340 lines
15 KiB
C
340 lines
15 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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* $Id$
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*
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*/
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#pragma once
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#include <pcl/sample_consensus/sac_model.h>
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#include <pcl/sample_consensus/model_types.h>
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#include <pcl/common/distances.h>
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namespace pcl
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{
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/** \brief @b SampleConsensusModelCylinder defines a model for 3D cylinder segmentation.
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* The model coefficients are defined as:
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* - \b point_on_axis.x : the X coordinate of a point located on the cylinder axis
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* - \b point_on_axis.y : the Y coordinate of a point located on the cylinder axis
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* - \b point_on_axis.z : the Z coordinate of a point located on the cylinder axis
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* - \b axis_direction.x : the X coordinate of the cylinder's axis direction
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* - \b axis_direction.y : the Y coordinate of the cylinder's axis direction
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* - \b axis_direction.z : the Z coordinate of the cylinder's axis direction
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* - \b radius : the cylinder's radius
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*
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* \author Radu Bogdan Rusu
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* \ingroup sample_consensus
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*/
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template <typename PointT, typename PointNT>
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class SampleConsensusModelCylinder : public SampleConsensusModel<PointT>, public SampleConsensusModelFromNormals<PointT, PointNT>
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{
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public:
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using SampleConsensusModel<PointT>::model_name_;
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using SampleConsensusModel<PointT>::input_;
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using SampleConsensusModel<PointT>::indices_;
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using SampleConsensusModel<PointT>::radius_min_;
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using SampleConsensusModel<PointT>::radius_max_;
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using SampleConsensusModelFromNormals<PointT, PointNT>::normals_;
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using SampleConsensusModelFromNormals<PointT, PointNT>::normal_distance_weight_;
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using SampleConsensusModel<PointT>::error_sqr_dists_;
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using PointCloud = typename SampleConsensusModel<PointT>::PointCloud;
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using PointCloudPtr = typename SampleConsensusModel<PointT>::PointCloudPtr;
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using PointCloudConstPtr = typename SampleConsensusModel<PointT>::PointCloudConstPtr;
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using Ptr = shared_ptr<SampleConsensusModelCylinder<PointT, PointNT> >;
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using ConstPtr = shared_ptr<const SampleConsensusModelCylinder<PointT, PointNT>>;
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/** \brief Constructor for base SampleConsensusModelCylinder.
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* \param[in] cloud the input point cloud dataset
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* \param[in] random if true set the random seed to the current time, else set to 12345 (default: false)
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*/
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SampleConsensusModelCylinder (const PointCloudConstPtr &cloud, bool random = false)
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: SampleConsensusModel<PointT> (cloud, random)
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, SampleConsensusModelFromNormals<PointT, PointNT> ()
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, axis_ (Eigen::Vector3f::Zero ())
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, eps_angle_ (0)
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{
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model_name_ = "SampleConsensusModelCylinder";
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sample_size_ = 2;
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model_size_ = 7;
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}
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/** \brief Constructor for base SampleConsensusModelCylinder.
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* \param[in] cloud the input point cloud dataset
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* \param[in] indices a vector of point indices to be used from \a cloud
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* \param[in] random if true set the random seed to the current time, else set to 12345 (default: false)
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*/
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SampleConsensusModelCylinder (const PointCloudConstPtr &cloud,
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const Indices &indices,
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bool random = false)
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: SampleConsensusModel<PointT> (cloud, indices, random)
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, SampleConsensusModelFromNormals<PointT, PointNT> ()
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, axis_ (Eigen::Vector3f::Zero ())
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, eps_angle_ (0)
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{
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model_name_ = "SampleConsensusModelCylinder";
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sample_size_ = 2;
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model_size_ = 7;
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}
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/** \brief Copy constructor.
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* \param[in] source the model to copy into this
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*/
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SampleConsensusModelCylinder (const SampleConsensusModelCylinder &source) :
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SampleConsensusModel<PointT> (),
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SampleConsensusModelFromNormals<PointT, PointNT> (),
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axis_ (Eigen::Vector3f::Zero ()),
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eps_angle_ (0)
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{
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*this = source;
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model_name_ = "SampleConsensusModelCylinder";
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}
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/** \brief Empty destructor */
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~SampleConsensusModelCylinder () {}
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/** \brief Copy constructor.
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* \param[in] source the model to copy into this
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*/
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inline SampleConsensusModelCylinder&
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operator = (const SampleConsensusModelCylinder &source)
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{
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SampleConsensusModel<PointT>::operator=(source);
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SampleConsensusModelFromNormals<PointT, PointNT>::operator=(source);
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axis_ = source.axis_;
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eps_angle_ = source.eps_angle_;
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return (*this);
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}
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/** \brief Set the angle epsilon (delta) threshold.
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* \param[in] ea the maximum allowed difference between the cylinder axis and the given axis.
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*/
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inline void
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setEpsAngle (const double ea) { eps_angle_ = ea; }
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/** \brief Get the angle epsilon (delta) threshold. */
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inline double
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getEpsAngle () const { return (eps_angle_); }
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/** \brief Set the axis along which we need to search for a cylinder direction.
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* \param[in] ax the axis along which we need to search for a cylinder direction
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*/
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inline void
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setAxis (const Eigen::Vector3f &ax) { axis_ = ax; }
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/** \brief Get the axis along which we need to search for a cylinder direction. */
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inline Eigen::Vector3f
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getAxis () const { return (axis_); }
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/** \brief Check whether the given index samples can form a valid cylinder model, compute the model coefficients
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* from these samples and store them in model_coefficients. The cylinder coefficients are: point_on_axis,
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* axis_direction, cylinder_radius_R
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* \param[in] samples the point indices found as possible good candidates for creating a valid model
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* \param[out] model_coefficients the resultant model coefficients
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*/
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bool
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computeModelCoefficients (const Indices &samples,
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Eigen::VectorXf &model_coefficients) const override;
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/** \brief Compute all distances from the cloud data to a given cylinder model.
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* \param[in] model_coefficients the coefficients of a cylinder model that we need to compute distances to
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* \param[out] distances the resultant estimated distances
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*/
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void
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getDistancesToModel (const Eigen::VectorXf &model_coefficients,
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std::vector<double> &distances) const override;
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/** \brief Select all the points which respect the given model coefficients as inliers.
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* \param[in] model_coefficients the coefficients of a cylinder model that we need to compute distances to
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* \param[in] threshold a maximum admissible distance threshold for determining the inliers from the outliers
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* \param[out] inliers the resultant model inliers
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*/
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void
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selectWithinDistance (const Eigen::VectorXf &model_coefficients,
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const double threshold,
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Indices &inliers) override;
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/** \brief Count all the points which respect the given model coefficients as inliers.
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*
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* \param[in] model_coefficients the coefficients of a model that we need to compute distances to
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* \param[in] threshold maximum admissible distance threshold for determining the inliers from the outliers
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* \return the resultant number of inliers
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*/
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std::size_t
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countWithinDistance (const Eigen::VectorXf &model_coefficients,
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const double threshold) const override;
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/** \brief Recompute the cylinder coefficients using the given inlier set and return them to the user.
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* @note: these are the coefficients of the cylinder model after refinement (e.g. after SVD)
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* \param[in] inliers the data inliers found as supporting the model
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* \param[in] model_coefficients the initial guess for the optimization
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* \param[out] optimized_coefficients the resultant recomputed coefficients after non-linear optimization
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*/
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void
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optimizeModelCoefficients (const Indices &inliers,
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const Eigen::VectorXf &model_coefficients,
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Eigen::VectorXf &optimized_coefficients) const override;
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/** \brief Create a new point cloud with inliers projected onto the cylinder model.
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* \param[in] inliers the data inliers that we want to project on the cylinder model
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* \param[in] model_coefficients the coefficients of a cylinder model
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* \param[out] projected_points the resultant projected points
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* \param[in] copy_data_fields set to true if we need to copy the other data fields
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*/
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void
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projectPoints (const Indices &inliers,
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const Eigen::VectorXf &model_coefficients,
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PointCloud &projected_points,
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bool copy_data_fields = true) const override;
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/** \brief Verify whether a subset of indices verifies the given cylinder model coefficients.
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* \param[in] indices the data indices that need to be tested against the cylinder model
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* \param[in] model_coefficients the cylinder model coefficients
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* \param[in] threshold a maximum admissible distance threshold for determining the inliers from the outliers
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*/
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bool
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doSamplesVerifyModel (const std::set<index_t> &indices,
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const Eigen::VectorXf &model_coefficients,
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const double threshold) const override;
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/** \brief Return a unique id for this model (SACMODEL_CYLINDER). */
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inline pcl::SacModel
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getModelType () const override { return (SACMODEL_CYLINDER); }
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protected:
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using SampleConsensusModel<PointT>::sample_size_;
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using SampleConsensusModel<PointT>::model_size_;
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/** \brief Get the distance from a point to a line (represented by a point and a direction)
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* \param[in] pt a point
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* \param[in] model_coefficients the line coefficients (a point on the line, line direction)
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*/
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double
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pointToLineDistance (const Eigen::Vector4f &pt, const Eigen::VectorXf &model_coefficients) const;
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/** \brief Project a point onto a line given by a point and a direction vector
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* \param[in] pt the input point to project
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* \param[in] line_pt the point on the line (make sure that line_pt[3] = 0 as there are no internal checks!)
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* \param[in] line_dir the direction of the line (make sure that line_dir[3] = 0 as there are no internal checks!)
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* \param[out] pt_proj the resultant projected point
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*/
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inline void
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projectPointToLine (const Eigen::Vector4f &pt,
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const Eigen::Vector4f &line_pt,
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const Eigen::Vector4f &line_dir,
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Eigen::Vector4f &pt_proj) const
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{
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float k = (pt.dot (line_dir) - line_pt.dot (line_dir)) / line_dir.dot (line_dir);
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// Calculate the projection of the point on the line
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pt_proj = line_pt + k * line_dir;
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}
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/** \brief Project a point onto a cylinder given by its model coefficients (point_on_axis, axis_direction,
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* cylinder_radius_R)
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* \param[in] pt the input point to project
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* \param[in] model_coefficients the coefficients of the cylinder (point_on_axis, axis_direction, cylinder_radius_R)
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* \param[out] pt_proj the resultant projected point
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*/
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void
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projectPointToCylinder (const Eigen::Vector4f &pt,
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const Eigen::VectorXf &model_coefficients,
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Eigen::Vector4f &pt_proj) const;
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/** \brief Check whether a model is valid given the user constraints.
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* \param[in] model_coefficients the set of model coefficients
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*/
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bool
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isModelValid (const Eigen::VectorXf &model_coefficients) const override;
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/** \brief Check if a sample of indices results in a good sample of points
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* indices. Pure virtual.
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* \param[in] samples the resultant index samples
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*/
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bool
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isSampleGood (const Indices &samples) const override;
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private:
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/** \brief The axis along which we need to search for a cylinder direction. */
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Eigen::Vector3f axis_;
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/** \brief The maximum allowed difference between the cylinder direction and the given axis. */
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double eps_angle_;
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/** \brief Functor for the optimization function */
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struct OptimizationFunctor : pcl::Functor<float>
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{
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/** Functor constructor
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* \param[in] indices the indices of data points to evaluate
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* \param[in] estimator pointer to the estimator object
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*/
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OptimizationFunctor (const pcl::SampleConsensusModelCylinder<PointT, PointNT> *model, const Indices& indices) :
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pcl::Functor<float> (indices.size ()), model_ (model), indices_ (indices) {}
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/** Cost function to be minimized
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* \param[in] x variables array
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* \param[out] fvec resultant functions evaluations
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* \return 0
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*/
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int
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operator() (const Eigen::VectorXf &x, Eigen::VectorXf &fvec) const
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{
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Eigen::Vector4f line_pt (x[0], x[1], x[2], 0);
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Eigen::Vector4f line_dir (x[3], x[4], x[5], 0);
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for (int i = 0; i < values (); ++i)
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{
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// dist = f - r
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Eigen::Vector4f pt = (*model_->input_)[indices_[i]].getVector4fMap();
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pt[3] = 0;
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fvec[i] = static_cast<float> (pcl::sqrPointToLineDistance (pt, line_pt, line_dir) - x[6]*x[6]);
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}
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return (0);
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}
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const pcl::SampleConsensusModelCylinder<PointT, PointNT> *model_;
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const Indices &indices_;
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};
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};
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}
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#ifdef PCL_NO_PRECOMPILE
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#include <pcl/sample_consensus/impl/sac_model_cylinder.hpp>
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#endif
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