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Add Weighted Sample Elimination #8554

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Add Weighted Sample Elimination #8554

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afabri
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@afabri afabri commented Oct 17, 2024 •
edited by lrineau
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Summary of Changes

For some other package we need a uniform sampling on a triangle mesh. There is a nice code for that in cyCodeBase.

See also the publication at http://www.cemyuksel.com/research/sampleelimination/.

To get started I only add an example that exposes the cy-API, so that we can use the console application right away.

Release Management

  • Affected package(s): PMP
  • Feature/Small Feature (if any):
  • Link to compiled documentation (obligatory for small feature) wrong link name to be changed
  • License and copyright ownership: GeometryFactory for the wrapper to come. cyCodeBase has a MIT license.

@afabri afabri added this to the 6.1-beta milestone Nov 5, 2024
@soesau
bugfixes and warnings
d23fb52
@soesau
added documentation
bc97771 
renamed weight_functor to weight_function
changed some default values of named parameters
@soesau
some doc adjustments
679146f
@soesau soesau force-pushed the PMP-PoissonDiskSampling-GF branch from 530a4ee to 679146f Compare February 12, 2025 09:37
afabri
afabri commented Feb 12, 2025
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Point_set_processing_3/include/CGAL/poisson_eliminate.h Outdated
continue;

const Point p2 = get(ipm, res[n]);
double d2 = CGAL::to_double((p - p2).squared_length());
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Do we have an approximate_something() ?? @sloriot

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CGAL::approximate_sqrt

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I was more wondering if we have an approximate_squared_distance(p,q)

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I am now using Kernel::compute_squared_distance_(2/3)_object or squared_distance_d_object depending on the Ambient_dimension of the Kernel.

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soesau commented Feb 14, 2025

/build:v0

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The documentation is built. It will be available, after a few minutes, here: https://cgal.github.io/8554/v0/Manual/index.html

sloriot
sloriot reviewed Feb 14, 2025
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Point_set_processing_3/doc/Point_set_processing_3/Point_set_processing_3.txt
The Poisson sample elimination is a greedy downsampling method that calculates a weight for each input point based on the density of its local neighborhood. Subsequently, the point with the highest weight is removed and the weights of the remaining points around it are updated until the target size is reached. A custom function to calculate the weight of a point can be provided.

The Poisson sample elimination has the following parameters:
- *dimensions*: The dimensions parameter specifies the dimension of the sampling domain of the point cloud, e.g., 2 if the point cloud is sampled from a surface, while the ambient dimension is typically 3. The default value is 2.
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Suggested change
- *dimensions*: The dimensions parameter specifies the dimension of the sampling domain of the point cloud, e.g., 2 if the point cloud is sampled from a surface, while the ambient dimension is typically 3. The default value is 2.
- *dimension*: The dimension of the sampling domain of the point cloud, e.g., 2 if the point cloud is sampled from a surface, while the ambient dimension is typically 3. The default value is 2.

Point_set_processing_3/doc/Point_set_processing_3/Point_set_processing_3.txt

The Poisson sample elimination has the following parameters:
- *dimensions*: The dimensions parameter specifies the dimension of the sampling domain of the point cloud, e.g., 2 if the point cloud is sampled from a surface, while the ambient dimension is typically 3. The default value is 2.
- *weight_function*: A custom *weight_function* can be provided to calculate the weight between two points. The type of the functor is as follows:
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- *weight_function*: A custom *weight_function* can be provided to calculate the weight between two points. The type of the functor is as follows:
- *weight_function*: A custom function can be provided to calculate the weight between two points. The type of the functor is as follows:

Point_set_processing_3/doc/Point_set_processing_3/Point_set_processing_3.txt
double(*func)(const Point &p, const Point &n, double squared_distance, double r_max)
\endcode
The default weight is \f$\left(1 - \frac{d_{p,n}}{2r_{max}}\right)^8\f$ with \f$d_{p,n}\f$ being the distance between the point p and its neighbor n.
- \f$r_{max}\f$: The \f$r_{max}\f$ parameter specifies the radius of the neighborhood, i.e., the neighboring points that are used to calculate the weight of a point. r_max has to be provided if a custom *weight_function* is used. Only points within a distance of \f$r_{max}\f$ are used to calculate the weight of a point. A large value can thus cause a large running time. The default is calculated based in the bounding volume \f$V\f$ of the input points, the *dimensions* parameter and the number of input points \f$N\f$:
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- \f$r_{max}\f$: The \f$r_{max}\f$ parameter specifies the radius of the neighborhood, i.e., the neighboring points that are used to calculate the weight of a point. r_max has to be provided if a custom *weight_function* is used. Only points within a distance of \f$r_{max}\f$ are used to calculate the weight of a point. A large value can thus cause a large running time. The default is calculated based in the bounding volume \f$V\f$ of the input points, the *dimensions* parameter and the number of input points \f$N\f$:
- \f$r_{max}\f$: The \f$r_{max}\f$ parameter specifies the radius of the neighborhood, i.e., the neighboring points that are used to calculate the weight of a point. \f$r_{max}\f$ has to be provided if a custom *weight_function* is used. Only points within a distance of \f$r_{max}\f$ are used to calculate the weight of a point. A large value can thus cause a large running time. The default is calculated based in the bounding volume \f$V\f$ of the input points, the *dimensions* parameter and the number of input points \f$N\f$:

Point_set_processing_3/include/CGAL/poisson_eliminate.h

/**
\ingroup PkgPointSetProcessing3Algorithms
Performs poisson disk elimination with a desired output size. A greedy method that calculates a weight based on the
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Performs poisson disk elimination with a desired output size. A greedy method that calculates a weight based on the
performs poisson disk elimination with a desired output size. A greedy method that calculates a weight based on the

Point_set_processing_3/include/CGAL/poisson_eliminate.h
\cgalNamedParamsEnd
*/
template<class PointRange, class OutputIterator, class NamedParameters = parameters::Default_named_parameters>
void poisson_eliminate(PointRange &points, std::size_t number_of_points, OutputIterator output, const NamedParameters& np = parameters::default_values()) {
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I wonder if eliminate is the right word since output points are copied. Also, why is PointRange not const? is it reordered?

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