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Update files with new package name (Poisson_surface_reconstruction_3)

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Simon Giraudot 2015-09-04 17:58:07 +02:00
parent 43f7f3cdff
commit d9d94f082e
20 changed files with 190 additions and 187 deletions
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4
Documentation/Doxyfile-RewriteRules
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@ -842,7 +842,7 @@ EXAMPLE_RECURSIVE = YES
IMAGE_PATH = ../Generator/doc/Generator/fig \
../Straight_skeleton_2/doc/Straight_skeleton_2/fig \
../Polynomial/doc/Polynomial/fig \
../Surface_reconstruction_points_3/doc/Surface_reconstruction_points_3/fig \
../Poisson_surface_reconstruction_3/doc/Poisson_surface_reconstruction_3/fig \
../GraphicsView/doc/GraphicsView/fig \
../Minkowski_sum_3/doc/Minkowski_sum_3/fig \
../Triangulation_3/doc/Triangulation_3/fig \
@ -1806,7 +1806,7 @@ SKIP_FUNCTION_MACROS = YES
TAGFILES = ./tags/Generator.tag=../../CGAL.CGAL.Geometric-Object-Generators/html \
./tags/Straight_skeleton_2.tag=../../CGAL.CGAL.2D-Straight-Skeleton-and-Polygon-Offsetting/html \
./tags/Polynomial.tag=../../CGAL.CGAL.Polynomial/html \
./tags/Surface_reconstruction_points_3.tag=../../CGAL.CGAL.Surface-Reconstruction-from-Point-Sets/html \
./tags/Poisson_surface_reconstruction_3.tag=../../CGAL.CGAL.Poisson-Surface-Reconstruction/html \
./tags/GraphicsView.tag=../../CGAL.CGAL.CGAL-and-the-Qt-Graphics-View-Framework/html \
./tags/Minkowski_sum_3.tag=../../CGAL.CGAL.3D-Minkowski-Sum-of-Polyhedra/html \
./tags/Triangulation_3.tag=../../CGAL.CGAL.3D-Triangulations/html \

2
Documentation/doc/Documentation/Doxyfile.in
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@ -120,7 +120,7 @@ IMAGE_PATH = ${CMAKE_SOURCE_DIR}/Documentation/doc/Documentation/fig \
${CMAKE_SOURCE_DIR}/Subdivision_method_3/doc/Subdivision_method_3/fig \
${CMAKE_SOURCE_DIR}/Surface_mesh_parameterization/doc/Surface_mesh_parameterization/fig \
${CMAKE_SOURCE_DIR}/Surface_mesh/doc/Surface_mesh/fig \
${CMAKE_SOURCE_DIR}/Surface_reconstruction_points_3/doc/Surface_reconstruction_points_3/fig \
${CMAKE_SOURCE_DIR}/Poisson_surface_reconstruction_3/doc/Poisson_surface_reconstruction_3/fig \
${CMAKE_SOURCE_DIR}/Stream_lines_2/doc/Stream_lines_2/fig \
${CMAKE_SOURCE_DIR}/Stream_support/doc/Stream_support/fig \
${CMAKE_SOURCE_DIR}/Surface_modeling/doc/Surface_modeling/fig \

2
Documentation/doc/Documentation/Installation.txt
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@ -501,7 +501,7 @@ to speed up operations of the Polynomial package, such as GCDs. It is recommende
\sc{Eigen} is a `C++` template library for linear algebra. \sc{Eigen} supports all
matrix sizes, various matrix decomposition methods and sparse linear solvers.
In \cgal, \sc{Eigen} provides sparse linear solvers in the \ref PkgSurfaceReconstructionFromPointSets
In \cgal, \sc{Eigen} provides sparse linear solvers in the \ref PkgPoissonSurfaceReconstruction
and the \ref PkgSurfaceParameterization packages.
In addition, \sc{Eigen} also provides singular value decomposition for the \ref PkgJet_fitting_3

2
Documentation/doc/Documentation/dependencies
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@ -83,7 +83,7 @@ Voronoi_diagram_2
Surface_mesh_simplification
Subdivision_method_3
Surface_mesh_parameterization
Surface_reconstruction_points_3
Poisson_surface_reconstruction_3
Surface_mesh_segmentation
Stream_lines_2
Stream_support

9
Documentation/doc/Documentation/packages.txt
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@ -93,12 +93,15 @@ h1 {
\package_listing{Mesh_2}
\package_listing{Surface_mesher}
\package_listing{Surface_reconstruction_points_3}
\package_listing{Scale_space_reconstruction_3}
\package_listing{Advancing_front_surface_reconstruction}
\package_listing{Skin_surface_3}
\package_listing{Mesh_3}
\section PartReconstruction Surface Reconstruction
\package_listing{Poisson_surface_reconstruction_3}
\package_listing{Scale_space_reconstruction_3}
\package_listing{Advancing_front_surface_reconstruction}
\section PartGeometryProcessing Geometry Processing
\package_listing{Polygon_mesh_processing}

2
Documentation/rewrite_rules.txt
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@ -1965,7 +1965,7 @@
- \ref CGAL::Surface_mesh_simplification::LindstromTurk_cost `cgal_manual/Surface_mesh_simplification_ref/FunctionObjectClass_Surface_mesh_simplification--LindstromTurk_cost.html`
- \ref CGAL::Surface_mesh_simplification::LindstromTurk_placement `cgal_manual/Surface_mesh_simplification_ref/FunctionObjectClass_Surface_mesh_simplification--LindstromTurk_placement.html`
- \ref CGAL::Surface_mesh_simplification::Midpoint_placement `cgal_manual/Surface_mesh_simplification_ref/FunctionObjectClass_Surface_mesh_simplification--Midpoint_placement.html`
- \ref CGAL::Poisson_reconstruction_function `cgal_manual/Surface_reconstruction_points_3_ref/Class_Poisson_reconstruction_function.html`
- \ref CGAL::Poisson_reconstruction_function `cgal_manual/Poisson_surface_reconstruction_3_ref/Class_Poisson_reconstruction_function.html`
- \ref CGAL::compute_intersection_points() `cgal_manual/Sweep_line_2_ref/Function_compute_intersection_points.html`
- \ref CGAL::compute_subcurves() `cgal_manual/Sweep_line_2_ref/Function_compute_subcurves.html`
- \ref CGAL::do_curves_intersect() `cgal_manual/Sweep_line_2_ref/Function_do_curves_intersect.html`

2
Point_set_processing_3/doc/Point_set_processing_3/Point_set_processing_3.txt
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@ -30,7 +30,7 @@ points or points with normals (alignment is not covered in \cgal);
-# Smoothing to reduce noise in the input data;
-# Normal estimation and orientation when the normals are not already provided
by the acquisition device; and
-# Surface reconstruction. Chapter \ref Chapter_Surface_Reconstruction_from_Point_Sets "Surface Reconstruction from Point Sets"
-# Surface reconstruction. Chapter \ref Chapter_Poisson_Surface_Reconstruction "Poisson Surface Reconstruction"
deals with surface reconstruction from point sets with normal attributes.
\cgalFigureBegin{Point_set_processing_3figpipeline,pipeline.jpg}

2
Point_set_processing_3/doc/Point_set_processing_3/dependencies
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@ -4,7 +4,7 @@ STL_Extension
Algebraic_foundations
Circulator
Stream_support
Surface_reconstruction_points_3
Poisson_surface_reconstruction_3
Property_map
Bounding_volumes
Principal_component_analysis

2
Point_set_processing_3/doc/Property_map/Property_map.txt
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@ -26,7 +26,7 @@ Property maps in the Boost manuals: <A HREF="http://www.boost.org/libs/property_
Some algorithms in \cgal take as input parameters iterator ranges and property maps to access information attached to elements of the sequence.
For example, the algorithms of chapters \ref Chapter_Point_Set_Processing "Point Set Processing" and
\ref Chapter_Surface_Reconstruction_from_Point_Sets "Surface Reconstruction from Point Sets"
\ref Chapter_Poisson_Surface_Reconstruction "Poisson Surface Reconstruction"
take as input parameters iterator ranges and property
maps to access each point's position and normal. Position and normal
might be represented in various ways, e.g., as a class derived from

2
Point_set_processing_3/doc/Property_map/dependencies
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@ -5,4 +5,4 @@ Algebraic_foundations
Circulator
Stream_support
Point_set_processing_3
Surface_reconstruction_points_3
Poisson_surface_reconstruction_3

6
Poisson_surface_reconstruction_3/doc/Poisson_surface_reconstruction_3/Doxyfile.in
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@ -1,9 +1,9 @@
@INCLUDE = ${CGAL_DOC_PACKAGE_DEFAULTS}
PROJECT_NAME = "CGAL ${CGAL_CREATED_VERSION_NUM} - Surface Reconstruction from Point Sets"
PROJECT_NAME = "CGAL ${CGAL_CREATED_VERSION_NUM} - Poisson Surface Reconstruction"
INPUT = ${CMAKE_SOURCE_DIR}/Surface_reconstruction_points_3/doc/Surface_reconstruction_points_3/ \
${CMAKE_SOURCE_DIR}/Surface_reconstruction_points_3/include
INPUT = ${CMAKE_SOURCE_DIR}/Poisson_surface_reconstruction_3/doc/Poisson_surface_reconstruction_3/ \
${CMAKE_SOURCE_DIR}/Poisson_surface_reconstruction_3/include
EXTRACT_ALL = false
HIDE_UNDOC_CLASSES = true
WARN_IF_UNDOCUMENTED = false

8
Poisson_surface_reconstruction_3/doc/Poisson_surface_reconstruction_3/PackageDescription.txt
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@ -1,12 +1,12 @@
/// \defgroup PkgSurfaceReconstructionFromPointSets Surface Reconstruction from Point Sets Reference
/// \defgroup PkgPoissonSurfaceReconstruction Poisson Surface Reconstruction Reference
/*!
\addtogroup PkgSurfaceReconstructionFromPointSets
\cgalPkgDescriptionBegin{Surface Reconstruction from Point Sets,PkgSurfaceReconstructionFromPointSetsSummary}
\addtogroup PkgPoissonSurfaceReconstruction
\cgalPkgDescriptionBegin{Poisson Surface Reconstruction,PkgPoissonSurfaceReconstructionSummary}
\cgalPkgPicture{surface_reconstruction_points_detail.png}
\cgalPkgSummaryBegin
\cgalPkgAuthors{Pierre Alliez, Laurent Saboret, Gaël Guennebaud}
\cgalPkgDesc{This package implements a surface reconstruction method: Poisson Surface Reconstruction. It takes as input a set of points with oriented normals and computes an implicit function. The \cgal surface mesh generator can then be used to extract an iso-surface from this function. }
\cgalPkgManuals{Chapter_Surface_Reconstruction_from_Point_Sets,PkgSurfaceReconstructionFromPointSets}
\cgalPkgManuals{Chapter_Poisson_Surface_Reconstruction,PkgPoissonSurfaceReconstruction}
\cgalPkgSummaryEnd
\cgalPkgShortInfoBegin
\cgalPkgSince{3.5}

88
Poisson_surface_reconstruction_3/doc/Poisson_surface_reconstruction_3/Poisson_surface_reconstruction_3.txt
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@ -2,12 +2,12 @@ namespace CGAL {
/*!
\mainpage User Manual
\anchor Chapter_Surface_Reconstruction_from_Point_Sets
\anchor Chapter_Poisson_Surface_Reconstruction
\cgalAutoToc
\authors Pierre Alliez, Laurent Saboret, Ga&euml;l Guennebaud
\section Surface_reconstruction_points_3Introduction Introduction
\section Poisson_surface_reconstruction_3Introduction Introduction
This \cgal component implements a surface reconstruction method which
takes as input point sets with oriented normals and computes an
@ -17,7 +17,7 @@ an isosurface of this function with the \cgal Surface Mesh Generator
\cgalCite{cgal:ry-gsddrm-06} or potentially with any other surface
contouring algorithm.
\cgalFigureBegin{Surface_reconstruction_points_3figintroduction,introduction.jpg}
\cgalFigureBegin{Poisson_surface_reconstruction_3figintroduction,introduction.jpg}
Poisson surface reconstruction.\n
Left: 17K points sampled on the statue of an elephant with a Minolta laser scanner. Right: reconstructed surface mesh.
\cgalFigureEnd
@ -28,7 +28,7 @@ function of the inferred solid (Poisson Surface Reconstruction -
referred to as Poisson). Poisson is a two steps process: it requires
solving for the implicit function before function evaluation.
\section Surface_reconstruction_points_3Common Common Reconstruction Pipeline
\section Poisson_surface_reconstruction_3Common Common Reconstruction Pipeline
Surface reconstruction from point sets is often a sequential process
with the following steps: 1) Scanning and scan alignment produce a set
@ -45,11 +45,11 @@ describes algorithms to pre-process the point set before
reconstruction with functions devoted to the simplification, outlier
removal, smoothing, normal estimation and normal orientation.
\cgalFigureBegin{Surface_reconstruction_points_3figpipeline,pipeline.jpg}
\cgalFigureBegin{Poisson_surface_reconstruction_3figpipeline,pipeline.jpg}
Common surface reconstruction pipeline.
\cgalFigureEnd
\section Surface_reconstruction_points_3Poisson Poisson
\section Poisson_surface_reconstruction_3Poisson Poisson
Given a set of 3D points with oriented normals (denoted oriented
points in the sequel) sampled on the boundary of a 3D solid, the
@ -74,20 +74,20 @@ the triangulation using a sparse linear solver. Eventually, the \cgal
surface mesh generator extracts an isosurface with function value set
by default to be the median value of \f$ f\f$ at all input points.
\subsection Surface_reconstruction_points_3Interface Interface
\subsection Poisson_surface_reconstruction_3Interface Interface
The class template declaration is `template<class Gt> class Poisson_reconstruction_function` wher
`Gt` is a geometric traits class.
For details see: `Poisson_reconstruction_function<GeomTraits>`
\subsection Surface_reconstruction_points_3Example Example
\subsection Poisson_surface_reconstruction_3Example Example
The following example reads a point set, creates a Poisson implicit function and reconstructs a surface.
\cgalExample{Surface_reconstruction_points_3/poisson_reconstruction_example.cpp}
\cgalExample{Poisson_surface_reconstruction_3/poisson_reconstruction_example.cpp}
\section Surface_reconstruction_points_3Contouring Contouring
\section Poisson_surface_reconstruction_3Contouring Contouring
The computed implicit functions can be iso-contoured to reconstruct a
@ -101,7 +101,7 @@ The parameter `Tag` affects the behavior of `make_surface_mesh()`:
- `Manifold_with_boundary_tag`: the output mesh is guaranteed to be manifold and may have boundaries.
- `Non_manifold_tag`: the output mesh has no guarantee and hence is outputted as a polygon soup.
\section Surface_reconstruction_points_3Output Output
\section Poisson_surface_reconstruction_3Output Output
The surface reconstructed by `make_surface_mesh()` is required to be a
model of the concept `SurfaceMeshComplex_2InTriangulation_3`, a data
@ -116,7 +116,7 @@ and to convert it to a polyhedron (when it is manifold):
- `output_surface_facets_to_off()`
- `output_surface_facets_to_polyhedron()`
See \ref Surface_reconstruction_points_3/poisson_reconstruction_example.cpp "poisson_reconstruction_example.cpp" example above.
See \ref Poisson_surface_reconstruction_3/poisson_reconstruction_example.cpp "poisson_reconstruction_example.cpp" example above.
\section surface_reconstruction_section_case_studies Case Studies
@ -127,7 +127,7 @@ user with some hints about the ideal sampling and contouring
conditions, and depicts some failure cases when these conditions are
not matched.
\subsection Surface_reconstruction_points_3IdealConditions Ideal Conditions
\subsection Poisson_surface_reconstruction_3IdealConditions Ideal Conditions
The user must keep in mind that the Poisson surface reconstruction
algorithm comprises two phases (computing the implicit function from
@ -135,21 +135,21 @@ the input point set and contouring an iso-surface of this
function). Both require some care in terms of sampling conditions and
parameter tuning.
\subsection Surface_reconstruction_points_3PointSet Point Set
\subsection Poisson_surface_reconstruction_3PointSet Point Set
Ideally the current implementation of the Poisson surface
reconstruction method expects a dense 3D oriented point set (typically
matching the epsilon-sampling condition \cgalCite{cgal:bo-pgsms-05}) and
sampled over a closed, smooth surface. Oriented herein means that all
3D points must come with consistently oriented normals to the inferred
surface. \cgalFigureRef{Surface_reconstruction_points_3figbimba} and \cgalFigureRef{Surface_reconstruction_points_3figeros}
surface. \cgalFigureRef{Poisson_surface_reconstruction_3figbimba} and \cgalFigureRef{Poisson_surface_reconstruction_3figeros}
illustrate cases where these ideal conditions are met.
\cgalFigureBegin{Surface_reconstruction_points_3figbimba,bimba.jpg}
\cgalFigureBegin{Poisson_surface_reconstruction_3figbimba,bimba.jpg}
Poisson reconstruction. Left: 120K points sampled on a statue (Minolta laser scanner). Right: reconstructed surface mesh.
\cgalFigureEnd
\cgalFigureBegin{Surface_reconstruction_points_3figeros,eros.jpg}
\cgalFigureBegin{Poisson_surface_reconstruction_3figeros,eros.jpg}
Left: 120K points sampled on a statue (Minolta laser scanner). Right: reconstructed surface mesh.
\cgalFigureEnd
@ -157,17 +157,17 @@ The algorithm is fairly robust to anisotropic sampling and to
noise. It is also robust to missing data through filling the
corresponding holes as the algorithm is designed to reconstruct the
indicator function of an inferred solid (see
\cgalFigureRef{Surface_reconstruction_points_3figholes_good}).
\cgalFigureRef{Poisson_surface_reconstruction_3figholes_good}).
\cgalFigureBegin{Surface_reconstruction_points_3figholes_good,holes_good.jpg}
\cgalFigureBegin{Poisson_surface_reconstruction_3figholes_good,holes_good.jpg}
Top left: 65K points sampled on a hand (Kreon laser scanner). Bottom left: the point set is highly anisotropic due to the scanning technology. Right: reconstructed surface mesh and closeup. The holes are properly closed.
\cgalFigureEnd
The algorithm is in general not robust to outliers, although a few
outliers do not always create a failure, see
\cgalFigureRef{Surface_reconstruction_points_3figoutliers}.
\cgalFigureRef{Poisson_surface_reconstruction_3figoutliers}.
\cgalFigureBegin{Surface_reconstruction_points_3figoutliers,outliers.jpg}
\cgalFigureBegin{Poisson_surface_reconstruction_3figoutliers,outliers.jpg}
Left: 70K points sampled on an elephant with few outliers emphasized with disks. Right: reconstructed surface mesh.
\cgalFigureEnd
@ -181,7 +181,7 @@ connected components care should be taken to orient the normals of
each component in alternation (inward/outward) so that the final
contouring stage picks a proper contouring value.
\subsection Surface_reconstruction_points_3ContouringP Contouring Parameters
\subsection Poisson_surface_reconstruction_3ContouringP Contouring Parameters
Our implementation of the Poisson surface reconstruction algorithm
computes an implicit function represented as a piecewise linear
@ -193,7 +193,7 @@ and hence may contain sharp creases. As the contouring algorithm
sharp creases may create spurious clusters of vertices in the final
reconstructed surface mesh when setting a small mesh sizing or surface
approximation error parameter (see
\cgalFigureRef{Surface_reconstruction_points_3figcontouring_bad}).
\cgalFigureRef{Poisson_surface_reconstruction_3figcontouring_bad}).
One way to avoid these spurious clusters consists of adjusting the
mesh sizing and surface approximation parameters large enough compared
@ -205,18 +205,18 @@ contouring parameters:
- Max triangle radius: at least 100 times the average spacing.
- Approximation distance: at least 0.25 times the average spacing.
\cgalFigureBegin{Surface_reconstruction_points_3figcontouring_bad,contouring_bad.jpg}
\cgalFigureBegin{Poisson_surface_reconstruction_3figcontouring_bad,contouring_bad.jpg}
Left: surface reconstructed with approximation distance = 0.25 * average spacing. Right: surface reconstructed with approximation distance = 0.15 * average spacing. Notice the spurious cluster on the chick.
\cgalFigureEnd
\subsection Surface_reconstruction_points_3DegradedConditions Degraded Conditions
\subsection Poisson_surface_reconstruction_3DegradedConditions Degraded Conditions
The conditions listed above are rather restrictive and in practice not
all of them are met in the applications. We now illustrates the
behavior of the algorithm when the conditions are not met in terms of
sampling, wrongly oriented normals, noise and sharp creases.
\subsection Surface_reconstruction_points_3SparseSampling Sparse Sampling
\subsection Poisson_surface_reconstruction_3SparseSampling Sparse Sampling
The reconstruction algorithm expects a sufficiently dense point
set. Although there is no formal proof of correctness of the algorithm
@ -227,22 +227,22 @@ feature size (the distance to the medial axis, which captures
altogether curvature, thickness and separation). When this condition
is not met the reconstruction does not reconstruct the thin
undersampled features (see
\cgalFigureRef{Surface_reconstruction_points_3figsampling}).
\cgalFigureRef{Poisson_surface_reconstruction_3figsampling}).
\cgalFigureBegin{Surface_reconstruction_points_3figsampling,sampling.jpg}
\cgalFigureBegin{Poisson_surface_reconstruction_3figsampling,sampling.jpg}
Left: 50K points sampled on the Neptune trident. The reconstruction (not shown) is successful in this case. Right: point set simplified to 1K points then reconstructed (all input points are depicted with normals). The thin feature is not reconstructed.
\cgalFigureEnd
\subsection Surface_reconstruction_points_3LargeHoles Large Holes
\subsection Poisson_surface_reconstruction_3LargeHoles Large Holes
The reconstruction is devised to solve for an implicit function which
is an approximate indicator function of an inferred solid. For this
reason the contouring algorithm always extracts a closed surface mesh
and hence is able to fill the small holes where data are missing due,
e.g., to occlusions during acquisition (see
\cgalFigureRef{Surface_reconstruction_points_3figholes_bad}).
\cgalFigureRef{Poisson_surface_reconstruction_3figholes_bad}).
\cgalFigureBegin{Surface_reconstruction_points_3figholes_bad,holes_bad.jpg}
\cgalFigureBegin{Poisson_surface_reconstruction_3figholes_bad,holes_bad.jpg}
Left: 65K points sampled on a hand with no data captured at the wrist base. Right: reconstructed surface mesh. The surface is properly closed on the fingers and also closed at the wrist but in a less plausible manner.
\cgalFigureEnd
@ -255,11 +255,11 @@ This can be avoided by a two pass approach. The first pass for a subset of the p
serves to get an approximation of the surface at the holes. This surface then serves to
compute a smoother 3D Delaunay triangulation for the second pass with the full set of points.
\cgalFigureBegin{Surface_reconstruction_points_3-fig-two_passes,two-passes.png}
\cgalFigureBegin{Poisson_surface_reconstruction_3-fig-two_passes,two-passes.png}
Left: The wrist. Middle: one pass. Right: two passes.
\cgalFigureEnd
\subsection Surface_reconstruction_points_3WronglyOriented Wrongly Oriented Normals
\subsection Poisson_surface_reconstruction_3WronglyOriented Wrongly Oriented Normals
The Poisson surface reconstruction approaches solves for an implicit
function whose gradient best matches a set of input normals. Because
@ -267,16 +267,16 @@ it solves this problem in the least squares sense, it is robust to few
isolated wrongly oriented (flipped) normals. Nevertheless a cluster of
wrongly oriented normals leads to an incorrect implicit function and
hence to spurious geometric or even topological distortion (see
\cgalFigureRef{Surface_reconstruction_points_3figflipped_normals}).
\cgalFigureRef{Poisson_surface_reconstruction_3figflipped_normals}).
\cgalFigureBegin{Surface_reconstruction_points_3figflipped_normals,flipped_normals.jpg}
\cgalFigureBegin{Poisson_surface_reconstruction_3figflipped_normals,flipped_normals.jpg}
Left: points sampled on a sphere with a cluster of wrongly oriented normals. Right: reconstructed surface mesh with a spurious bump.
\cgalFigureEnd
\subsection Surface_reconstruction_points_3NoiseandOutliers Noise and Outliers
\subsection Poisson_surface_reconstruction_3NoiseandOutliers Noise and Outliers
A large amount of noise inevitably impacts on the reconstruction (see
\cgalFigureRef{Surface_reconstruction_points_3fignoise}, top) and the
\cgalFigureRef{Poisson_surface_reconstruction_3fignoise}, top) and the
current implementation does not provide any mean to trade data fitting
for smoothness. Nevertheless if the signal-to-noise ratio is
sufficiently high and/or the surface approximation and sizing
@ -285,9 +285,9 @@ the noise level the output surface mesh will appear smooth (not
shown). If the user wants to produce a smooth and detailed output
surface mesh, we recommend to apply smoothing through
`jet_smooth_point_set()` (see
\cgalFigureRef{Surface_reconstruction_points_3fignoise}, bottom).
\cgalFigureRef{Poisson_surface_reconstruction_3fignoise}, bottom).
\cgalFigureBegin{Surface_reconstruction_points_3fignoise,noise.jpg}
\cgalFigureBegin{Poisson_surface_reconstruction_3fignoise,noise.jpg}
Top-left: points sampled on a sphere and corrupted with a lot of noise. Top-right: reconstructed surface mesh. Bottom-left: smoothed point set. Bottom-right: reconstructed surface mesh.
\cgalFigureEnd
@ -296,13 +296,13 @@ into spurious small connected components and massive distortion near
the inferred surface. In this case the outliers must be removed
through `remove_outliers()`.
\subsection Surface_reconstruction_points_3SharpCreases Sharp Creases
\subsection Poisson_surface_reconstruction_3SharpCreases Sharp Creases
The current reconstruction algorithm is not able to recover the sharp
creases and corners present in the inferred surface. This translates
into smoothed sharp creases.
\cgalFigureBegin{Surface_reconstruction_points_3figsharp_features,sharp_features.jpg}
\cgalFigureBegin{Poisson_surface_reconstruction_3figsharp_features,sharp_features.jpg}
Left: 5K points sampled on a mechanical piece with sharp features (creases, darts and corners). Right: reconstructed surface mesh with smoothed creases.
\cgalFigureEnd
@ -318,7 +318,7 @@ with the 03 option which maximizes speed. All measurements were done using the
\subsection SurfReconstPerfPIF Poisson Implicit Function
The point set chosen for benchmarking the Poisson implicit function is the Bimba con Nastrino point set
(1.6 million points) depicted by \cgalFigureRef{Surface_reconstruction_points_3-fig-contouring_bench}.
(1.6 million points) depicted by \cgalFigureRef{Poisson_surface_reconstruction_3-fig-contouring_bench}.
We measure the Poisson implicit function computation (i.e., the call to
`Poisson_reconstruction_function::compute_implicit_function()` denoted by Poisson solve hereafter)
for this point set as well as for simplified versions obtained through random simplification.
@ -427,7 +427,7 @@ Reconstruction error (mm)
</TABLE>
\cgalFigureBegin{Surface_reconstruction_points_3-fig-contouring_bench,contouring_bench.jpg}
\cgalFigureBegin{Poisson_surface_reconstruction_3-fig-contouring_bench,contouring_bench.jpg}
Contouring duration (in s) and reconstruction error (mm)
against several approximation distance parameters
for the Bimba con Nastrino point set simplified to 100k points.
@ -538,7 +538,7 @@ Reconstruction error (mm)
</TABLE>
\cgalFigureBegin{Surface_reconstruction_points_3-fig-simplification_bench,simplification_bench.jpg}
\cgalFigureBegin{Poisson_surface_reconstruction_3-fig-simplification_bench,simplification_bench.jpg}
Reconstruction error (mm) against number of points
for the Bimba con Nastrino point set with 1.6M points
as well as for simplified versions.

2
Poisson_surface_reconstruction_3/doc/Poisson_surface_reconstruction_3/examples.txt
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@ -1 +1 @@
/// \example Surface_reconstruction_points_3/poisson_reconstruction_example.cpp
/// \example Poisson_surface_reconstruction_3/poisson_reconstruction_example.cpp

2
Poisson_surface_reconstruction_3/examples/Poisson_surface_reconstruction_3/CMakeLists.txt
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@ -1,6 +1,6 @@
# This is the CMake script for compiling this folder.
project( Surface_reconstruction_points_3_example )
project( Poisson_surface_reconstruction_3_example )
cmake_minimum_required(VERSION 2.8.11)

2
Poisson_surface_reconstruction_3/include/CGAL/Poisson_reconstruction_function.h
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@ -144,7 +144,7 @@ struct Special_wrapper_of_two_functions_keep_pointers {
/*!
\ingroup PkgSurfaceReconstructionFromPointSets
\ingroup PkgPoissonSurfaceReconstruction
\brief Implementation of the Poisson Surface Reconstruction method.

2
Poisson_surface_reconstruction_3/include/CGAL/surface_reconstruction_points_assertions.h
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@ -23,7 +23,7 @@
/// \cond SKIP_IN_MANUAL
/// @file surface_reconstruction_points_assertions.h
/// Define checking macros for the Surface_reconstruction_points_3 package
/// Define checking macros for the Poisson_surface_reconstruction_3 package
// Note that this header file is intentionnaly not protected with a
// macro (as <cassert>). Calling it a second time with another value

2
Poisson_surface_reconstruction_3/test/Poisson_surface_reconstruction_3/CMakeLists.txt
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@ -1,6 +1,6 @@
# This is the CMake script for compiling this folder.
project( Surface_reconstruction_points_3_test )
project( Poisson_surface_reconstruction_3_test )
cmake_minimum_required(VERSION 2.8.11)

2
Polyhedron/demo/Polyhedron/include/UI_point_3.h
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@ -10,7 +10,7 @@
#include <algorithm>
/// The UI_point_3 class represents a 3D point in Surface_reconstruction_points_3 demo.
/// The UI_point_3 class represents a 3D point in Poisson_surface_reconstruction_3 demo.
/// It contains:
/// - a position,
/// - a normal,

234
copyright
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@ -8,120 +8,120 @@ U = Utrecht University
R = RU Groningen
AABB_tree I
Algebraic_foundations ETIMU
Algebraic_kernel_d IM
Algebraic_kernel_for_circles I
Algebraic_kernel_for_spheres I
Alpha_shapes_2 I
Alpha_shapes_3 I
Apollonius_graph_2 I
Approximate_min_ellipsoid_d E
Arithmetic_kernel M
Arrangement_on_surface_2 T
BGL G
Boolean_set_operations_2 T
Box_intersection_d M
CGAL_Core NYU; Chee Yap agreed to upgrade
CGAL_ImageIO third party lib under LGPL
CGAL_ipelets I
Cartesian_kernel ETIMU
Circular_kernel_2 I
Circular_kernel_3 I
Circulator ETIMU
Combinatorial_map Cnrs; Guillaume Damiand upgraded
Conic_2 ETIMU
Convex_decomposition_3 M
Convex_hull_2 M
Convex_hull_3 M
Convex_hull_d M
Developers_manual ETIMU
Distance_2 ETIMU
Distance_3 ETIMU
Envelope_2 T
Envelope_3 T
Filtered_kernel I
Generator ETIMU
Geomview ETIMU
GraphicsView G
HalfedgeDS ETIMU
Hash_map M
Homogeneous_kernel ETIMU
Installation ETIMU
Interpolation I
Intersections_2 ETIMU
Intersections_3 ETIMU
Interval_skip_list G
Interval_support M
Inventor ETIMU
Jet_fitting_3 I
Kernel_23 ETIMU
Kernel_d ETIMU
Kinetic_data_structures Stanford; Leo Guibas agreed to upgrade
LEDA ETIMU
Largest_empty_rect_2 T
MacOSX F
Maintenance ETIMUG
Manual ETIMU
Manual_tools EIM, Modena Software, Silicon Graphics
Matrix_search E
Mesh_2 I
Mesh_3 I
Min_annulus_d E
Min_circle_2 E
Min_ellipse_2 E
Min_quadrilateral_2 E
Min_sphere_d E
Min_sphere_of_spheres_d E
Minkowski_sum_2 T
Minkowski_sum_3 M
Modifier ETIMU
Modular_arithmetic MI
Nef_2 M
Nef_3 M
Nef_S2 M
Number_types ETIMU
OpenNL third party lib under LGPL 3
Optimisation_basic E
Optimisation_doc E
Partition_2 M
Periodic_3_triangulation_3 I
Point_set_2 Halle transfered copyright to Inria
Point_set_processing_3 I
Polygon ETIMU
Polyhedron E
Polyhedron_IO E
Polynomial M
Polytope_distance_d E
Principal_component_analysis I
Profiling_tools ETIMU
QP_solver E
Qt_widget I
Random_numbers ETIMU
Ridges_3 I
Robustness M
STL_Extension ETIMU
Scripts ETIMU
SearchStructures E
Segment_Delaunay_graph_2 I Menelaos removed Notre Dame U
Skin_surface_3 R Gert Vegter agreed to upgrade
Snap_rounding_2 T
Spatial_searching U
Spatial_sorting I
Straight_skeleton_2 Cacciola; Fernando agreed to upgrade to GPL
Stream_lines_2 I
Stream_support ETIMU
Subdivision_method_3 G
Surface_mesh_parameterization I
Surface_mesh_simplification G
Surface_mesher I
Surface_reconstruction_points_3I
Testsuite IG
Triangulation_2 I
Triangulation_3 I
Union_find M
Voronoi_diagram_2 F I sent mail to Forth
Width_3 E
iostream ETIMU
kdtree T
wininst ETIMU
AABB_tree I
Algebraic_foundations ETIMU
Algebraic_kernel_d IM
Algebraic_kernel_for_circles I
Algebraic_kernel_for_spheres I
Alpha_shapes_2 I
Alpha_shapes_3 I
Apollonius_graph_2 I
Approximate_min_ellipsoid_d E
Arithmetic_kernel M
Arrangement_on_surface_2 T
BGL G
Boolean_set_operations_2 T
Box_intersection_d M
CGAL_Core NYU; Chee Yap agreed to upgrade
CGAL_ImageIO third party lib under LGPL
CGAL_ipelets I
Cartesian_kernel ETIMU
Circular_kernel_2 I
Circular_kernel_3 I
Circulator ETIMU
Combinatorial_map Cnrs; Guillaume Damiand upgraded
Conic_2 ETIMU
Convex_decomposition_3 M
Convex_hull_2 M
Convex_hull_3 M
Convex_hull_d M
Developers_manual ETIMU
Distance_2 ETIMU
Distance_3 ETIMU
Envelope_2 T
Envelope_3 T
Filtered_kernel I
Generator ETIMU
Geomview ETIMU
GraphicsView G
HalfedgeDS ETIMU
Hash_map M
Homogeneous_kernel ETIMU
Installation ETIMU
Interpolation I
Intersections_2 ETIMU
Intersections_3 ETIMU
Interval_skip_list G
Interval_support M
Inventor ETIMU
Jet_fitting_3 I
Kernel_23 ETIMU
Kernel_d ETIMU
Kinetic_data_structures Stanford; Leo Guibas agreed to upgrade
LEDA ETIMU
Largest_empty_rect_2 T
MacOSX F
Maintenance ETIMUG
Manual ETIMU
Manual_tools EIM, Modena Software, Silicon Graphics
Matrix_search E
Mesh_2 I
Mesh_3 I
Min_annulus_d E
Min_circle_2 E
Min_ellipse_2 E
Min_quadrilateral_2 E
Min_sphere_d E
Min_sphere_of_spheres_d E
Minkowski_sum_2 T
Minkowski_sum_3 M
Modifier ETIMU
Modular_arithmetic MI
Nef_2 M
Nef_3 M
Nef_S2 M
Number_types ETIMU
OpenNL third party lib under LGPL 3
Optimisation_basic E
Optimisation_doc E
Partition_2 M
Periodic_3_triangulation_3 I
Point_set_2 Halle transfered copyright to Inria
Point_set_processing_3 I
Polygon ETIMU
Polyhedron E
Polyhedron_IO E
Polynomial M
Polytope_distance_d E
Principal_component_analysis I
Profiling_tools ETIMU
QP_solver E
Qt_widget I
Random_numbers ETIMU
Ridges_3 I
Robustness M
STL_Extension ETIMU
Scripts ETIMU
SearchStructures E
Segment_Delaunay_graph_2 I Menelaos removed Notre Dame U
Skin_surface_3 R Gert Vegter agreed to upgrade
Snap_rounding_2 T
Spatial_searching U
Spatial_sorting I
Straight_skeleton_2 Cacciola; Fernando agreed to upgrade to GPL
Stream_lines_2 I
Stream_support ETIMU
Subdivision_method_3 G
Surface_mesh_parameterization I
Surface_mesh_simplification G
Surface_mesher I
Poisson_surface_reconstruction_3I
Testsuite IG
Triangulation_2 I
Triangulation_3 I
Union_find M
Voronoi_diagram_2 F I sent mail to Forth
Width_3 E
iostream ETIMU
kdtree T
wininst ETIMU