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@ -194,7 +194,7 @@ projecting each point onto a smooth parametric surface patch
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Function `bilateral_smooth_point_set()` smooths the input point set by
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Function `bilateral_smooth_point_set()` smooths the input point set by
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iteratively projecting each point onto the implicit surface patch fitted over its `k` nearest neighbors.
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iteratively projecting each point onto the implicit surface patch fitted over its `k` nearest neighbors.
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Bilateral projection preserves sharp features according to the normal (gradient) information.
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Bilateral projection preserves sharp features according to the normal (gradient) information.
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Normals are thus required as input. See section 4 in \cgalCite{ear-2013}.
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Normals are thus required as input. For more details, see section 4 of \cgalCite{ear-2013}.
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\subsection Point_set_processing_3Example_5 Jet smoothing example
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\subsection Point_set_processing_3Example_5 Jet smoothing example
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@ -268,7 +268,7 @@ normals:
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\section Point_set_processing_3Upsampling Upsampling
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\section Point_set_processing_3Upsampling Upsampling
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The function `edge_aware_upsample_point_set()` generates a denser point set from an input point set. This has applications in point-based rendering, hole filling, and sparse surface reconstruction.
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The function `edge_aware_upsample_point_set()` generates a denser point set from an input point set. This has applications in point-based rendering, hole filling, and sparse surface reconstruction.
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The algorithm can progressively upsample the point set while approaching the edge singularities, see \cgalCite{ear-2013} for more detail.
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The algorithm can progressively upsample the point set while approaching the edge singularities. See \cgalCite{ear-2013} for more details.
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\subsection Point_set_processing_3Example_8 Example
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\subsection Point_set_processing_3Example_8 Example
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