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finished AABB in regularize_and_simplify_point_set.h

This commit is contained in:
Shihao Wu 2013-09-19 22:12:42 +08:00
parent 825d98a4f3
commit 43b70bd3e3
2 changed files with 52 additions and 110 deletions
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12
Point_set_processing_3/examples/Point_set_processing_3/wlop_simplify_and_regularize_point_set_example.cpp
View File

@ -17,8 +17,8 @@ typedef Kernel::Point_3 Point;
int main(void)
{
const std::string INPUT_FILENAME_WITHOUT_EXT = "data/sphere_20k";
//const std::string INPUT_FILENAME_WITHOUT_EXT = "data/saint_jean_370K";
//const std::string INPUT_FILENAME_WITHOUT_EXT = "data/sphere_20k";
const std::string INPUT_FILENAME_WITHOUT_EXT = "data/saint_jean_370K";
//const std::string INPUT_FILENAME_WITHOUT_EXT = "data/qtr_piston_noise";
// Reads a .xyz point set file in points[], *with normals*.
@ -33,8 +33,8 @@ int main(void)
}
//Algorithm parameters
const double retain_percentage = 10; // percentage of points to retain.
const double neighbor_radius = 0.3; // neighbors size.
const double retain_percentage = 2; // percentage of points to retain.
const double neighbor_radius = 0.03; // neighbors size.
const unsigned int iter_number = 30; // number of iterations.
const bool need_compute_density = true; // if needed to compute density.
@ -85,6 +85,10 @@ int main(void)
neighbor_radius,
iter_number,
need_compute_density);
long memory = CGAL::Memory_sizer().virtual_size();
std::cout << "total done: " << task_timer.time() << " seconds, "
<< (memory>>20) << " Mb allocated" << std::endl;
// Copy results to sample points
std::copy(sample_points_begin,

150
Point_set_processing_3/include/CGAL/regularize_and_simplify_point_set.h
View File

@ -58,43 +58,6 @@ namespace CGAL {
namespace regularize_and_simplify_internal{
// Item in the Kd-tree: position (Point_3) + index
template <typename Kernel>
class Kd_tree_element : public Kernel::Point_3
{
public:
unsigned int index;
// basic geometric types
typedef typename CGAL::Origin Origin;
typedef typename Kernel::Point_3 Base;
Kd_tree_element(const Origin& o = ORIGIN, unsigned int id=0)
: Base(o), index(id)
{}
Kd_tree_element(const Base& p, unsigned int id=0)
: Base(p), index(id)
{}
Kd_tree_element(const Kd_tree_element& other)
: Base(other), index(other.index)
{}
};
// Helper class for the Kd-tree
template <typename Kernel>
class Kd_tree_gt : public Kernel
{
public:
typedef Kd_tree_element<Kernel> Point_3;
};
template <typename Kernel>
class Kd_tree_traits : public CGAL::Search_traits_3<Kd_tree_gt<Kernel> >
{
public:
typedef typename Kernel::Point_3 PointType;
};
/// Compute average term for each sample points
/// According to their KNN neighborhood original points
///
@ -243,8 +206,7 @@ compute_repulsion_term(
for(; iter != neighbor_sample_points.end(); iter++)
{
Point& np = *(*iter);
int sample_index = std::distance(sample_first_iter,
*iter);
int sample_index = std::distance(sample_first_iter, *iter);
FT dist2 = CGAL::squared_distance(query, np);
if (!is_density_weight_set_empty)
@ -306,7 +268,7 @@ template </*typename Concurrency_tag, */typename Kernel, typename Tree>
typename Kernel::FT
compute_density_weight_for_original_point(
const typename Kernel::Point_3& query, ///< 3D point to project
Tree& tree, ///< KD-tree
Tree& aabb_tree, ///< KD-tree
const typename Kernel::FT radius
)
{
@ -318,30 +280,30 @@ compute_density_weight_for_original_point(
typedef typename Kernel::Vector_3 Vector;
typedef typename Kernel::FT FT;
// types for K nearest neighbors search
typedef regularize_and_simplify_internal::Kd_tree_traits<Kernel> Tree_traits;
typedef CGAL::Orthogonal_k_neighbor_search<Tree_traits> Neighbor_search;
typedef typename Neighbor_search::iterator Search_iterator;
// types for AABB
typedef Kernel::Sphere_3 Circle;
typedef std::vector<Point>::iterator Iterator;
typedef CGAL::AABB_point_primitive<Kernel, Iterator> Primitive;
typedef CGAL::AABB_traits<Kernel, Primitive> Traits_AABB;
typedef CGAL::AABB_tree<Traits_AABB> AABB_Tree;
//types for range search
typedef regularize_and_simplify_internal::Kd_tree_element<Kernel> Kd_tree_point;
typedef regularize_and_simplify_internal::Kd_tree_traits<Kernel> Traits;
typedef CGAL::Fuzzy_sphere<Traits> Fuzzy_sphere;
std::vector<typename Primitive::Id> neighbor_original_points;
Circle sphere_query(query, radius);
aabb_tree.all_contained_primitives(sphere_query,
std::back_inserter(neighbor_original_points));
//Compute density weight
FT radius2 = radius * radius;
FT density_weight = (FT)1.0;
FT iradius16 = -(FT)4.0 / radius2;
//range search
Fuzzy_sphere fs(query, radius, 0.0);
std::vector<Kd_tree_point> neighbors;
tree.search(std::back_inserter(neighbors), fs);
//parallel
std::vector<Kd_tree_point>::iterator iter = neighbors.begin();
for (; iter != neighbors.end(); iter++)
std::vector<typename Primitive::Id>::iterator iter = neighbor_original_points.begin();
for (; iter != neighbor_original_points.end(); iter++)
{
Point& np = *iter;
Point& np = *(*iter);
FT dist2 = CGAL::squared_distance(query, np);
density_weight += std::exp(dist2 * iradius16);
}
@ -364,7 +326,7 @@ template </*typename Concurrency_tag, */typename Kernel, typename Tree>
typename Kernel::FT
compute_density_weight_for_sample_point(
const typename Kernel::Point_3& query, ///< 3D point to project
Tree& tree, ///< KD-tree
Tree& aabb_tree, ///< KD-tree
const typename Kernel::FT radius
)
{
@ -373,30 +335,29 @@ compute_density_weight_for_sample_point(
typedef typename Kernel::Vector_3 Vector;
typedef typename Kernel::FT FT;
// types for K nearest neighbors search
typedef regularize_and_simplify_internal::Kd_tree_traits<Kernel> Tree_traits;
typedef CGAL::Orthogonal_k_neighbor_search<Tree_traits> Neighbor_search;
typedef typename Neighbor_search::iterator Search_iterator;
// types for AABB
typedef Kernel::Sphere_3 Circle;
typedef std::vector<Point>::iterator Iterator;
typedef CGAL::AABB_point_primitive<Kernel, Iterator> Primitive;
typedef CGAL::AABB_traits<Kernel, Primitive> Traits_AABB;
typedef CGAL::AABB_tree<Traits_AABB> AABB_Tree;
//types for range search
typedef regularize_and_simplify_internal::Kd_tree_element<Kernel> Kd_tree_point;
typedef regularize_and_simplify_internal::Kd_tree_traits<Kernel> Traits;
typedef CGAL::Fuzzy_sphere<Traits> Fuzzy_sphere;
std::vector<typename Primitive::Id> neighbor_sample_points;
Circle sphere_query(query, radius);
aabb_tree.all_contained_primitives(sphere_query,
std::back_inserter(neighbor_sample_points));
//Compute density weight
FT radius2 = radius * radius;
FT density_weight = (FT)1.0;
FT iradius16 = -(FT)4.0 / radius2;
//range search
Fuzzy_sphere fs(query, radius, 0.0);
std::vector<Point> neighbors;
tree.search(std::back_inserter(neighbors), fs);
//parallel
std::vector<Point>::iterator iter = neighbors.begin();
for (; iter != neighbors.end(); iter++)
std::vector<typename Primitive::Id>::iterator iter = neighbor_sample_points.begin();
for (; iter != neighbor_sample_points.end(); iter++)
{
Point& np = *iter;
Point& np = *(*iter);
FT dist2 = CGAL::squared_distance(query, np);
density_weight += std::exp(dist2 * iradius16);
}
@ -455,16 +416,9 @@ regularize_and_simplify_point_set(
typedef typename Kernel::Vector_3 Vector;
typedef typename Kernel::FT FT;
// types for K nearest neighbors search structure
typedef regularize_and_simplify_internal::Kd_tree_element<Kernel> Kd_tree_element;
typedef regularize_and_simplify_internal::Kd_tree_traits<Kernel> Tree_traits;
typedef CGAL::Orthogonal_k_neighbor_search<Tree_traits> Neighbor_search;
typedef typename Neighbor_search::Tree Tree;
typedef typename Neighbor_search::iterator Search_iterator;
// types for AABB
typedef Kernel::Sphere_3 Circle;
//typedef std::vector<Kd_tree_point>::iterator Iterator;
typedef std::vector<Point>::iterator Iterator;
typedef CGAL::AABB_point_primitive<Kernel, Iterator> Primitive;
typedef CGAL::AABB_traits<Kernel, Primitive> Traits_AABB;
@ -503,15 +457,6 @@ regularize_and_simplify_point_set(
task_timer.start();
std::cout << "Initialization / Compute Density For Original" << std::endl;
std::vector<Kd_tree_element> original_treeElements;
//parallel
for (it = first_original_point, i=0 ; it != beyond ; ++it, ++i)
{
Point& p0 = get(point_pmap,it);
original_treeElements.push_back(Kd_tree_element(p0,i));
}
Tree original_tree(original_treeElements.begin(),
original_treeElements.end());
AABB_Tree aabb_original_tree(first_original_point,
beyond);
@ -524,9 +469,9 @@ regularize_and_simplify_point_set(
for (it = first_original_point; it != beyond ; ++it)
{
FT density = regularize_and_simplify_internal::
compute_density_weight_for_original_point<Kernel, Tree>
compute_density_weight_for_original_point<Kernel, AABB_Tree>
(get(point_pmap, it),
original_tree,
aabb_original_tree,
radius);
original_density_weight_set.push_back(density);
@ -543,16 +488,9 @@ regularize_and_simplify_point_set(
task_timer.reset();
std::cout << "Compute average term and repulsion term " << std::endl;
// Initiate a KD-tree search for sample points
std::vector<Kd_tree_element> sample_treeElements;
//parallel
ForwardIterator first_sample_point = sample_points.begin();
for (i=0 ; i < sample_points.size(); i++)
{
Point& p0 = sample_points[i];
sample_treeElements.push_back(Kd_tree_element(p0,i));
}
Tree sample_tree(sample_treeElements.begin(), sample_treeElements.end());
AABB_Tree aabb_sample_tree(sample_points.begin(),
sample_points.end());
// Compute sample density weight for sample points if user needed
@ -564,8 +502,8 @@ regularize_and_simplify_point_set(
for (i=0 ; i < sample_points.size(); i++)
{
FT density = regularize_and_simplify_internal::
compute_density_weight_for_sample_point<Kernel, Tree>
(sample_points[i], sample_tree, radius);
compute_density_weight_for_sample_point<Kernel, AABB_Tree>
(sample_points[i], aabb_sample_tree, radius);
sample_density_weight_set.push_back(density);
}
@ -596,11 +534,11 @@ regularize_and_simplify_point_set(
Point& p = sample_points[i];
repulsion_set[i] = regularize_and_simplify_internal::
compute_repulsion_term<Kernel, AABB_Tree, ForwardIterator>
(p,
aabb_sample_tree,
radius,
sample_density_weight_set,
first_sample_point);
(p,
aabb_sample_tree,
radius,
sample_density_weight_set,
first_sample_point);
}
for (i = 0; i < sample_points.size(); i++)
@ -611,7 +549,7 @@ regularize_and_simplify_point_set(
long memory = CGAL::Memory_sizer().virtual_size();
std::cout << "done: " << task_timer.time() << " seconds, "
<< (memory>>20) << " Mb allocated" << std::endl;
<< (memory>>20) << " Mb allocated" << std::endl;
std::cout << "iterate: " << iter_n + 1 << std::endl << std::endl;
}