164 lines
6.4 KiB
C++
164 lines
6.4 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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#ifndef PCL_FEATURES_IMPL_MOMENT_INVARIANTS_H_
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#define PCL_FEATURES_IMPL_MOMENT_INVARIANTS_H_
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#include <pcl/features/moment_invariants.h>
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#include <pcl/common/centroid.h>
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//////////////////////////////////////////////////////////////////////////////////////////////
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template <typename PointInT, typename PointOutT> void
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pcl::MomentInvariantsEstimation<PointInT, PointOutT>::computePointMomentInvariants (
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const pcl::PointCloud<PointInT> &cloud, const pcl::Indices &indices,
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float &j1, float &j2, float &j3)
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{
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// Estimate the XYZ centroid
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compute3DCentroid (cloud, indices, xyz_centroid_);
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// Initialize the centralized moments
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float mu200 = 0, mu020 = 0, mu002 = 0, mu110 = 0, mu101 = 0, mu011 = 0;
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// Iterate over the nearest neighbors set
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for (const auto &index : indices)
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{
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// Demean the points
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temp_pt_[0] = cloud[index].x - xyz_centroid_[0];
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temp_pt_[1] = cloud[index].y - xyz_centroid_[1];
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temp_pt_[2] = cloud[index].z - xyz_centroid_[2];
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mu200 += temp_pt_[0] * temp_pt_[0];
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mu020 += temp_pt_[1] * temp_pt_[1];
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mu002 += temp_pt_[2] * temp_pt_[2];
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mu110 += temp_pt_[0] * temp_pt_[1];
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mu101 += temp_pt_[0] * temp_pt_[2];
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mu011 += temp_pt_[1] * temp_pt_[2];
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}
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// Save the moment invariants
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j1 = mu200 + mu020 + mu002;
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j2 = mu200*mu020 + mu200*mu002 + mu020*mu002 - mu110*mu110 - mu101*mu101 - mu011*mu011;
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j3 = mu200*mu020*mu002 + 2*mu110*mu101*mu011 - mu002*mu110*mu110 - mu020*mu101*mu101 - mu200*mu011*mu011;
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}
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//////////////////////////////////////////////////////////////////////////////////////////////
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template <typename PointInT, typename PointOutT> void
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pcl::MomentInvariantsEstimation<PointInT, PointOutT>::computePointMomentInvariants (
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const pcl::PointCloud<PointInT> &cloud, float &j1, float &j2, float &j3)
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{
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// Estimate the XYZ centroid
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compute3DCentroid (cloud, xyz_centroid_);
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// Initialize the centralized moments
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float mu200 = 0, mu020 = 0, mu002 = 0, mu110 = 0, mu101 = 0, mu011 = 0;
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// Iterate over the nearest neighbors set
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for (const auto& point: cloud.points)
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{
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// Demean the points
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temp_pt_[0] = point.x - xyz_centroid_[0];
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temp_pt_[1] = point.y - xyz_centroid_[1];
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temp_pt_[2] = point.z - xyz_centroid_[2];
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mu200 += temp_pt_[0] * temp_pt_[0];
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mu020 += temp_pt_[1] * temp_pt_[1];
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mu002 += temp_pt_[2] * temp_pt_[2];
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mu110 += temp_pt_[0] * temp_pt_[1];
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mu101 += temp_pt_[0] * temp_pt_[2];
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mu011 += temp_pt_[1] * temp_pt_[2];
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}
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// Save the moment invariants
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j1 = mu200 + mu020 + mu002;
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j2 = mu200*mu020 + mu200*mu002 + mu020*mu002 - mu110*mu110 - mu101*mu101 - mu011*mu011;
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j3 = mu200*mu020*mu002 + 2*mu110*mu101*mu011 - mu002*mu110*mu110 - mu020*mu101*mu101 - mu200*mu011*mu011;
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}
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//////////////////////////////////////////////////////////////////////////////////////////////
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template <typename PointInT, typename PointOutT> void
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pcl::MomentInvariantsEstimation<PointInT, PointOutT>::computeFeature (PointCloudOut &output)
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{
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// Allocate enough space to hold the results
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// \note This resize is irrelevant for a radiusSearch ().
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pcl::Indices nn_indices (k_);
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std::vector<float> nn_dists (k_);
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output.is_dense = true;
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// Save a few cycles by not checking every point for NaN/Inf values if the cloud is set to dense
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if (input_->is_dense)
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{
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// Iterating over the entire index vector
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for (std::size_t idx = 0; idx < indices_->size (); ++idx)
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{
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if (this->searchForNeighbors ((*indices_)[idx], search_parameter_, nn_indices, nn_dists) == 0)
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{
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output[idx].j1 = output[idx].j2 = output[idx].j3 = std::numeric_limits<float>::quiet_NaN ();
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output.is_dense = false;
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continue;
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}
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computePointMomentInvariants (*surface_, nn_indices,
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output[idx].j1, output[idx].j2, output[idx].j3);
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}
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}
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else
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{
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// Iterating over the entire index vector
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for (std::size_t idx = 0; idx < indices_->size (); ++idx)
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{
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if (!isFinite ((*input_)[(*indices_)[idx]]) ||
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this->searchForNeighbors ((*indices_)[idx], search_parameter_, nn_indices, nn_dists) == 0)
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{
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output[idx].j1 = output[idx].j2 = output[idx].j3 = std::numeric_limits<float>::quiet_NaN ();
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output.is_dense = false;
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continue;
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}
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computePointMomentInvariants (*surface_, nn_indices,
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output[idx].j1, output[idx].j2, output[idx].j3);
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}
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}
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}
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#define PCL_INSTANTIATE_MomentInvariantsEstimation(T,NT) template class PCL_EXPORTS pcl::MomentInvariantsEstimation<T,NT>;
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#endif // PCL_FEATURES_IMPL_MOMENT_INVARIANTS_H_
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