139 lines
4.9 KiB
C++
139 lines
4.9 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: cvfh.hpp 5311 2012-03-26 22:02:04Z aaldoma $
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*
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*/
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#ifndef PCL_FEATURES_IMPL_CRH_H_
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#define PCL_FEATURES_IMPL_CRH_H_
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#include <pcl/features/crh.h>
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#include <pcl/common/fft/kiss_fftr.h>
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#include <pcl/common/transforms.h>
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//////////////////////////////////////////////////////////////////////////////////////////////
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template<typename PointInT, typename PointNT, typename PointOutT>
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void
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pcl::CRHEstimation<PointInT, PointNT, PointOutT>::computeFeature (PointCloudOut &output)
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{
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// Check if input was set
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if (!normals_)
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{
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PCL_ERROR ("[pcl::%s::computeFeature] No input dataset containing normals was given!\n", getClassName ().c_str ());
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output.width = output.height = 0;
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output.clear ();
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return;
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}
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if (normals_->size () != surface_->size ())
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{
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PCL_ERROR ("[pcl::%s::computeFeature] The number of points in the input dataset differs from the number of points in the dataset containing the normals!\n", getClassName ().c_str ());
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output.width = output.height = 0;
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output.clear ();
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return;
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}
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Eigen::Vector3f plane_normal;
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plane_normal[0] = -centroid_[0];
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plane_normal[1] = -centroid_[1];
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plane_normal[2] = -centroid_[2];
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Eigen::Vector3f z_vector = Eigen::Vector3f::UnitZ ();
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plane_normal.normalize ();
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Eigen::Vector3f axis = plane_normal.cross (z_vector);
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double rotation = -asin (axis.norm ());
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axis.normalize ();
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int nbins = nbins_;
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int bin_angle = 360 / nbins;
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Eigen::Affine3f transformPC (Eigen::AngleAxisf (static_cast<float> (rotation), axis));
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pcl::PointCloud<pcl::PointNormal> grid;
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grid.resize (indices_->size ());
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for (std::size_t i = 0; i < indices_->size (); i++)
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{
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grid[i].getVector4fMap () = (*surface_)[(*indices_)[i]].getVector4fMap ();
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grid[i].getNormalVector4fMap () = (*normals_)[(*indices_)[i]].getNormalVector4fMap ();
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}
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pcl::transformPointCloudWithNormals (grid, grid, transformPC);
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//fill spatial data vector and the zero-initialize or "value-initialize" an array on c++,
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// the initialization is made with () after the [nbins]
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std::vector<kiss_fft_scalar> spatial_data(nbins);
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float sum_w = 0;
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for (const auto &point : grid.points)
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{
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int bin = static_cast<int> ((((std::atan2 (point.normal_y, point.normal_x) + M_PI) * 180 / M_PI) / bin_angle)) % nbins;
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float w = std::sqrt (point.normal_y * point.normal_y + point.normal_x * point.normal_x);
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sum_w += w;
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spatial_data[bin] += w;
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}
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for (auto& data: spatial_data)
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data /= sum_w;
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std::vector<kiss_fft_cpx> freq_data(nbins / 2 + 1);
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kiss_fftr_cfg mycfg = kiss_fftr_alloc (nbins, 0, nullptr, nullptr);
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kiss_fftr (mycfg, spatial_data.data (), freq_data.data ());
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for (auto& data: freq_data)
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{
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data.r /= freq_data[0].r;
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data.i /= freq_data[0].r;
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}
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output.resize (1);
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output.width = output.height = 1;
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output[0].histogram[0] = freq_data[0].r; //dc
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int k = 1;
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for (int i = 1; i < (nbins / 2); i++, k += 2)
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{
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output[0].histogram[k] = freq_data[i].r;
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output[0].histogram[k + 1] = freq_data[i].i;
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}
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output[0].histogram[nbins - 1] = freq_data[nbins / 2].r; //nyquist
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}
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#define PCL_INSTANTIATE_CRHEstimation(T,NT,OutT) template class PCL_EXPORTS pcl::CRHEstimation<T,NT,OutT>;
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#endif // PCL_FEATURES_IMPL_CRH_H_
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