georegression.fitting.affine.MotionAffinePoint2D_F64 Maven / Gradle / Ivy
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GeoRegression is a free Java based geometry library for scientific computing in fields such as robotics and computer vision with a focus on 2D/3D space.
/*
* Copyright (C) 2011-2017, Peter Abeles. All Rights Reserved.
*
* This file is part of Geometric Regression Library (GeoRegression).
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package georegression.fitting.affine;
import georegression.fitting.MotionTransformPoint;
import georegression.struct.affine.Affine2D_F64;
import georegression.struct.point.Point2D_F64;
import org.ejml.data.DMatrixRMaj;
import org.ejml.dense.row.factory.LinearSolverFactory_DDRM;
import org.ejml.interfaces.linsol.LinearSolverDense;
import java.util.List;
/**
* Finds the best fit model parameters in the least squares sense which can describe the transform
* from the 'fromPts' list to the 'toPts' list.
*
* @author Peter Abeles
*/
public class MotionAffinePoint2D_F64 implements MotionTransformPoint {
private LinearSolverDense solver;
private DMatrixRMaj A;
protected DMatrixRMaj x;
private DMatrixRMaj y;
Affine2D_F64 model = new Affine2D_F64();
public MotionAffinePoint2D_F64() {
solver = LinearSolverFactory_DDRM.leastSquares(100, 2);
x = new DMatrixRMaj( 3, 2 );
A = new DMatrixRMaj( 0, 3 );
y = new DMatrixRMaj( 0, 2 );
}
@Override
public Affine2D_F64 getTransformSrcToDst() {
return model;
}
@Override
public boolean process( List srcPts, List dstPts) {
// grow or shrink the matrix sizes
int N = srcPts.size();
if( N != dstPts.size() ) {
throw new IllegalArgumentException( "From and to lists must be the same size" );
} else if( N < 3 ) {
throw new IllegalArgumentException( "Must be at least 3 points" );
}
if( A.data.length < N * 3 ) {
A.reshape( N, 3, true );
y.reshape( N, 2, true );
for( int i = 0; i < N; i++ ) {
A.set( i, 2, 1 );
}
} else {
A.reshape( N, 3, false );
y.reshape( N, 2, false );
}
// put the data into the matrices
for( int i = 0; i < N; i++ ) {
Point2D_F64 pt2 = srcPts.get( i );
Point2D_F64 pt1 = dstPts.get( i );
A.set( i, 0, pt2.x );
A.set( i, 1, pt2.y );
y.set( i, 0, pt1.x );
y.set( i, 1, pt1.y );
}
// decompose A
if( !solver.setA( A ) )
return false;
// solve
solver.solve( y, x );
// write it into the model
model.a11 = (double) x.data[0];
model.a12 = (double) x.data[2];
model.tx = (double) x.data[4];
model.a21 = (double) x.data[1];
model.a22 = (double) x.data[3];
model.ty = (double) x.data[5];
return true;
}
@Override
public int getMinimumPoints() {
return 3;
}
}