144 lines
5.7 KiB
C
144 lines
5.7 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) 2012, Yani Ioannou <yani.ioannou@gmail.com>
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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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#pragma once
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#include <pcl/features/feature.h>
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namespace pcl
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{
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/** \brief A Difference of Normals (DoN) scale filter implementation for point cloud data.
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*
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* For each point in the point cloud two normals estimated with a differing search radius (sigma_s, sigma_l)
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* are subtracted, the difference of these normals provides a scale-based feature which
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* can be further used to filter the point cloud, somewhat like the Difference of Guassians
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* in image processing, but instead on surfaces. Best results are had when the two search
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* radii are related as sigma_l=10*sigma_s, the octaves between the two search radii
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* can be though of as a filter bandwidth. For appropriate values and thresholds it
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* can be used for surface edge extraction.
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*
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* \attention The input normals given by setInputNormalsSmall and setInputNormalsLarge have
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* to match the input point cloud given by setInputCloud. This behavior is different than
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* feature estimation methods that extend FeatureFromNormals, which match the normals
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* with the search surface.
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*
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* \note For more information please see
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* <b>Yani Ioannou. Automatic Urban Modelling using Mobile Urban LIDAR Data.
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* Thesis (Master, Computing), Queen's University, March, 2010.</b>
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*
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* \author Yani Ioannou.
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* \ingroup features
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*/
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template <typename PointInT, typename PointNT, typename PointOutT>
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class DifferenceOfNormalsEstimation : public Feature<PointInT, PointOutT>
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{
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using Feature<PointInT, PointOutT>::getClassName;
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using Feature<PointInT, PointOutT>::feature_name_;
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using PCLBase<PointInT>::input_;
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using PointCloudN = pcl::PointCloud<PointNT>;
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using PointCloudNPtr = typename PointCloudN::Ptr;
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using PointCloudNConstPtr = typename PointCloudN::ConstPtr;
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using PointCloudOut = typename Feature<PointInT, PointOutT>::PointCloudOut;
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public:
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using Ptr = shared_ptr<DifferenceOfNormalsEstimation<PointInT, PointNT, PointOutT> >;
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using ConstPtr = shared_ptr<const DifferenceOfNormalsEstimation<PointInT, PointNT, PointOutT> >;
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/**
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* Creates a new Difference of Normals filter.
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*/
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DifferenceOfNormalsEstimation ()
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{
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feature_name_ = "DifferenceOfNormalsEstimation";
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}
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~DifferenceOfNormalsEstimation ()
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{
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//
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}
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/**
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* Set the normals calculated using a smaller search radius (scale) for the DoN operator.
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* @param normals the smaller radius (scale) of the DoN filter.
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*/
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inline void
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setNormalScaleSmall (const PointCloudNConstPtr &normals)
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{
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input_normals_small_ = normals;
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}
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/**
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* Set the normals calculated using a larger search radius (scale) for the DoN operator.
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* @param normals the larger radius (scale) of the DoN filter.
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*/
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inline void
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setNormalScaleLarge (const PointCloudNConstPtr &normals)
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{
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input_normals_large_ = normals;
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}
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/**
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* Computes the DoN vector for each point in the input point cloud and outputs the vector cloud to the given output.
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* @param output the cloud to output the DoN vector cloud to.
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*/
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void
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computeFeature (PointCloudOut &output) override;
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/**
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* Initialize for computation of features.
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* @return true if parameters (input normals, input) are sufficient to perform computation.
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*/
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bool
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initCompute () override;
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private:
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/** \brief Make the compute (&PointCloudOut); inaccessible from outside the class
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* \param[out] output the output point cloud
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*/
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void
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compute (PointCloudOut &) {}
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///The smallest radius (scale) used in the DoN filter.
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PointCloudNConstPtr input_normals_small_;
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///The largest radius (scale) used in the DoN filter.
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PointCloudNConstPtr input_normals_large_;
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};
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}
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#ifdef PCL_NO_PRECOMPILE
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#include <pcl/features/impl/don.hpp>
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#endif
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