit surface patch fitted over its `k` nearest neighbors.
Bilateral projection preserves sharp features according to the normal (gradient) information. Normals are thus required as input. See formula (2) and (4) in paper <a href="http://web.siat.ac.cn/~huihuang/EAR/EAR_page.html">[Huang et al. 2013]</a>.
Bilateral projection preserves sharp features according to the normal (gradient) information.
Normals are thus required as input. See formula (2) and (4) in \cgalCite{ear-2013}.
\subsection Point_set_processing_3Example_5 Jet smoothing example