412 lines
19 KiB
C
412 lines
19 KiB
C
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/*
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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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*
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*/
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#pragma once
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#include <pcl/point_types.h>
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#include <pcl/features/feature.h>
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#include <array> // for sRGB_LUT, sXYZ_LUT
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namespace pcl
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{
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/** \brief SHOTEstimation estimates the Signature of Histograms of OrienTations (SHOT) descriptor for
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* a given point cloud dataset containing points and normals.
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*
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* The suggested PointOutT is pcl::SHOT352.
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*
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* \note If you use this code in any academic work, please cite:
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*
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* - F. Tombari, S. Salti, L. Di Stefano
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* Unique Signatures of Histograms for Local Surface Description.
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* In Proceedings of the 11th European Conference on Computer Vision (ECCV),
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* Heraklion, Greece, September 5-11 2010.
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* - F. Tombari, S. Salti, L. Di Stefano
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* A Combined Texture-Shape Descriptor For Enhanced 3D Feature Matching.
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* In Proceedings of the 18th International Conference on Image Processing (ICIP),
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* Brussels, Belgium, September 11-14 2011.
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*
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* \author Samuele Salti, Federico Tombari
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* \ingroup features
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*/
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template <typename PointInT, typename PointNT, typename PointOutT, typename PointRFT = pcl::ReferenceFrame>
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class SHOTEstimationBase : public FeatureFromNormals<PointInT, PointNT, PointOutT>,
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public FeatureWithLocalReferenceFrames<PointInT, PointRFT>
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{
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public:
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using Ptr = shared_ptr<SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT> >;
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using ConstPtr = shared_ptr<const SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT> >;
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using Feature<PointInT, PointOutT>::feature_name_;
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using Feature<PointInT, PointOutT>::getClassName;
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using Feature<PointInT, PointOutT>::input_;
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using Feature<PointInT, PointOutT>::indices_;
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using Feature<PointInT, PointOutT>::k_;
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using Feature<PointInT, PointOutT>::search_parameter_;
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using Feature<PointInT, PointOutT>::search_radius_;
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using Feature<PointInT, PointOutT>::surface_;
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using Feature<PointInT, PointOutT>::fake_surface_;
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using FeatureFromNormals<PointInT, PointNT, PointOutT>::normals_;
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using FeatureWithLocalReferenceFrames<PointInT, PointRFT>::frames_;
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using PointCloudIn = typename Feature<PointInT, PointOutT>::PointCloudIn;
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protected:
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/** \brief Empty constructor.
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* \param[in] nr_shape_bins the number of bins in the shape histogram
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*/
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SHOTEstimationBase (int nr_shape_bins = 10) :
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nr_shape_bins_ (nr_shape_bins),
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lrf_radius_ (0),
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sqradius_ (0), radius3_4_ (0), radius1_4_ (0), radius1_2_ (0),
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nr_grid_sector_ (32),
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maxAngularSectors_ (32),
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descLength_ (0)
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{
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feature_name_ = "SHOTEstimation";
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};
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public:
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/** \brief Empty destructor */
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~SHOTEstimationBase () {}
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/** \brief Estimate the SHOT descriptor for a given point based on its spatial neighborhood of 3D points with normals
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* \param[in] index the index of the point in indices_
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* \param[in] indices the k-neighborhood point indices in surface_
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* \param[in] sqr_dists the k-neighborhood point distances in surface_
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* \param[out] shot the resultant SHOT descriptor representing the feature at the query point
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*/
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virtual void
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computePointSHOT (const int index,
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const pcl::Indices &indices,
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const std::vector<float> &sqr_dists,
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Eigen::VectorXf &shot) = 0;
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/** \brief Set the radius used for local reference frame estimation if the frames are not set by the user */
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virtual void
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setLRFRadius (float radius) { lrf_radius_ = radius; }
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/** \brief Get the radius used for local reference frame estimation */
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virtual float
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getLRFRadius () const { return lrf_radius_; }
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protected:
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/** \brief This method should get called before starting the actual computation. */
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bool
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initCompute () override;
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/** \brief Quadrilinear interpolation used when color and shape descriptions are NOT activated simultaneously
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*
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* \param[in] indices the neighborhood point indices
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* \param[in] sqr_dists the neighborhood point distances
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* \param[in] index the index of the point in indices_
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* \param[out] binDistance the resultant distance shape histogram
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* \param[in] nr_bins the number of bins in the shape histogram
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* \param[out] shot the resultant SHOT histogram
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*/
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void
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interpolateSingleChannel (const pcl::Indices &indices,
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const std::vector<float> &sqr_dists,
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const int index,
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std::vector<double> &binDistance,
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const int nr_bins,
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Eigen::VectorXf &shot);
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/** \brief Normalize the SHOT histogram.
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* \param[in,out] shot the SHOT histogram
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* \param[in] desc_length the length of the histogram
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*/
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void
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normalizeHistogram (Eigen::VectorXf &shot, int desc_length);
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/** \brief Create a binned distance shape histogram
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* \param[in] index the index of the point in indices_
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* \param[in] indices the k-neighborhood point indices in surface_
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* \param[out] bin_distance_shape the resultant histogram
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*/
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void
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createBinDistanceShape (int index, const pcl::Indices &indices,
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std::vector<double> &bin_distance_shape);
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/** \brief The number of bins in each shape histogram. */
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int nr_shape_bins_;
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/** \brief Placeholder for a point's SHOT. */
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Eigen::VectorXf shot_;
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/** \brief The radius used for the LRF computation */
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float lrf_radius_;
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/** \brief The squared search radius. */
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double sqradius_;
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/** \brief 3/4 of the search radius. */
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double radius3_4_;
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/** \brief 1/4 of the search radius. */
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double radius1_4_;
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/** \brief 1/2 of the search radius. */
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double radius1_2_;
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/** \brief Number of azimuthal sectors. */
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const int nr_grid_sector_;
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/** \brief ... */
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const int maxAngularSectors_;
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/** \brief One SHOT length. */
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int descLength_;
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};
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/** \brief SHOTEstimation estimates the Signature of Histograms of OrienTations (SHOT) descriptor for
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* a given point cloud dataset containing points and normals.
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*
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* The suggested PointOutT is pcl::SHOT352
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*
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* \note If you use this code in any academic work, please cite:
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*
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* - F. Tombari, S. Salti, L. Di Stefano
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* Unique Signatures of Histograms for Local Surface Description.
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* In Proceedings of the 11th European Conference on Computer Vision (ECCV),
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* Heraklion, Greece, September 5-11 2010.
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* - F. Tombari, S. Salti, L. Di Stefano
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* A Combined Texture-Shape Descriptor For Enhanced 3D Feature Matching.
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* In Proceedings of the 18th International Conference on Image Processing (ICIP),
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* Brussels, Belgium, September 11-14 2011.
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*
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* \author Samuele Salti, Federico Tombari
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* \ingroup features
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*/
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template <typename PointInT, typename PointNT, typename PointOutT = pcl::SHOT352, typename PointRFT = pcl::ReferenceFrame>
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class SHOTEstimation : public SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>
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{
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public:
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using Ptr = shared_ptr<SHOTEstimation<PointInT, PointNT, PointOutT, PointRFT> >;
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using ConstPtr = shared_ptr<const SHOTEstimation<PointInT, PointNT, PointOutT, PointRFT> >;
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using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::feature_name_;
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using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::getClassName;
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using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::indices_;
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using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::k_;
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using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::search_parameter_;
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using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::search_radius_;
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using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::surface_;
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using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::input_;
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using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::normals_;
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using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::descLength_;
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using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::nr_grid_sector_;
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using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::nr_shape_bins_;
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using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::sqradius_;
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using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::radius3_4_;
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using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::radius1_4_;
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using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::radius1_2_;
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using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::maxAngularSectors_;
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using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::interpolateSingleChannel;
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using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::shot_;
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using FeatureWithLocalReferenceFrames<PointInT, PointRFT>::frames_;
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using PointCloudIn = typename Feature<PointInT, PointOutT>::PointCloudIn;
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/** \brief Empty constructor. */
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SHOTEstimation () : SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT> (10)
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{
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feature_name_ = "SHOTEstimation";
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};
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/** \brief Empty destructor */
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~SHOTEstimation () {}
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/** \brief Estimate the SHOT descriptor for a given point based on its spatial neighborhood of 3D points with normals
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* \param[in] index the index of the point in indices_
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* \param[in] indices the k-neighborhood point indices in surface_
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* \param[in] sqr_dists the k-neighborhood point distances in surface_
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* \param[out] shot the resultant SHOT descriptor representing the feature at the query point
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*/
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void
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computePointSHOT (const int index,
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const pcl::Indices &indices,
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const std::vector<float> &sqr_dists,
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Eigen::VectorXf &shot) override;
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protected:
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/** \brief Estimate the Signatures of Histograms of OrienTations (SHOT) descriptors at a set of points given by
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* <setInputCloud (), setIndices ()> using the surface in setSearchSurface () and the spatial locator in
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* setSearchMethod ()
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* \param output the resultant point cloud model dataset that contains the SHOT feature estimates
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*/
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void
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computeFeature (pcl::PointCloud<PointOutT> &output) override;
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};
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/** \brief SHOTColorEstimation estimates the Signature of Histograms of OrienTations (SHOT) descriptor for a given point cloud dataset
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* containing points, normals and colors.
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*
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* The suggested PointOutT is pcl::SHOT1344
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*
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* \note If you use this code in any academic work, please cite:
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*
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* - F. Tombari, S. Salti, L. Di Stefano
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* Unique Signatures of Histograms for Local Surface Description.
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* In Proceedings of the 11th European Conference on Computer Vision (ECCV),
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* Heraklion, Greece, September 5-11 2010.
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* - F. Tombari, S. Salti, L. Di Stefano
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* A Combined Texture-Shape Descriptor For Enhanced 3D Feature Matching.
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* In Proceedings of the 18th International Conference on Image Processing (ICIP),
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* Brussels, Belgium, September 11-14 2011.
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*
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* \author Samuele Salti, Federico Tombari
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* \ingroup features
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*/
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template <typename PointInT, typename PointNT, typename PointOutT = pcl::SHOT1344, typename PointRFT = pcl::ReferenceFrame>
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class SHOTColorEstimation : public SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>
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{
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public:
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using Ptr = shared_ptr<SHOTColorEstimation<PointInT, PointNT, PointOutT, PointRFT> >;
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using ConstPtr = shared_ptr<const SHOTColorEstimation<PointInT, PointNT, PointOutT, PointRFT> >;
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using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::feature_name_;
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using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::getClassName;
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using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::indices_;
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using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::k_;
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using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::search_parameter_;
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using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::search_radius_;
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using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::surface_;
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using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::input_;
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using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::normals_;
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using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::descLength_;
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using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::nr_grid_sector_;
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using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::nr_shape_bins_;
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using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::sqradius_;
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using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::radius3_4_;
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using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::radius1_4_;
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using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::radius1_2_;
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using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::maxAngularSectors_;
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using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::interpolateSingleChannel;
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using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::shot_;
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using FeatureWithLocalReferenceFrames<PointInT, PointRFT>::frames_;
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using PointCloudIn = typename Feature<PointInT, PointOutT>::PointCloudIn;
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/** \brief Empty constructor.
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* \param[in] describe_shape
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* \param[in] describe_color
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*/
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SHOTColorEstimation (bool describe_shape = true,
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bool describe_color = true)
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: SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT> (10),
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b_describe_shape_ (describe_shape),
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b_describe_color_ (describe_color),
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nr_color_bins_ (30)
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{
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feature_name_ = "SHOTColorEstimation";
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};
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/** \brief Empty destructor */
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~SHOTColorEstimation () {}
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/** \brief Estimate the SHOT descriptor for a given point based on its spatial neighborhood of 3D points with normals
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* \param[in] index the index of the point in indices_
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* \param[in] indices the k-neighborhood point indices in surface_
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* \param[in] sqr_dists the k-neighborhood point distances in surface_
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* \param[out] shot the resultant SHOT descriptor representing the feature at the query point
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*/
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void
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computePointSHOT (const int index,
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const pcl::Indices &indices,
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const std::vector<float> &sqr_dists,
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Eigen::VectorXf &shot) override;
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protected:
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/** \brief Estimate the Signatures of Histograms of OrienTations (SHOT) descriptors at a set of points given by
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* <setInputCloud (), setIndices ()> using the surface in setSearchSurface () and the spatial locator in
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* setSearchMethod ()
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* \param output the resultant point cloud model dataset that contains the SHOT feature estimates
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*/
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void
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computeFeature (pcl::PointCloud<PointOutT> &output) override;
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/** \brief Quadrilinear interpolation; used when color and shape descriptions are both activated
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* \param[in] indices the neighborhood point indices
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* \param[in] sqr_dists the neighborhood point distances
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* \param[in] index the index of the point in indices_
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* \param[out] binDistanceShape the resultant distance shape histogram
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* \param[out] binDistanceColor the resultant color shape histogram
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* \param[in] nr_bins_shape the number of bins in the shape histogram
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* \param[in] nr_bins_color the number of bins in the color histogram
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* \param[out] shot the resultant SHOT histogram
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*/
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void
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interpolateDoubleChannel (const pcl::Indices &indices,
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const std::vector<float> &sqr_dists,
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const int index,
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std::vector<double> &binDistanceShape,
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std::vector<double> &binDistanceColor,
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const int nr_bins_shape,
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const int nr_bins_color,
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Eigen::VectorXf &shot);
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/** \brief Compute shape descriptor. */
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bool b_describe_shape_;
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/** \brief Compute color descriptor. */
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bool b_describe_color_;
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/** \brief The number of bins in each color histogram. */
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int nr_color_bins_;
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public:
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/** \brief Converts RGB triplets to CIELab space.
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* \param[in] R the red channel
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* \param[in] G the green channel
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* \param[in] B the blue channel
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* \param[out] L the lightness
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* \param[out] A the first color-opponent dimension
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* \param[out] B2 the second color-opponent dimension
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*/
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static void
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RGB2CIELAB (unsigned char R, unsigned char G, unsigned char B, float &L, float &A, float &B2);
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static std::array<float, 256> sRGB_LUT;
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static std::array<float, 4000> sXYZ_LUT;
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};
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}
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#ifdef PCL_NO_PRECOMPILE
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#include <pcl/features/impl/shot.hpp>
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#endif
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