Added 4PCS for initial pairwise point cloud registration

registration/include/pcl/registration/impl/transformation_estimation_3point.hpp

@@ -0,0 +1,181 @@
+/*
+ * Software License Agreement (BSD License)
+ *
+ *  Point Cloud Library (PCL) - www.pointclouds.org
+ *  Copyright (c) 2014-, 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.
+ *
+ */
+#ifndef PCL_REGISTRATION_IMPL_TRANSFORMATION_ESTIMATION_3POINT_H_
+#define PCL_REGISTRATION_IMPL_TRANSFORMATION_ESTIMATION_3POINT_H_
+
+#include <pcl/common/eigen.h>
+#include <pcl/registration/transformation_estimation_3point.h>
+
+///////////////////////////////////////////////////////////////////////////////////////////
+template <typename PointSource, typename PointTarget, typename Scalar> inline void
+pcl::registration::TransformationEstimation3Point<PointSource, PointTarget, Scalar>::estimateRigidTransformation (
+    const pcl::PointCloud<PointSource> &cloud_src,
+    const pcl::PointCloud<PointTarget> &cloud_tgt,
+    Matrix4 &transformation_matrix) const
+{
+  if (cloud_src.points.size () != 3 || cloud_tgt.points.size () != 3)
+  {
+    PCL_ERROR ("[pcl::TransformationEstimation3Point::estimateRigidTransformation] Number of points in source (%lu) and target (%lu) must be 3!\n", 
+      cloud_src.points.size (), cloud_tgt.points.size ());
+    return;
+  }
+
+  ConstCloudIterator<PointSource> source_it (cloud_src);
+  ConstCloudIterator<PointTarget> target_it (cloud_tgt);
+  estimateRigidTransformation (source_it, target_it, transformation_matrix);
+}
+
+///////////////////////////////////////////////////////////////////////////////////////////
+template <typename PointSource, typename PointTarget, typename Scalar> void
+pcl::registration::TransformationEstimation3Point<PointSource, PointTarget, Scalar>::estimateRigidTransformation (
+    const pcl::PointCloud<PointSource> &cloud_src,
+    const std::vector<int> &indices_src,
+    const pcl::PointCloud<PointTarget> &cloud_tgt,
+    Matrix4 &transformation_matrix) const
+{
+  if (indices_src.size () != 3 || cloud_tgt.points.size () != 3)
+  {
+    PCL_ERROR ("[pcl::TransformationEstimation3Point::estimateRigidTransformation] Number of indices in source (%lu) and points in target (%lu) must be 3!\n", 
+      indices_src.size (), cloud_tgt.points.size ());
+    return;
+  }
+
+  ConstCloudIterator<PointSource> source_it (cloud_src, indices_src);
+  ConstCloudIterator<PointTarget> target_it (cloud_tgt);
+  estimateRigidTransformation (source_it, target_it, transformation_matrix);
+}
+
+///////////////////////////////////////////////////////////////////////////////////////////
+template <typename PointSource, typename PointTarget, typename Scalar> inline void
+pcl::registration::TransformationEstimation3Point<PointSource, PointTarget, Scalar>::estimateRigidTransformation (
+    const pcl::PointCloud<PointSource> &cloud_src,
+    const std::vector<int> &indices_src,
+    const pcl::PointCloud<PointTarget> &cloud_tgt,
+    const std::vector<int> &indices_tgt,
+    Matrix4 &transformation_matrix) const
+{
+  if (indices_src.size () != 3 || indices_tgt.size () != 3)
+  {
+    PCL_ERROR ("[pcl::TransformationEstimation3Point::estimateRigidTransformation] Number of indices in source (%lu) and target (%lu) must be 3!\n", 
+      indices_src.size (), indices_tgt.size ());
+    return;
+  }
+
+  ConstCloudIterator<PointSource> source_it (cloud_src, indices_src);
+  ConstCloudIterator<PointTarget> target_it (cloud_tgt, indices_tgt);
+  estimateRigidTransformation (source_it, target_it, transformation_matrix);
+}
+
+///////////////////////////////////////////////////////////////////////////////////////////
+template <typename PointSource, typename PointTarget, typename Scalar> void
+pcl::registration::TransformationEstimation3Point<PointSource, PointTarget, Scalar>::estimateRigidTransformation (
+    const pcl::PointCloud<PointSource> &cloud_src,
+    const pcl::PointCloud<PointTarget> &cloud_tgt,
+    const pcl::Correspondences &correspondences,
+    Matrix4 &transformation_matrix) const
+{
+  if (correspondences.size () != 3)
+  {
+    PCL_ERROR ("[pcl::TransformationEstimation3Point::estimateRigidTransformation] Number of correspondences (%lu) must be 3!\n", 
+      correspondences.size ());
+    return;
+  }
+
+  ConstCloudIterator<PointSource> source_it (cloud_src, correspondences, true);
+  ConstCloudIterator<PointTarget> target_it (cloud_tgt, correspondences, false);
+  estimateRigidTransformation (source_it, target_it, transformation_matrix);
+}
+
+///////////////////////////////////////////////////////////////////////////////////////////
+template <typename PointSource, typename PointTarget, typename Scalar> inline void
+pcl::registration::TransformationEstimation3Point<PointSource, PointTarget, Scalar>::estimateRigidTransformation (
+    ConstCloudIterator<PointSource>& source_it,
+    ConstCloudIterator<PointTarget>& target_it,
+    Matrix4 &transformation_matrix) const
+{
+  transformation_matrix.setIdentity ();
+  source_it.reset ();
+  target_it.reset ();
+
+  Eigen::Matrix <Scalar, 4, 1> source_mean, target_mean;    
+  pcl::compute3DCentroid (source_it, source_mean);
+  pcl::compute3DCentroid (target_it, target_mean);
+
+  source_it.reset ();
+  target_it.reset ();
+
+  Eigen::Matrix <Scalar, Eigen::Dynamic, Eigen::Dynamic> source_demean, target_demean;
+  pcl::demeanPointCloud (source_it, source_mean, source_demean, 3);
+  pcl::demeanPointCloud (target_it, target_mean, target_demean, 3);
+
+  source_it.reset ();
+  target_it.reset ();
+
+  Eigen::Matrix <Scalar, 3, 1> s1 = source_demean.col (1).head (3) - source_demean.col (0).head (3); 
+  s1.normalize ();
+
+  Eigen::Matrix <Scalar, 3, 1> s2 = source_demean.col (2).head (3) - source_demean.col (0).head (3); 
+  s2 -= s2.dot (s1) * s1;
+  s2.normalize ();
+
+  Eigen::Matrix <Scalar, 3, 3> source_rot;
+  source_rot.col (0) = s1;
+  source_rot.col (1) = s2;
+  source_rot.col (2) = s1.cross (s2);
+
+  Eigen::Matrix <Scalar, 3, 1> t1 = target_demean.col (1).head (3) - target_demean.col (0).head (3); 
+  t1.normalize ();
+
+  Eigen::Matrix <Scalar, 3, 1> t2 = target_demean.col (2).head (3) - target_demean.col (0).head (3); 
+  t2 -= t2.dot (t1) * t1;
+  t2.normalize ();
+
+  Eigen::Matrix <Scalar, 3, 3> target_rot;
+  target_rot.col (0) = t1;
+  target_rot.col (1) = t2;
+  target_rot.col (2) = t1.cross (t2);
+
+  //Eigen::Matrix <Scalar, 3, 3> R = source_rot * target_rot.transpose ();
+  Eigen::Matrix <Scalar, 3, 3> R = target_rot * source_rot.transpose ();
+  transformation_matrix.topLeftCorner (3, 3) = R;
+  //transformation_matrix.block (0, 3, 3, 1) = source_mean.head (3) - R * target_mean.head (3);
+  transformation_matrix.block (0, 3, 3, 1) = target_mean.head (3) - R * source_mean.head (3);
+}
+
+//#define PCL_INSTANTIATE_TransformationEstimation3Point(T,U) template class PCL_EXPORTS pcl::registration::TransformationEstimation3Point<T,U>;
+
+#endif // PCL_REGISTRATION_IMPL_TRANSFORMATION_ESTIMATION_3POINT_H_

registration/include/pcl/registration/matching_candidate.h

@@ -0,0 +1,103 @@
+/*
+ * Software License Agreement (BSD License)
+ *
+ *  Point Cloud Library (PCL) - www.pointclouds.org
+ *  Copyright (c) 2014-, Open Perception, Inc.
+ *  Copyright (C) 2008 Ben Gurion University of the Negev, Beer Sheva, Israel.
+ *
+ *  All rights reserved
+ *
+ *  Redistribution and use in source and binary forms, with or without
+ *  modification, are permitted provided that the following conditions are met
+ *
+ *   * The use for research only (no for any commercial application).
+ *   * 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_REGISTRATION_MATCHING_CANDIDATE_H_
+#define PCL_REGISTRATION_MATCHING_CANDIDATE_H_
+
+#include <pcl/registration/registration.h>
+#include <pcl/common/common.h>
+
+namespace pcl
+{
+  namespace registration
+  {
+    /** \brief Container for matching candidate consisting of
+    *
+    * * fitness score value as a result of the matching algorithm
+    * * correspondences between source and target data set
+    * * transformation matrix calculated based on the correspondences
+    *
+    */
+    struct MatchingCandidate
+    {
+      /** \brief Constructor. */
+      MatchingCandidate () :
+        fitness_score (FLT_MAX),
+        correspondences (),
+        transformation (Eigen::Matrix4f::Identity ())
+      {};
+
+      /** \brief Value constructor. */
+      MatchingCandidate (float s, const pcl::Correspondences &c, const Eigen::Matrix4f &m) :
+        fitness_score (s),
+        correspondences (c),
+        transformation (m)
+      {};
+
+      /** \brief Destructor. */
+      ~MatchingCandidate ()
+      {};
+
+
+      /** \brief Fitness score of current candidate resulting from matching algorithm. */
+      float fitness_score;
+
+      /** \brief Correspondences between source <-> target. */
+      pcl::Correspondences correspondences;
+
+      /** \brief Corresponding transformation matrix retrieved using \a corrs. */
+      Eigen::Matrix4f transformation;
+
+      EIGEN_MAKE_ALIGNED_OPERATOR_NEW
+    };
+
+    /** \brief Sorting of candidates based on fitness score value. */
+    struct by_score
+    {
+      /** \brief Operator used to sort candidates based on fitness score. */
+      bool operator () (MatchingCandidate const &left, MatchingCandidate const &right)
+      {
+        return (left.fitness_score < right.fitness_score);
+      }
+    };
+
+  };  // namespace registration
+}; // namespace pcl
+
+
+#endif // PCL_REGISTRATION_MATCHING_CANDIDATE_H_