/* * Software License Agreement (BSD License) * * Point Cloud Library (PCL) - www.pointclouds.org * Copyright (c) 2010-2011, Willow Garage, Inc. * Copyright (c) 2012-, Open Perception, Inc. * * All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions * are met: * * * Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * * Redistributions in binary form must reproduce the above * copyright notice, this list of conditions and the following * disclaimer in the documentation and/or other materials provided * with the distribution. * * Neither the name of the copyright holder(s) nor the names of its * contributors may be used to endorse or promote products derived * from this software without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS * FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE * COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN * ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE * POSSIBILITY OF SUCH DAMAGE. * * $Id$ * */ #pragma once #include #include #include namespace pcl { /** \brief @b SampleConsensusModelCylinder defines a model for 3D cylinder segmentation. * The model coefficients are defined as: * - \b point_on_axis.x : the X coordinate of a point located on the cylinder axis * - \b point_on_axis.y : the Y coordinate of a point located on the cylinder axis * - \b point_on_axis.z : the Z coordinate of a point located on the cylinder axis * - \b axis_direction.x : the X coordinate of the cylinder's axis direction * - \b axis_direction.y : the Y coordinate of the cylinder's axis direction * - \b axis_direction.z : the Z coordinate of the cylinder's axis direction * - \b radius : the cylinder's radius * * \author Radu Bogdan Rusu * \ingroup sample_consensus */ template class SampleConsensusModelCylinder : public SampleConsensusModel, public SampleConsensusModelFromNormals { public: using SampleConsensusModel::model_name_; using SampleConsensusModel::input_; using SampleConsensusModel::indices_; using SampleConsensusModel::radius_min_; using SampleConsensusModel::radius_max_; using SampleConsensusModelFromNormals::normals_; using SampleConsensusModelFromNormals::normal_distance_weight_; using SampleConsensusModel::error_sqr_dists_; using PointCloud = typename SampleConsensusModel::PointCloud; using PointCloudPtr = typename SampleConsensusModel::PointCloudPtr; using PointCloudConstPtr = typename SampleConsensusModel::PointCloudConstPtr; using Ptr = shared_ptr >; using ConstPtr = shared_ptr>; /** \brief Constructor for base SampleConsensusModelCylinder. * \param[in] cloud the input point cloud dataset * \param[in] random if true set the random seed to the current time, else set to 12345 (default: false) */ SampleConsensusModelCylinder (const PointCloudConstPtr &cloud, bool random = false) : SampleConsensusModel (cloud, random) , SampleConsensusModelFromNormals () , axis_ (Eigen::Vector3f::Zero ()) , eps_angle_ (0) { model_name_ = "SampleConsensusModelCylinder"; sample_size_ = 2; model_size_ = 7; } /** \brief Constructor for base SampleConsensusModelCylinder. * \param[in] cloud the input point cloud dataset * \param[in] indices a vector of point indices to be used from \a cloud * \param[in] random if true set the random seed to the current time, else set to 12345 (default: false) */ SampleConsensusModelCylinder (const PointCloudConstPtr &cloud, const Indices &indices, bool random = false) : SampleConsensusModel (cloud, indices, random) , SampleConsensusModelFromNormals () , axis_ (Eigen::Vector3f::Zero ()) , eps_angle_ (0) { model_name_ = "SampleConsensusModelCylinder"; sample_size_ = 2; model_size_ = 7; } /** \brief Copy constructor. * \param[in] source the model to copy into this */ SampleConsensusModelCylinder (const SampleConsensusModelCylinder &source) : SampleConsensusModel (), SampleConsensusModelFromNormals (), axis_ (Eigen::Vector3f::Zero ()), eps_angle_ (0) { *this = source; model_name_ = "SampleConsensusModelCylinder"; } /** \brief Empty destructor */ ~SampleConsensusModelCylinder () {} /** \brief Copy constructor. * \param[in] source the model to copy into this */ inline SampleConsensusModelCylinder& operator = (const SampleConsensusModelCylinder &source) { SampleConsensusModel::operator=(source); SampleConsensusModelFromNormals::operator=(source); axis_ = source.axis_; eps_angle_ = source.eps_angle_; return (*this); } /** \brief Set the angle epsilon (delta) threshold. * \param[in] ea the maximum allowed difference between the cylinder axis and the given axis. */ inline void setEpsAngle (const double ea) { eps_angle_ = ea; } /** \brief Get the angle epsilon (delta) threshold. */ inline double getEpsAngle () const { return (eps_angle_); } /** \brief Set the axis along which we need to search for a cylinder direction. * \param[in] ax the axis along which we need to search for a cylinder direction */ inline void setAxis (const Eigen::Vector3f &ax) { axis_ = ax; } /** \brief Get the axis along which we need to search for a cylinder direction. */ inline Eigen::Vector3f getAxis () const { return (axis_); } /** \brief Check whether the given index samples can form a valid cylinder model, compute the model coefficients * from these samples and store them in model_coefficients. The cylinder coefficients are: point_on_axis, * axis_direction, cylinder_radius_R * \param[in] samples the point indices found as possible good candidates for creating a valid model * \param[out] model_coefficients the resultant model coefficients */ bool computeModelCoefficients (const Indices &samples, Eigen::VectorXf &model_coefficients) const override; /** \brief Compute all distances from the cloud data to a given cylinder model. * \param[in] model_coefficients the coefficients of a cylinder model that we need to compute distances to * \param[out] distances the resultant estimated distances */ void getDistancesToModel (const Eigen::VectorXf &model_coefficients, std::vector &distances) const override; /** \brief Select all the points which respect the given model coefficients as inliers. * \param[in] model_coefficients the coefficients of a cylinder model that we need to compute distances to * \param[in] threshold a maximum admissible distance threshold for determining the inliers from the outliers * \param[out] inliers the resultant model inliers */ void selectWithinDistance (const Eigen::VectorXf &model_coefficients, const double threshold, Indices &inliers) override; /** \brief Count all the points which respect the given model coefficients as inliers. * * \param[in] model_coefficients the coefficients of a model that we need to compute distances to * \param[in] threshold maximum admissible distance threshold for determining the inliers from the outliers * \return the resultant number of inliers */ std::size_t countWithinDistance (const Eigen::VectorXf &model_coefficients, const double threshold) const override; /** \brief Recompute the cylinder coefficients using the given inlier set and return them to the user. * @note: these are the coefficients of the cylinder model after refinement (e.g. after SVD) * \param[in] inliers the data inliers found as supporting the model * \param[in] model_coefficients the initial guess for the optimization * \param[out] optimized_coefficients the resultant recomputed coefficients after non-linear optimization */ void optimizeModelCoefficients (const Indices &inliers, const Eigen::VectorXf &model_coefficients, Eigen::VectorXf &optimized_coefficients) const override; /** \brief Create a new point cloud with inliers projected onto the cylinder model. * \param[in] inliers the data inliers that we want to project on the cylinder model * \param[in] model_coefficients the coefficients of a cylinder model * \param[out] projected_points the resultant projected points * \param[in] copy_data_fields set to true if we need to copy the other data fields */ void projectPoints (const Indices &inliers, const Eigen::VectorXf &model_coefficients, PointCloud &projected_points, bool copy_data_fields = true) const override; /** \brief Verify whether a subset of indices verifies the given cylinder model coefficients. * \param[in] indices the data indices that need to be tested against the cylinder model * \param[in] model_coefficients the cylinder model coefficients * \param[in] threshold a maximum admissible distance threshold for determining the inliers from the outliers */ bool doSamplesVerifyModel (const std::set &indices, const Eigen::VectorXf &model_coefficients, const double threshold) const override; /** \brief Return a unique id for this model (SACMODEL_CYLINDER). */ inline pcl::SacModel getModelType () const override { return (SACMODEL_CYLINDER); } protected: using SampleConsensusModel::sample_size_; using SampleConsensusModel::model_size_; /** \brief Get the distance from a point to a line (represented by a point and a direction) * \param[in] pt a point * \param[in] model_coefficients the line coefficients (a point on the line, line direction) */ double pointToLineDistance (const Eigen::Vector4f &pt, const Eigen::VectorXf &model_coefficients) const; /** \brief Project a point onto a line given by a point and a direction vector * \param[in] pt the input point to project * \param[in] line_pt the point on the line (make sure that line_pt[3] = 0 as there are no internal checks!) * \param[in] line_dir the direction of the line (make sure that line_dir[3] = 0 as there are no internal checks!) * \param[out] pt_proj the resultant projected point */ inline void projectPointToLine (const Eigen::Vector4f &pt, const Eigen::Vector4f &line_pt, const Eigen::Vector4f &line_dir, Eigen::Vector4f &pt_proj) const { float k = (pt.dot (line_dir) - line_pt.dot (line_dir)) / line_dir.dot (line_dir); // Calculate the projection of the point on the line pt_proj = line_pt + k * line_dir; } /** \brief Project a point onto a cylinder given by its model coefficients (point_on_axis, axis_direction, * cylinder_radius_R) * \param[in] pt the input point to project * \param[in] model_coefficients the coefficients of the cylinder (point_on_axis, axis_direction, cylinder_radius_R) * \param[out] pt_proj the resultant projected point */ void projectPointToCylinder (const Eigen::Vector4f &pt, const Eigen::VectorXf &model_coefficients, Eigen::Vector4f &pt_proj) const; /** \brief Check whether a model is valid given the user constraints. * \param[in] model_coefficients the set of model coefficients */ bool isModelValid (const Eigen::VectorXf &model_coefficients) const override; /** \brief Check if a sample of indices results in a good sample of points * indices. Pure virtual. * \param[in] samples the resultant index samples */ bool isSampleGood (const Indices &samples) const override; private: /** \brief The axis along which we need to search for a cylinder direction. */ Eigen::Vector3f axis_; /** \brief The maximum allowed difference between the cylinder direction and the given axis. */ double eps_angle_; /** \brief Functor for the optimization function */ struct OptimizationFunctor : pcl::Functor { /** Functor constructor * \param[in] indices the indices of data points to evaluate * \param[in] estimator pointer to the estimator object */ OptimizationFunctor (const pcl::SampleConsensusModelCylinder *model, const Indices& indices) : pcl::Functor (indices.size ()), model_ (model), indices_ (indices) {} /** Cost function to be minimized * \param[in] x variables array * \param[out] fvec resultant functions evaluations * \return 0 */ int operator() (const Eigen::VectorXf &x, Eigen::VectorXf &fvec) const { Eigen::Vector4f line_pt (x[0], x[1], x[2], 0); Eigen::Vector4f line_dir (x[3], x[4], x[5], 0); for (int i = 0; i < values (); ++i) { // dist = f - r Eigen::Vector4f pt = (*model_->input_)[indices_[i]].getVector4fMap(); pt[3] = 0; fvec[i] = static_cast (pcl::sqrPointToLineDistance (pt, line_pt, line_dir) - x[6]*x[6]); } return (0); } const pcl::SampleConsensusModelCylinder *model_; const Indices &indices_; }; }; } #ifdef PCL_NO_PRECOMPILE #include #endif