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/*
* Software License Agreement (BSD License)
*
* Point Cloud Library (PCL) - www.pointclouds.org
* Copyright (c) 2012, Yani Ioannou <yani.ioannou@gmail.com>
*
* 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.
*
*/
#ifndef PCL_FILTERS_DON_IMPL_H_
#define PCL_FILTERS_DON_IMPL_H_
#include <pcl/features/don.h>
//////////////////////////////////////////////////////////////////////////////////////////////
template <typename PointInT, typename PointNT, typename PointOutT> bool
pcl::DifferenceOfNormalsEstimation<PointInT, PointNT, PointOutT>::initCompute ()
{
// Check if input normals are set
if (!input_normals_small_)
{
PCL_ERROR ("[pcl::%s::initCompute] No input dataset containing small support radius normals was given!\n", getClassName().c_str ());
Feature<PointInT, PointOutT>::deinitCompute();
return (false);
}
if (!input_normals_large_)
{
PCL_ERROR ("[pcl::%s::initCompute] No input dataset containing large support radius normals was given!\n", getClassName().c_str ());
Feature<PointInT, PointOutT>::deinitCompute();
return (false);
}
// Check if the size of normals is the same as the size of the surface
if (input_normals_small_->size () != input_->size ())
{
PCL_ERROR ("[pcl::%s::initCompute] ", getClassName().c_str ());
PCL_ERROR ("The number of points in the input dataset differs from ");
PCL_ERROR ("the number of points in the dataset containing the small support radius normals!\n");
Feature<PointInT, PointOutT>::deinitCompute ();
return (false);
}
if (input_normals_large_->size () != input_->size ())
{
PCL_ERROR ("[pcl::%s::initCompute] ", getClassName().c_str ());
PCL_ERROR ("The number of points in the input dataset differs from ");
PCL_ERROR ("the number of points in the dataset containing the large support radius normals!\n");
Feature<PointInT, PointOutT>::deinitCompute ();
return (false);
}
return (true);
}
//////////////////////////////////////////////////////////////////////////////////////////////
template <typename PointInT, typename PointNT, typename PointOutT> void
pcl::DifferenceOfNormalsEstimation<PointInT, PointNT, PointOutT>::computeFeature (PointCloudOut &output)
{
//perform DoN subtraction and return results
for (std::size_t point_id = 0; point_id < input_->size (); ++point_id)
{
output[point_id].getNormalVector3fMap () = ((*input_normals_small_)[point_id].getNormalVector3fMap ()
- (*input_normals_large_)[point_id].getNormalVector3fMap ()) / 2.0;
if(!std::isfinite (output[point_id].normal_x) ||
!std::isfinite (output[point_id].normal_y) ||
!std::isfinite (output[point_id].normal_z)){
output[point_id].getNormalVector3fMap () = Eigen::Vector3f(0,0,0);
}
output[point_id].curvature = output[point_id].getNormalVector3fMap ().norm();
}
}
#define PCL_INSTANTIATE_DifferenceOfNormalsEstimation(T,NT,OutT) template class PCL_EXPORTS pcl::DifferenceOfNormalsEstimation<T,NT,OutT>;
#endif // PCL_FILTERS_DON_H_