265 lines
12 KiB
C++
265 lines
12 KiB
C++
/*
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* Software License Agreement (BSD License)
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*
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* Point Cloud Library (PCL) - www.pointclouds.org
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* Copyright (c) 2010-2011, Willow Garage, Inc.
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* Copyright (c) 2012-, Open Perception, Inc.
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*
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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 the copyright holder(s) 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 <numeric> // for partial_sum
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#include <pcl/features/usc.h>
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#include <pcl/features/shot_lrf.h>
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#include <pcl/common/angles.h>
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#include <pcl/common/geometry.h>
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#include <pcl/common/point_tests.h> // for pcl::isFinite
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#include <pcl/common/utils.h>
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//////////////////////////////////////////////////////////////////////////////////////////////
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template <typename PointInT, typename PointOutT, typename PointRFT> bool
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pcl::UniqueShapeContext<PointInT, PointOutT, PointRFT>::initCompute ()
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{
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if (!Feature<PointInT, PointOutT>::initCompute ())
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{
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PCL_ERROR ("[pcl::%s::initCompute] Init failed.\n", getClassName ().c_str ());
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return (false);
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}
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// Default LRF estimation alg: SHOTLocalReferenceFrameEstimation
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typename SHOTLocalReferenceFrameEstimation<PointInT, PointRFT>::Ptr lrf_estimator(new SHOTLocalReferenceFrameEstimation<PointInT, PointRFT>());
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lrf_estimator->setRadiusSearch (local_radius_);
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lrf_estimator->setInputCloud (input_);
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lrf_estimator->setIndices (indices_);
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if (!fake_surface_)
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lrf_estimator->setSearchSurface(surface_);
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if (!FeatureWithLocalReferenceFrames<PointInT, PointRFT>::initLocalReferenceFrames (indices_->size (), lrf_estimator))
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{
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PCL_ERROR ("[pcl::%s::initCompute] Init failed.\n", getClassName ().c_str ());
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return (false);
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}
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if (search_radius_< min_radius_)
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{
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PCL_ERROR ("[pcl::%s::initCompute] search_radius_ must be GREATER than min_radius_.\n", getClassName ().c_str ());
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return (false);
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}
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// Update descriptor length
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descriptor_length_ = elevation_bins_ * azimuth_bins_ * radius_bins_;
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// Compute radial, elevation and azimuth divisions
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float azimuth_interval = 360.0f / static_cast<float> (azimuth_bins_);
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float elevation_interval = 180.0f / static_cast<float> (elevation_bins_);
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// Reallocate divisions and volume lut
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radii_interval_.clear ();
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phi_divisions_.clear ();
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theta_divisions_.clear ();
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volume_lut_.clear ();
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// Fills radii interval based on formula (1) in section 2.1 of Frome's paper
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radii_interval_.resize (radius_bins_ + 1);
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for (std::size_t j = 0; j < radius_bins_ + 1; j++)
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radii_interval_[j] = static_cast<float> (std::exp (std::log (min_radius_) + ((static_cast<float> (j) / static_cast<float> (radius_bins_)) * std::log (search_radius_/min_radius_))));
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// Fill theta divisions of elevation
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theta_divisions_.resize (elevation_bins_ + 1, elevation_interval);
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theta_divisions_[0] = 0;
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std::partial_sum(theta_divisions_.begin (), theta_divisions_.end (), theta_divisions_.begin ());
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// Fill phi divisions of elevation
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phi_divisions_.resize (azimuth_bins_ + 1, azimuth_interval);
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phi_divisions_[0] = 0;
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std::partial_sum(phi_divisions_.begin (), phi_divisions_.end (), phi_divisions_.begin ());
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// LookUp Table that contains the volume of all the bins
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// "phi" term of the volume integral
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// "integr_phi" has always the same value so we compute it only one time
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float integr_phi = pcl::deg2rad (phi_divisions_[1]) - pcl::deg2rad (phi_divisions_[0]);
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// exponential to compute the cube root using pow
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float e = 1.0f / 3.0f;
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// Resize volume look up table
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volume_lut_.resize (radius_bins_ * elevation_bins_ * azimuth_bins_);
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// Fill volumes look up table
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for (std::size_t j = 0; j < radius_bins_; j++)
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{
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// "r" term of the volume integral
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float integr_r = (radii_interval_[j+1]*radii_interval_[j+1]*radii_interval_[j+1] / 3) - (radii_interval_[j]*radii_interval_[j]*radii_interval_[j]/ 3);
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for (std::size_t k = 0; k < elevation_bins_; k++)
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{
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// "theta" term of the volume integral
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float integr_theta = std::cos (deg2rad (theta_divisions_[k])) - std::cos (deg2rad (theta_divisions_[k+1]));
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// Volume
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float V = integr_phi * integr_theta * integr_r;
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// Compute cube root of the computed volume commented for performance but left
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// here for clarity
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// float cbrt = pow(V, e);
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// cbrt = 1 / cbrt;
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for (std::size_t l = 0; l < azimuth_bins_; l++)
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// Store in lut 1/cbrt
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//volume_lut_[ (l*elevation_bins_*radius_bins_) + k*radius_bins_ + j ] = cbrt;
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volume_lut_[(l*elevation_bins_*radius_bins_) + k*radius_bins_ + j] = 1.0f / powf (V, e);
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}
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}
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return (true);
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}
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//////////////////////////////////////////////////////////////////////////////////////////////
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template <typename PointInT, typename PointOutT, typename PointRFT> void
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pcl::UniqueShapeContext<PointInT, PointOutT, PointRFT>::computePointDescriptor (std::size_t index, /*float rf[9],*/ std::vector<float> &desc)
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{
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pcl::Vector3fMapConst origin = (*input_)[(*indices_)[index]].getVector3fMap ();
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const Eigen::Vector3f x_axis ((*frames_)[index].x_axis[0],
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(*frames_)[index].x_axis[1],
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(*frames_)[index].x_axis[2]);
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//const Eigen::Vector3f& y_axis = (*frames_)[index].y_axis.getNormalVector3fMap ();
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const Eigen::Vector3f normal ((*frames_)[index].z_axis[0],
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(*frames_)[index].z_axis[1],
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(*frames_)[index].z_axis[2]);
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// Find every point within specified search_radius_
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pcl::Indices nn_indices;
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std::vector<float> nn_dists;
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const std::size_t neighb_cnt = searchForNeighbors ((*indices_)[index], search_radius_, nn_indices, nn_dists);
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// For each point within radius
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for (std::size_t ne = 0; ne < neighb_cnt; ne++)
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{
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if (pcl::utils::equal(nn_dists[ne], 0.0f))
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continue;
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// Get neighbours coordinates
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Eigen::Vector3f neighbour = (*surface_)[nn_indices[ne]].getVector3fMap ();
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// ----- Compute current neighbour polar coordinates -----
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// Get distance between the neighbour and the origin
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float r = std::sqrt (nn_dists[ne]);
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// Project point into the tangent plane
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Eigen::Vector3f proj;
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pcl::geometry::project (neighbour, origin, normal, proj);
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proj -= origin;
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// Normalize to compute the dot product
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proj.normalize ();
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// Compute the angle between the projection and the x axis in the interval [0,360]
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Eigen::Vector3f cross = x_axis.cross (proj);
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float phi = rad2deg (std::atan2 (cross.norm (), x_axis.dot (proj)));
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phi = cross.dot (normal) < 0.f ? (360.0f - phi) : phi;
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/// Compute the angle between the neighbour and the z axis (normal) in the interval [0, 180]
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Eigen::Vector3f no = neighbour - origin;
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no.normalize ();
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float theta = normal.dot (no);
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theta = pcl::rad2deg (std::acos (std::min (1.0f, std::max (-1.0f, theta))));
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/// Compute the Bin(j, k, l) coordinates of current neighbour
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const auto rad_min = std::lower_bound(std::next (radii_interval_.cbegin ()), radii_interval_.cend (), r);
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const auto theta_min = std::lower_bound(std::next (theta_divisions_.cbegin ()), theta_divisions_.cend (), theta);
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const auto phi_min = std::lower_bound(std::next (phi_divisions_.cbegin ()), phi_divisions_.cend (), phi);
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/// Bin (j, k, l)
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const auto j = std::distance(radii_interval_.cbegin (), std::prev(rad_min));
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const auto k = std::distance(theta_divisions_.cbegin (), std::prev(theta_min));
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const auto l = std::distance(phi_divisions_.cbegin (), std::prev(phi_min));
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/// Local point density = number of points in a sphere of radius "point_density_radius_" around the current neighbour
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pcl::Indices neighbour_indices;
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std::vector<float> neighbour_didtances;
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float point_density = static_cast<float> (searchForNeighbors (*surface_, nn_indices[ne], point_density_radius_, neighbour_indices, neighbour_didtances));
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/// point_density is always bigger than 0 because FindPointsWithinRadius returns at least the point itself
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float w = (1.0f / point_density) * volume_lut_[(l*elevation_bins_*radius_bins_) +
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(k*radius_bins_) +
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j];
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assert (w >= 0.0);
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if (w == std::numeric_limits<float>::infinity ())
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PCL_ERROR ("Shape Context Error INF!\n");
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if (std::isnan(w))
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PCL_ERROR ("Shape Context Error IND!\n");
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/// Accumulate w into correspondent Bin(j,k,l)
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desc[(l*elevation_bins_*radius_bins_) + (k*radius_bins_) + j] += w;
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assert (desc[(l*elevation_bins_*radius_bins_) + (k*radius_bins_) + j] >= 0);
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} // end for each neighbour
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}
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//////////////////////////////////////////////////////////////////////////////////////////////
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template <typename PointInT, typename PointOutT, typename PointRFT> void
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pcl::UniqueShapeContext<PointInT, PointOutT, PointRFT>::computeFeature (PointCloudOut &output)
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{
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assert (descriptor_length_ == 1960);
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output.is_dense = true;
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for (std::size_t point_index = 0; point_index < indices_->size (); ++point_index)
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{
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//output[point_index].descriptor.resize (descriptor_length_);
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// If the point is not finite, set the descriptor to NaN and continue
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const PointRFT& current_frame = (*frames_)[point_index];
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if (!isFinite ((*input_)[(*indices_)[point_index]]) ||
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!std::isfinite (current_frame.x_axis[0]) ||
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!std::isfinite (current_frame.y_axis[0]) ||
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!std::isfinite (current_frame.z_axis[0]) )
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{
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std::fill_n (output[point_index].descriptor, descriptor_length_,
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std::numeric_limits<float>::quiet_NaN ());
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std::fill_n (output[point_index].rf, 9, 0);
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output.is_dense = false;
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continue;
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}
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for (int d = 0; d < 3; ++d)
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{
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output[point_index].rf[0 + d] = current_frame.x_axis[d];
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output[point_index].rf[3 + d] = current_frame.y_axis[d];
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output[point_index].rf[6 + d] = current_frame.z_axis[d];
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}
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std::vector<float> descriptor (descriptor_length_);
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computePointDescriptor (point_index, descriptor);
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std::copy (descriptor.cbegin (), descriptor.cend (), output[point_index].descriptor);
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}
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}
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#define PCL_INSTANTIATE_UniqueShapeContext(T,OutT,RFT) template class PCL_EXPORTS pcl::UniqueShapeContext<T,OutT,RFT>;
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