\( \newcommand{\E}{\mathrm{E}} \) \( \newcommand{\A}{\mathrm{A}} \) \( \newcommand{\R}{\mathrm{R}} \) \( \newcommand{\N}{\mathrm{N}} \) \( \newcommand{\Q}{\mathrm{Q}} \) \( \newcommand{\Z}{\mathrm{Z}} \) \( \def\ccSum #1#2#3{ \sum_{#1}^{#2}{#3} } \def\ccProd #1#2#3{ \sum_{#1}^{#2}{#3} }\)
CGAL 5.0 - Point Set Processing
Point_set_processing_3/remove_outliers_example.cpp
#include <CGAL/Exact_predicates_inexact_constructions_kernel.h>
#include <CGAL/property_map.h>
#include <CGAL/compute_average_spacing.h>
#include <CGAL/remove_outliers.h>
#include <CGAL/IO/read_xyz_points.h>
#include <vector>
#include <fstream>
#include <iostream>
// types
typedef Kernel::Point_3 Point;
int main(int argc, char*argv[])
{
const char* fname = (argc>1)?argv[1]:"data/oni.xyz";
// Reads a .xyz point set file in points[].
// The Identity_property_map property map can be omitted here as it is the default value.
std::vector<Point> points;
std::ifstream stream(fname);
if (!stream ||
!CGAL::read_xyz_points(stream, std::back_inserter(points),
CGAL::parameters::point_map(CGAL::Identity_property_map<Point>())))
{
std::cerr << "Error: cannot read file " << fname << std::endl;
return EXIT_FAILURE;
}
// Removes outliers using erase-remove idiom.
// The Identity_property_map property map can be omitted here as it is the default value.
const int nb_neighbors = 24; // considers 24 nearest neighbor points
// Estimate scale of the point set with average spacing
const double average_spacing = CGAL::compute_average_spacing<CGAL::Sequential_tag>
(points, nb_neighbors);
// FIRST OPTION //
// I don't know the ratio of outliers present in the point set
std::vector<Point>::iterator first_to_remove
(points,
nb_neighbors,
CGAL::parameters::threshold_percent (100.). // No limit on the number of outliers to remove
threshold_distance (2. * average_spacing)); // Point with distance above 2*average_spacing are considered outliers
std::cerr << (100. * std::distance(first_to_remove, points.end()) / (double)(points.size()))
<< "% of the points are considered outliers when using a distance threshold of "
<< 2. * average_spacing << std::endl;
// SECOND OPTION //
// I know the ratio of outliers present in the point set
const double removed_percentage = 5.0; // percentage of points to remove
points.erase(CGAL::remove_outliers
(points,
nb_neighbors,
CGAL::parameters::threshold_percent(removed_percentage). // Minimum percentage to remove
threshold_distance(0.)), // No distance threshold (can be omitted)
points.end());
// Optional: after erase(), use Scott Meyer's "swap trick" to trim excess capacity
std::vector<Point>(points).swap(points);
return EXIT_SUCCESS;
}