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BoofCV is an open source Java library for real-time computer vision and robotics applications.
/*
* Copyright (c) 2021, Peter Abeles. All Rights Reserved.
*
* This file is part of BoofCV (http://boofcv.org).
*
* 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 boofcv.alg.geo.calibration;
import lombok.Getter;
import org.ejml.data.DMatrixRMaj;
import org.ejml.dense.row.CommonOps_DDRM;
import org.ejml.dense.row.MatrixFeatures_DDRM;
import org.ejml.dense.row.linsol.svd.SolveNullSpaceSvd_DDRM;
import java.util.List;
/**
*
* Estimates camera calibration matrix from a set of homographies using linear algebra. Based upon the
* description found in [1], but has been modified to improve stability and flexibility. Two
* variants are implemented inside this class. One variant assumes that the skew is zero and requires two or
* more homographies and the other variant does not assume the skew is zero and requires three or more
* homographies. The calibration matrix structure is shown below.
*
*
*
* Calibration matrix is defined as follows:
* [ α c u0 ]
* [ 0 β v0 ]
* [ 0 0 1 ]
* where 'c' is the camera's skew.
*
*
*
* The zero skew variant is a modification of what was described in [1]. Instead of simply adding another row
* to force the skew to be zero that entire part of the equation has been omitted. The algorithm described in
* [1] was numerically unstable and did not produce meaningful results.
*
*
*
* [1] Zhengyou Zhang, "Flexible Camera Calibration By Viewing a Plane From Unknown Orientations,",
* International Conference on Computer Vision (ICCV'99), Corfu, Greece, pages 666-673, September 1999.
*
*/
public class Zhang99CalibrationMatrixFromHomographies {
// system of equations
private DMatrixRMaj A = new DMatrixRMaj(1, 1);
private SolveNullSpaceSvd_DDRM solverNull = new SolveNullSpaceSvd_DDRM();
// a vectorized description of the B = A^-T * A^-1 matrix.
private DMatrixRMaj b = new DMatrixRMaj(1, 1);
// the found calibration matrix
private DMatrixRMaj K = new DMatrixRMaj(3, 3);
/** if it should assume the skew is zero or not */
@Getter private boolean assumeZeroSkew;
/**
* Configures calibration estimation.
*
* @param assumeZeroSkew Assume that skew matrix is zero or not
*/
public Zhang99CalibrationMatrixFromHomographies( boolean assumeZeroSkew ) {
setAssumeZeroSkew(assumeZeroSkew);
}
public Zhang99CalibrationMatrixFromHomographies() {}
/**
* Specifies if it should assume skew is zero or not
*
* @param zeroSkew true if skew is zero
*/
public void setAssumeZeroSkew( boolean zeroSkew ) {
this.assumeZeroSkew = zeroSkew;
if (assumeZeroSkew)
b.reshape(5, 1);
else
b.reshape(6, 1);
}
/**
* Given a set of homographies computed from a sequence of images that observe the same
* plane it estimates the camera's calibration.
*
* @param homographies Homographies computed from observations of the calibration grid.
*/
public void process( List homographies ) {
if (assumeZeroSkew) {
if (homographies.size() < 2)
throw new IllegalArgumentException("At least two homographies are required. Found " + homographies.size());
} else if (homographies.size() < 3) {
throw new IllegalArgumentException("At least three homographies are required. Found " + homographies.size());
}
if (assumeZeroSkew) {
setupA_NoSkew(homographies);
if (!solverNull.process(A, 1, b))
throw new RuntimeException("SVD failed");
computeParam_ZeroSkew();
} else {
setupA(homographies);
if (!solverNull.process(A, 1, b))
throw new RuntimeException("SVD failed");
computeParam();
}
if (MatrixFeatures_DDRM.hasUncountable(K)) {
throw new RuntimeException("Failed!");
}
}
/**
* Sets up the system of equations which are to be solved. This equation is derived from
* constraints (3) and (4) in the paper. See section 3.1.
*
* @param homographies set of observed homographies.
*/
private void setupA( List homographies ) {
A.reshape(2*homographies.size(), 6, false);
DMatrixRMaj h1 = new DMatrixRMaj(3, 1);
DMatrixRMaj h2 = new DMatrixRMaj(3, 1);
DMatrixRMaj v12 = new DMatrixRMaj(1, 6);
DMatrixRMaj v11 = new DMatrixRMaj(1, 6);
DMatrixRMaj v22 = new DMatrixRMaj(1, 6);
DMatrixRMaj v11m22 = new DMatrixRMaj(1, 6);
for (int i = 0; i < homographies.size(); i++) {
DMatrixRMaj H = homographies.get(i);
CommonOps_DDRM.extract(H, 0, 3, 0, 1, h1, 0, 0);
CommonOps_DDRM.extract(H, 0, 3, 1, 2, h2, 0, 0);
// normalize H by the max value to reduce numerical error when computing A
// several numbers are multiplied against each other and could become quite large/small
double max1 = CommonOps_DDRM.elementMaxAbs(h1);
double max2 = CommonOps_DDRM.elementMaxAbs(h2);
double max = Math.max(max1, max2);
CommonOps_DDRM.divide(h1, max);
CommonOps_DDRM.divide(h2, max);
// compute elements of A
computeV(h1, h2, v12);
computeV(h1, h1, v11);
computeV(h2, h2, v22);
CommonOps_DDRM.subtract(v11, v22, v11m22);
CommonOps_DDRM.insert(v12, A, i*2, 0);
CommonOps_DDRM.insert(v11m22, A, i*2 + 1, 0);
}
}
/**
* Similar to {@link #setupA(List)} but all references to B12 have been removed
* since it will always be zero when the skew is zero
*
* @param homographies set of observed homographies.
*/
private void setupA_NoSkew( List homographies ) {
A.reshape(2*homographies.size(), 5, false);
DMatrixRMaj h1 = new DMatrixRMaj(3, 1);
DMatrixRMaj h2 = new DMatrixRMaj(3, 1);
DMatrixRMaj v12 = new DMatrixRMaj(1, 5);
DMatrixRMaj v11 = new DMatrixRMaj(1, 5);
DMatrixRMaj v22 = new DMatrixRMaj(1, 5);
DMatrixRMaj v11m22 = new DMatrixRMaj(1, 5);
for (int i = 0; i < homographies.size(); i++) {
DMatrixRMaj H = homographies.get(i);
CommonOps_DDRM.extract(H, 0, 3, 0, 1, h1, 0, 0);
CommonOps_DDRM.extract(H, 0, 3, 1, 2, h2, 0, 0);
// normalize H by the max value to reduce numerical error when computing A
// several numbers are multiplied against each other and could become quite large/small
double max1 = CommonOps_DDRM.elementMaxAbs(h1);
double max2 = CommonOps_DDRM.elementMaxAbs(h2);
double max = Math.max(max1, max2);
CommonOps_DDRM.divide(h1, max);
CommonOps_DDRM.divide(h2, max);
// compute elements of A
computeV_NoSkew(h1, h2, v12);
computeV_NoSkew(h1, h1, v11);
computeV_NoSkew(h2, h2, v22);
CommonOps_DDRM.subtract(v11, v22, v11m22);
CommonOps_DDRM.insert(v12, A, i*2, 0);
CommonOps_DDRM.insert(v11m22, A, i*2 + 1, 0);
}
}
/**
* This computes the v_ij vector found in the paper.
*/
private void computeV( DMatrixRMaj h1, DMatrixRMaj h2, DMatrixRMaj v ) {
double h1x = h1.get(0, 0);
double h1y = h1.get(1, 0);
double h1z = h1.get(2, 0);
double h2x = h2.get(0, 0);
double h2y = h2.get(1, 0);
double h2z = h2.get(2, 0);
v.set(0, 0, h1x*h2x);
v.set(0, 1, h1x*h2y + h1y*h2x);
v.set(0, 2, h1y*h2y);
v.set(0, 3, h1z*h2x + h1x*h2z);
v.set(0, 4, h1z*h2y + h1y*h2z);
v.set(0, 5, h1z*h2z);
}
/**
* This computes the v_ij vector found in the paper. Leaving out components that would
* interact with B12, since that is known to be zero.
*/
private void computeV_NoSkew( DMatrixRMaj h1, DMatrixRMaj h2, DMatrixRMaj v ) {
double h1x = h1.get(0, 0);
double h1y = h1.get(1, 0);
double h1z = h1.get(2, 0);
double h2x = h2.get(0, 0);
double h2y = h2.get(1, 0);
double h2z = h2.get(2, 0);
v.set(0, 0, h1x*h2x);
v.set(0, 1, h1y*h2y);
v.set(0, 2, h1z*h2x + h1x*h2z);
v.set(0, 3, h1z*h2y + h1y*h2z);
v.set(0, 4, h1z*h2z);
}
/**
* Compute the calibration parameters from the b matrix.
*/
private void computeParam() {
// reduce overflow/underflow
CommonOps_DDRM.divide(b, CommonOps_DDRM.elementMaxAbs(b));
double B11 = b.get(0, 0);
double B12 = b.get(1, 0);
double B22 = b.get(2, 0);
double B13 = b.get(3, 0);
double B23 = b.get(4, 0);
double B33 = b.get(5, 0);
double temp0 = B12*B13 - B11*B23;
double temp1 = B11*B22 - B12*B12;
double v0 = temp0/temp1;
double lambda = B33 - (B13*B13 + v0*temp0)/B11;
// Using abs() inside is an adhoc modification to make it more stable
// If there is any good theoretical reason for it, that's a pure accident. Seems
// to work well in practice
double a = Math.sqrt(Math.abs(lambda/B11));
double b = Math.sqrt(Math.abs(lambda*B11/temp1));
double c = -B12*b/B11;
double u0 = c*v0/a - B13/B11;
K.set(0, 0, a);
K.set(0, 1, c);
K.set(0, 2, u0);
K.set(1, 1, b);
K.set(1, 2, v0);
K.set(2, 2, 1);
}
/**
* Compute the calibration parameters from the b matrix when the skew is assumed to be zero
*/
private void computeParam_ZeroSkew() {
// reduce overflow/underflow
CommonOps_DDRM.divide(b, CommonOps_DDRM.elementMaxAbs(b));
double B11 = b.get(0, 0);
double B22 = b.get(1, 0);
double B13 = b.get(2, 0);
double B23 = b.get(3, 0);
double B33 = b.get(4, 0);
double temp0 = -B11*B23;
double temp1 = B11*B22;
double v0 = temp0/temp1;
double lambda = B33 - (B13*B13 + v0*temp0)/B11;
// Using abs() inside is an adhoc modification to make it more stable
// If there is any good theoretical reason for it, that's a pure accident. Seems
// to work well in practice
double a = Math.sqrt(Math.abs(lambda/B11));
double b = Math.sqrt(Math.abs(lambda*B11/temp1));
double u0 = -B13/B11;
K.set(0, 0, a);
K.set(0, 1, 0);
K.set(0, 2, u0);
K.set(1, 1, b);
K.set(1, 2, v0);
K.set(2, 2, 1);
}
/**
* Returns the computed calibration matrix.
*
* @return Calibration matrix.
*/
public DMatrixRMaj getCalibrationMatrix() {
return K;
}
public SolveNullSpaceSvd_DDRM getSolverNull() {
return solverNull;
}
}
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