117 lines
3.8 KiB
C++
117 lines
3.8 KiB
C++
/*
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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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*
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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/common/gaussian.h>
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namespace pcl
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{
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template <typename PointT> void
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GaussianKernel::convolveRows(const pcl::PointCloud<PointT> &input,
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std::function <float (const PointT& p)> field_accessor,
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const Eigen::VectorXf& kernel,
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pcl::PointCloud<float> &output) const
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{
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assert(kernel.size () % 2 == 1);
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int kernel_width = kernel.size () -1;
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int radius = kernel.size () / 2.0;
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if(output.height < input.height || output.width < input.width)
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{
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output.width = input.width;
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output.height = input.height;
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output.resize (input.height * input.width);
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}
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int i;
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for(int j = 0; j < input.height; j++)
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{
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for (i = 0 ; i < radius ; i++)
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output (i,j) = 0;
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for ( ; i < input.width - radius ; i++) {
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output (i,j) = 0;
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for (int k = kernel_width, l = i - radius; k >= 0 ; k--, l++)
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output (i,j) += field_accessor (input (l,j)) * kernel[k];
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}
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for ( ; i < input.width ; i++)
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output (i,j) = 0;
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}
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}
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template <typename PointT> void
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GaussianKernel::convolveCols(const pcl::PointCloud<PointT> &input,
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std::function <float (const PointT& p)> field_accessor,
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const Eigen::VectorXf& kernel,
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pcl::PointCloud<float> &output) const
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{
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assert(kernel.size () % 2 == 1);
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int kernel_width = kernel.size () -1;
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int radius = kernel.size () / 2.0;
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if(output.height < input.height || output.width < input.width)
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{
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output.width = input.width;
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output.height = input.height;
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output.resize (input.height * input.width);
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}
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int j;
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for(int i = 0; i < input.width; i++)
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{
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for (j = 0 ; j < radius ; j++)
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output (i,j) = 0;
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for ( ; j < input.height - radius ; j++) {
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output (i,j) = 0;
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for (int k = kernel_width, l = j - radius ; k >= 0 ; k--, l++)
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{
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output (i,j) += field_accessor (input (i,l)) * kernel[k];
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}
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}
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for ( ; j < input.height ; j++)
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output (i,j) = 0;
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}
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}
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} // namespace pcl
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