161 lines
6.2 KiB
C++
161 lines
6.2 KiB
C++
/*
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* Software License Agreement (BSD License)
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*
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* Copyright (c) 2010, Willow Garage, Inc.
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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/pcl_base.h>
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#include <pcl/pcl_macros.h>
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#include <pcl/search/search.h> // for Search
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namespace pcl
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{
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////////////////////////////////////////////////////////////////////////////////////////////
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/** \brief Obtain the difference between two aligned point clouds as another point cloud, given a distance threshold.
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* \param src the input point cloud source
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* \param threshold the distance threshold (tolerance) for point correspondences. (e.g., check if f a point p1 from
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* src has a correspondence > threshold than a point p2 from tgt)
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* \param tree the spatial locator (e.g., kd-tree) used for nearest neighbors searching built over the target cloud
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* \param output the resultant output point cloud difference
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* \ingroup segmentation
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*/
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template <typename PointT>
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void getPointCloudDifference (
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const pcl::PointCloud<PointT> &src,
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double threshold,
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const typename pcl::search::Search<PointT>::Ptr &tree,
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pcl::PointCloud<PointT> &output);
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////////////////////////////////////////////////////////////////////////////////////////////
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////////////////////////////////////////////////////////////////////////////////////////////
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////////////////////////////////////////////////////////////////////////////////////////////
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/** \brief @b SegmentDifferences obtains the difference between two spatially
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* aligned point clouds and returns the difference between them for a maximum
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* given distance threshold.
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* \author Radu Bogdan Rusu
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* \ingroup segmentation
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*/
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template <typename PointT>
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class SegmentDifferences: public PCLBase<PointT>
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{
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using BasePCLBase = PCLBase<PointT>;
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public:
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using PointCloud = pcl::PointCloud<PointT>;
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using PointCloudPtr = typename PointCloud::Ptr;
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using PointCloudConstPtr = typename PointCloud::ConstPtr;
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using KdTree = pcl::search::Search<PointT>;
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using KdTreePtr = typename KdTree::Ptr;
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using PointIndicesPtr = PointIndices::Ptr;
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using PointIndicesConstPtr = PointIndices::ConstPtr;
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/** \brief Empty constructor. */
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SegmentDifferences () :
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tree_ (), target_ (), distance_threshold_ (0)
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{};
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/** \brief Provide a pointer to the target dataset against which we
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* compare the input cloud given in setInputCloud
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*
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* \param cloud the target PointCloud dataset
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*/
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inline void
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setTargetCloud (const PointCloudConstPtr &cloud) { target_ = cloud; }
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/** \brief Get a pointer to the input target point cloud dataset. */
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inline PointCloudConstPtr const
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getTargetCloud () { return (target_); }
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/** \brief Provide a pointer to the search object.
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* \param tree a pointer to the spatial search object.
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*/
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inline void
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setSearchMethod (const KdTreePtr &tree) { tree_ = tree; }
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/** \brief Get a pointer to the search method used. */
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inline KdTreePtr
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getSearchMethod () { return (tree_); }
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/** \brief Set the maximum distance tolerance (squared) between corresponding
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* points in the two input datasets.
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*
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* \param sqr_threshold the squared distance tolerance as a measure in L2 Euclidean space
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*/
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inline void
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setDistanceThreshold (double sqr_threshold) { distance_threshold_ = sqr_threshold; }
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/** \brief Get the squared distance tolerance between corresponding points as a
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* measure in the L2 Euclidean space.
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*/
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inline double
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getDistanceThreshold () { return (distance_threshold_); }
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/** \brief Segment differences between two input point clouds.
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* \param output the resultant difference between the two point clouds as a PointCloud
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*/
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void
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segment (PointCloud &output);
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protected:
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// Members derived from the base class
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using BasePCLBase::input_;
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using BasePCLBase::indices_;
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using BasePCLBase::initCompute;
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using BasePCLBase::deinitCompute;
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/** \brief A pointer to the spatial search object. */
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KdTreePtr tree_;
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/** \brief The input target point cloud dataset. */
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PointCloudConstPtr target_;
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/** \brief The distance tolerance (squared) as a measure in the L2
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* Euclidean space between corresponding points.
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*/
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double distance_threshold_;
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/** \brief Class getName method. */
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virtual std::string
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getClassName () const { return ("SegmentDifferences"); }
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};
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}
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#ifdef PCL_NO_PRECOMPILE
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#include <pcl/segmentation/impl/segment_differences.hpp>
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#endif
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