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/*
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* SimilarityTransform.cpp
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*
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* Copyright (c) 2014-2022 SEACAVE
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*
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* Author(s):
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*
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* cDc <cdc.seacave@gmail.com>
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*
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*
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* This program is free software: you can redistribute it and/or modify
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* it under the terms of the GNU Affero General Public License as published by
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* the Free Software Foundation, either version 3 of the License, or
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* (at your option) any later version.
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*
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* This program is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU Affero General Public License for more details.
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*
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* You should have received a copy of the GNU Affero General Public License
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* along with this program. If not, see <http://www.gnu.org/licenses/>.
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*
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*
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* Additional Terms:
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*
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* You are required to preserve legal notices and author attributions in
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* that material or in the Appropriate Legal Notices displayed by works
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* containing it.
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*/
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#include "Common.h"
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#include "SimilarityTransform.h"
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// D E F I N E S ///////////////////////////////////////////////////
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// S T R U C T S ///////////////////////////////////////////////////
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// find the similarity transform that best aligns the given two sets of corresponding 3D points
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bool SEACAVE::SimilarityTransform(const CLISTDEF0(Point3)& points, const CLISTDEF0(Point3)& pointsRef, Matrix4x4& transform)
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{
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ASSERT(points.size() == pointsRef.size());
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typedef Eigen::Matrix<REAL,3,Eigen::Dynamic> PointsVec;
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PointsVec p(3, points.size());
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PointsVec pRef(3, pointsRef.size());
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FOREACH(i, points) {
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p.col(i) = static_cast<const Point3::EVec&>(points[i]);
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pRef.col(i) = static_cast<const Point3::EVec&>(pointsRef[i]);
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}
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transform = Eigen::umeyama(p, pRef);
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return true;
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} // SimilarityTransform
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/*----------------------------------------------------------------*/
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void SEACAVE::DecomposeSimilarityTransform(const Matrix4x4& transform, Matrix3x3& R, Point3& t, REAL& s)
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{
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const Eigen::Transform<REAL,3,Eigen::Affine,Eigen::RowMajor> T(static_cast<const Matrix4x4::EMat&>(transform));
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Eigen::Matrix<REAL,3,3> rotation, scaling;
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T.computeRotationScaling(&rotation, &scaling);
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R = rotation;
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t = T.translation();
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s = scaling.diagonal().mean();
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} // DecomposeSimilarityTransform
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/*----------------------------------------------------------------*/
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