507 lines
20 KiB
C++
507 lines
20 KiB
C++
/*
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* Software License Agreement (BSD License)
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*
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* Copyright (c) 2010, Willow Garage, Inc.
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* All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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*
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* * Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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* * Redistributions in binary form must reproduce the above
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* copyright notice, this list of conditions and the following
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* disclaimer in the documentation and/or other materials provided
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* with the distribution.
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* * Neither the name of Willow Garage, Inc. nor the names of its
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* contributors may be used to endorse or promote products derived
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* from this software without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
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* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
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* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
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* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
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* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
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* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
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* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
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* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
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* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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* POSSIBILITY OF SUCH DAMAGE.
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*
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* $Id$
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*
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*/
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#pragma once
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#include <pcl/memory.h>
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#include <pcl/pcl_macros.h>
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#include <pcl/surface/reconstruction.h>
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#include <boost/dynamic_bitset/dynamic_bitset.hpp> // for dynamic_bitset
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#include <unordered_map>
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namespace pcl
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{
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/** \brief The 12 edges of a cell. */
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const int I_SHIFT_EP[12][2] = {
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{0, 4}, {1, 5}, {2, 6}, {3, 7},
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{0, 1}, {1, 2}, {2, 3}, {3, 0},
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{4, 5}, {5, 6}, {6, 7}, {7, 4}
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};
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const int I_SHIFT_PT[4] = {
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0, 4, 5, 7
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};
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const int I_SHIFT_EDGE[3][2] = {
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{0,1}, {1,3}, {1,2}
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};
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/** \brief Grid projection surface reconstruction method.
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* \author Rosie Li
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*
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* \note If you use this code in any academic work, please cite:
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* - Ruosi Li, Lu Liu, Ly Phan, Sasakthi Abeysinghe, Cindy Grimm, Tao Ju.
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* Polygonizing extremal surfaces with manifold guarantees.
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* In Proceedings of the 14th ACM Symposium on Solid and Physical Modeling, 2010.
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* \ingroup surface
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*/
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template <typename PointNT>
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class GridProjection : public SurfaceReconstruction<PointNT>
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{
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public:
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using Ptr = shared_ptr<GridProjection<PointNT> >;
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using ConstPtr = shared_ptr<const GridProjection<PointNT> >;
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using SurfaceReconstruction<PointNT>::input_;
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using SurfaceReconstruction<PointNT>::tree_;
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using PointCloudPtr = typename pcl::PointCloud<PointNT>::Ptr;
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using KdTree = pcl::KdTree<PointNT>;
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using KdTreePtr = typename KdTree::Ptr;
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/** \brief Data leaf. */
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struct Leaf
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{
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Leaf () {}
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pcl::Indices data_indices;
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Eigen::Vector4f pt_on_surface;
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Eigen::Vector3f vect_at_grid_pt;
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};
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typedef std::unordered_map<int, Leaf, std::hash<int>, std::equal_to<>, Eigen::aligned_allocator<std::pair<const int, Leaf>>> HashMap;
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/** \brief Constructor. */
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GridProjection ();
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/** \brief Constructor.
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* \param in_resolution set the resolution of the grid
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*/
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GridProjection (double in_resolution);
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/** \brief Destructor. */
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~GridProjection ();
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/** \brief Set the size of the grid cell
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* \param resolution the size of the grid cell
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*/
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inline void
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setResolution (double resolution)
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{
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leaf_size_ = resolution;
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}
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inline double
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getResolution () const
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{
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return (leaf_size_);
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}
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/** \brief When averaging the vectors, we find the union of all the input data
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* points within the padding area,and do a weighted average. Say if the padding
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* size is 1, when we process cell (x,y,z), we will find union of input data points
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* from (x-1) to (x+1), (y-1) to (y+1), (z-1) to (z+1)(in total, 27 cells). In this
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* way, even the cells itself doesn't contain any data points, we will still process it
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* because there are data points in the padding area. This can help us fix holes which
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* is smaller than the padding size.
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* \param padding_size The num of padding cells we want to create
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*/
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inline void
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setPaddingSize (int padding_size)
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{
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padding_size_ = padding_size;
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}
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inline int
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getPaddingSize () const
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{
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return (padding_size_);
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}
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/** \brief Set this only when using the k nearest neighbors search
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* instead of finding the point union
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* \param k The number of nearest neighbors we are looking for
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*/
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inline void
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setNearestNeighborNum (int k)
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{
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k_ = k;
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}
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inline int
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getNearestNeighborNum () const
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{
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return (k_);
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}
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/** \brief Binary search is used in projection. given a point x, we find another point
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* which is 3*cell_size_ far away from x. Then we do a binary search between these
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* two points to find where the projected point should be.
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*/
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inline void
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setMaxBinarySearchLevel (int max_binary_search_level)
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{
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max_binary_search_level_ = max_binary_search_level;
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}
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inline int
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getMaxBinarySearchLevel () const
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{
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return (max_binary_search_level_);
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}
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///////////////////////////////////////////////////////////
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inline const HashMap&
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getCellHashMap () const
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{
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return (cell_hash_map_);
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}
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inline const std::vector<Eigen::Vector3f, Eigen::aligned_allocator<Eigen::Vector3f> >&
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getVectorAtDataPoint () const
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{
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return (vector_at_data_point_);
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}
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inline const std::vector<Eigen::Vector4f, Eigen::aligned_allocator<Eigen::Vector4f> >&
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getSurface () const
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{
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return (surface_);
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}
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protected:
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/** \brief Get the bounding box for the input data points, also calculating the
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* cell size, and the gaussian scale factor
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*/
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void
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getBoundingBox ();
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/** \brief The actual surface reconstruction method.
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* \param[out] polygons the resultant polygons, as a set of vertices. The Vertices structure contains an array of point indices.
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*/
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bool
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reconstructPolygons (std::vector<pcl::Vertices> &polygons);
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/** \brief Create the surface.
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*
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* The 1st step is filling the padding, so that all the cells in the padding
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* area are in the hash map. The 2nd step is store the vector, and projected
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* point. The 3rd step is finding all the edges intersects the surface, and
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* creating surface.
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*
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* \param[out] output the resultant polygonal mesh
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*/
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void
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performReconstruction (pcl::PolygonMesh &output) override;
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/** \brief Create the surface.
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*
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* The 1st step is filling the padding, so that all the cells in the padding
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* area are in the hash map. The 2nd step is store the vector, and projected
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* point. The 3rd step is finding all the edges intersects the surface, and
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* creating surface.
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*
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* \param[out] points the resultant points lying on the surface
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* \param[out] polygons the resultant polygons, as a set of vertices. The Vertices structure contains an array of point indices.
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*/
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void
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performReconstruction (pcl::PointCloud<PointNT> &points,
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std::vector<pcl::Vertices> &polygons) override;
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/** \brief When the input data points don't fill into the 1*1*1 box,
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* scale them so that they can be filled in the unit box. Otherwise,
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* it will be some drawing problem when doing visulization
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* \param scale_factor scale all the input data point by scale_factor
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*/
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void
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scaleInputDataPoint (double scale_factor);
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/** \brief Get the 3d index (x,y,z) of the cell based on the location of
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* the cell
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* \param p the coordinate of the input point
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* \param index the output 3d index
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*/
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inline void
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getCellIndex (const Eigen::Vector4f &p, Eigen::Vector3i& index) const
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{
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for (int i = 0; i < 3; ++i)
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index[i] = static_cast<int> ((p[i] - min_p_(i)) / leaf_size_);
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}
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/** \brief Given the 3d index (x, y, z) of the cell, get the
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* coordinates of the cell center
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* \param index the output 3d index
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* \param center the resultant cell center
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*/
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inline void
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getCellCenterFromIndex (const Eigen::Vector3i &index, Eigen::Vector4f ¢er) const
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{
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for (int i = 0; i < 3; ++i)
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center[i] =
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min_p_[i] + static_cast<float> (index[i]) *
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static_cast<float> (leaf_size_) +
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static_cast<float> (leaf_size_) / 2.0f;
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}
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/** \brief Given cell center, caluate the coordinates of the eight vertices of the cell
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* \param cell_center the coordinates of the cell center
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* \param pts the coordinates of the 8 vertices
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*/
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void
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getVertexFromCellCenter (const Eigen::Vector4f &cell_center,
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std::vector<Eigen::Vector4f, Eigen::aligned_allocator<Eigen::Vector4f> > &pts) const;
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/** \brief Given an index (x, y, z) in 3d, translate it into the index
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* in 1d
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* \param index the index of the cell in (x,y,z) 3d format
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*/
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inline int
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getIndexIn1D (const Eigen::Vector3i &index) const
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{
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//assert(data_size_ > 0);
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return (index[0] * data_size_ * data_size_ +
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index[1] * data_size_ + index[2]);
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}
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/** \brief Given an index in 1d, translate it into the index (x, y, z)
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* in 3d
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* \param index_1d the input 1d index
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* \param index_3d the output 3d index
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*/
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inline void
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getIndexIn3D (int index_1d, Eigen::Vector3i& index_3d) const
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{
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//assert(data_size_ > 0);
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index_3d[0] = index_1d / (data_size_ * data_size_);
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index_1d -= index_3d[0] * data_size_ * data_size_;
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index_3d[1] = index_1d / data_size_;
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index_1d -= index_3d[1] * data_size_;
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index_3d[2] = index_1d;
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}
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/** \brief For a given 3d index of a cell, test whether the cells within its
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* padding area exist in the hash table, if no, create an entry for that cell.
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* \param index the index of the cell in (x,y,z) format
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*/
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void
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fillPad (const Eigen::Vector3i &index);
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/** \brief Obtain the index of a cell and the pad size.
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* \param index the input index
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* \param pt_union_indices the union of input data points within the cell and padding cells
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*/
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void
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getDataPtsUnion (const Eigen::Vector3i &index, pcl::Indices &pt_union_indices);
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/** \brief Given the index of a cell, exam it's up, left, front edges, and add
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* the vectices to m_surface list.the up, left, front edges only share 4
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* points, we first get the vectors at these 4 points and exam whether those
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* three edges are intersected by the surface \param index the input index
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* \param pt_union_indices the union of input data points within the cell and padding cells
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*/
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void
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createSurfaceForCell (const Eigen::Vector3i &index, pcl::Indices &pt_union_indices);
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/** \brief Given the coordinates of one point, project it onto the surface,
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* return the projected point. Do a binary search between p and p+projection_distance
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* to find the projected point
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* \param p the coordinates of the input point
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* \param pt_union_indices the union of input data points within the cell and padding cells
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* \param projection the resultant point projected
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*/
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void
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getProjection (const Eigen::Vector4f &p, pcl::Indices &pt_union_indices, Eigen::Vector4f &projection);
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/** \brief Given the coordinates of one point, project it onto the surface,
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* return the projected point. Find the plane which fits all the points in
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* pt_union_indices, projected p to the plane to get the projected point.
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* \param p the coordinates of the input point
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* \param pt_union_indices the union of input data points within the cell and padding cells
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* \param projection the resultant point projected
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*/
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void
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getProjectionWithPlaneFit (const Eigen::Vector4f &p,
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pcl::Indices &pt_union_indices,
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Eigen::Vector4f &projection);
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/** \brief Given the location of a point, get it's vector
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* \param p the coordinates of the input point
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* \param pt_union_indices the union of input data points within the cell and padding cells
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* \param vo the resultant vector
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*/
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void
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getVectorAtPoint (const Eigen::Vector4f &p,
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pcl::Indices &pt_union_indices, Eigen::Vector3f &vo);
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/** \brief Given the location of a point, get it's vector
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* \param p the coordinates of the input point
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* \param k_indices the k nearest neighbors of the query point
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* \param k_squared_distances the squared distances of the k nearest
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* neighbors to the query point
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* \param vo the resultant vector
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*/
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void
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getVectorAtPointKNN (const Eigen::Vector4f &p,
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pcl::Indices &k_indices,
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std::vector<float> &k_squared_distances,
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Eigen::Vector3f &vo);
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/** \brief Get the magnitude of the vector by summing up the distance.
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* \param p the coordinate of the input point
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* \param pt_union_indices the union of input data points within the cell and padding cells
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*/
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double
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getMagAtPoint (const Eigen::Vector4f &p, const pcl::Indices &pt_union_indices);
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/** \brief Get the 1st derivative
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* \param p the coordinate of the input point
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* \param vec the vector at point p
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* \param pt_union_indices the union of input data points within the cell and padding cells
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*/
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double
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getD1AtPoint (const Eigen::Vector4f &p, const Eigen::Vector3f &vec,
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const pcl::Indices &pt_union_indices);
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/** \brief Get the 2nd derivative
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* \param p the coordinate of the input point
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* \param vec the vector at point p
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* \param pt_union_indices the union of input data points within the cell and padding cells
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*/
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double
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getD2AtPoint (const Eigen::Vector4f &p, const Eigen::Vector3f &vec,
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const pcl::Indices &pt_union_indices);
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/** \brief Test whether the edge is intersected by the surface by
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* doing the dot product of the vector at two end points. Also test
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* whether the edge is intersected by the maximum surface by examing
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* the 2nd derivative of the intersection point
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* \param end_pts the two points of the edge
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* \param vect_at_end_pts
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* \param pt_union_indices the union of input data points within the cell and padding cells
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*/
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bool
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isIntersected (const std::vector<Eigen::Vector4f, Eigen::aligned_allocator<Eigen::Vector4f> > &end_pts,
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std::vector<Eigen::Vector3f, Eigen::aligned_allocator<Eigen::Vector3f> > &vect_at_end_pts,
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pcl::Indices &pt_union_indices);
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/** \brief Find point where the edge intersects the surface.
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* \param level binary search level
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* \param end_pts the two end points on the edge
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* \param vect_at_end_pts the vectors at the two end points
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* \param start_pt the starting point we use for binary search
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* \param pt_union_indices the union of input data points within the cell and padding cells
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* \param intersection the resultant intersection point
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*/
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void
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findIntersection (int level,
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const std::vector<Eigen::Vector4f, Eigen::aligned_allocator<Eigen::Vector4f> > &end_pts,
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const std::vector<Eigen::Vector3f, Eigen::aligned_allocator<Eigen::Vector3f> > &vect_at_end_pts,
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const Eigen::Vector4f &start_pt,
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pcl::Indices &pt_union_indices,
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Eigen::Vector4f &intersection);
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/** \brief Go through all the entries in the hash table and update the
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* cellData.
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*
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* When creating the hash table, the pt_on_surface field store the center
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* point of the cell.After calling this function, the projection operator will
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* project the center point onto the surface, and the pt_on_surface field will
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* be updated using the projected point.Also the vect_at_grid_pt field will be
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* updated using the vector at the upper left front vertex of the cell.
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*
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* \param index_1d the index of the cell after flatting it's 3d index into a 1d array
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* \param index_3d the index of the cell in (x,y,z) 3d format
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* \param pt_union_indices the union of input data points within the cell and pads
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* \param cell_data information stored in the cell
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*/
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void
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storeVectAndSurfacePoint (int index_1d, const Eigen::Vector3i &index_3d,
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pcl::Indices &pt_union_indices, const Leaf &cell_data);
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/** \brief Go through all the entries in the hash table and update the cellData.
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* When creating the hash table, the pt_on_surface field store the center point
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* of the cell.After calling this function, the projection operator will project the
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* center point onto the surface, and the pt_on_surface field will be updated
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* using the projected point.Also the vect_at_grid_pt field will be updated using
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* the vector at the upper left front vertex of the cell. When projecting the point
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* and calculating the vector, using K nearest neighbors instead of using the
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* union of input data point within the cell and pads.
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*
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* \param index_1d the index of the cell after flatting it's 3d index into a 1d array
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* \param index_3d the index of the cell in (x,y,z) 3d format
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* \param cell_data information stored in the cell
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*/
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void
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storeVectAndSurfacePointKNN (int index_1d, const Eigen::Vector3i &index_3d, const Leaf &cell_data);
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private:
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/** \brief Map containing the set of leaves. */
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HashMap cell_hash_map_;
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/** \brief Min and max data points. */
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Eigen::Vector4f min_p_, max_p_;
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/** \brief The size of a leaf. */
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double leaf_size_;
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/** \brief Gaussian scale. */
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double gaussian_scale_;
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/** \brief Data size. */
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int data_size_;
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/** \brief Max binary search level. */
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int max_binary_search_level_;
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/** \brief Number of neighbors (k) to use. */
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int k_;
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/** \brief Padding size. */
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int padding_size_;
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/** \brief The point cloud input (XYZ+Normals). */
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PointCloudPtr data_;
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/** \brief Store the surface normal(vector) at the each input data point. */
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std::vector<Eigen::Vector3f, Eigen::aligned_allocator<Eigen::Vector3f> > vector_at_data_point_;
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/** \brief An array of points which lay on the output surface. */
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std::vector<Eigen::Vector4f, Eigen::aligned_allocator<Eigen::Vector4f> > surface_;
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/** \brief Bit map which tells if there is any input data point in the cell. */
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boost::dynamic_bitset<> occupied_cell_list_;
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/** \brief Class get name method. */
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std::string getClassName () const override { return ("GridProjection"); }
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public:
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PCL_MAKE_ALIGNED_OPERATOR_NEW
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};
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}
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