| OpenCV 3.4.8 Open Source Computer Vision

samples/cpp/tutorial_code/features2D/Homography/decompose_homography.cpp

An example program with homography decomposition.

Check the corresponding tutorial for more details.

#include <iostream>
#include <opencv2/core.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/calib3d.hpp>
using namespace std;
using namespace cv;
namespace
{
enum Pattern { CHESSBOARD, CIRCLES_GRID, ASYMMETRIC_CIRCLES_GRID };
void calcChessboardCorners(Size boardSize, float squareSize, vector<Point3f>& corners, Pattern patternType = CHESSBOARD)
{
corners.resize(0);
switch (patternType) {
case CHESSBOARD:
case CIRCLES_GRID:
for( int i = 0; i < boardSize.height; i++ )
for( int j = 0; j < boardSize.width; j++ )
corners.push_back(Point3f(float(j*squareSize),
float(i*squareSize), 0));
break;
case ASYMMETRIC_CIRCLES_GRID:
for( int i = 0; i < boardSize.height; i++ )
for( int j = 0; j < boardSize.width; j++ )
corners.push_back(Point3f(float((2*j + i % 2)*squareSize),
float(i*squareSize), 0));
break;
default:
CV_Error(Error::StsBadArg, "Unknown pattern type\n");
}
}
Mat computeHomography(const Mat &R_1to2, const Mat &tvec_1to2, const double d_inv, const Mat &normal)
{
Mat homography = R_1to2 + d_inv * tvec_1to2*normal.t();
return homography;
}
void computeC2MC1(const Mat &R1, const Mat &tvec1, const Mat &R2, const Mat &tvec2,
Mat &R_1to2, Mat &tvec_1to2)
{
//c2Mc1 = c2Mo * oMc1 = c2Mo * c1Mo.inv()
R_1to2 = R2 * R1.t();
tvec_1to2 = R2 * (-R1.t()*tvec1) + tvec2;
}
void decomposeHomography(const string &img1Path, const string &img2Path, const Size &patternSize,
const float squareSize, const string &intrinsicsPath)
{
Mat img1 = imread( samples::findFile( img1Path) );
Mat img2 = imread( samples::findFile( img2Path) );
vector<Point2f> corners1, corners2;
bool found1 = findChessboardCorners(img1, patternSize, corners1);
bool found2 = findChessboardCorners(img2, patternSize, corners2);
if (!found1 || !found2)
{
cout << "Error, cannot find the chessboard corners in both images." << endl;
return;
}
vector<Point3f> objectPoints;
calcChessboardCorners(patternSize, squareSize, objectPoints);
FileStorage fs( samples::findFile( intrinsicsPath ), FileStorage::READ);
Mat cameraMatrix, distCoeffs;
fs["camera_matrix"] >> cameraMatrix;
fs["distortion_coefficients"] >> distCoeffs;
Mat rvec1, tvec1;
solvePnP(objectPoints, corners1, cameraMatrix, distCoeffs, rvec1, tvec1);
Mat rvec2, tvec2;
solvePnP(objectPoints, corners2, cameraMatrix, distCoeffs, rvec2, tvec2);
Mat R1, R2;
Rodrigues(rvec1, R1);
Rodrigues(rvec2, R2);
Mat R_1to2, t_1to2;
computeC2MC1(R1, tvec1, R2, tvec2, R_1to2, t_1to2);
Mat rvec_1to2;
Rodrigues(R_1to2, rvec_1to2);
Mat normal = (Mat_<double>(3,1) << 0, 0, 1);
Mat normal1 = R1*normal;
Mat origin(3, 1, CV_64F, Scalar(0));
Mat origin1 = R1*origin + tvec1;
double d_inv1 = 1.0 / normal1.dot(origin1);
Mat homography_euclidean = computeHomography(R_1to2, t_1to2, d_inv1, normal1);
Mat homography = cameraMatrix * homography_euclidean * cameraMatrix.inv();
homography /= homography.at<double>(2,2);
homography_euclidean /= homography_euclidean.at<double>(2,2);
vector<Mat> Rs_decomp, ts_decomp, normals_decomp;
int solutions = decomposeHomographyMat(homography, cameraMatrix, Rs_decomp, ts_decomp, normals_decomp);
cout << "Decompose homography matrix computed from the camera displacement:" << endl << endl;
for (int i = 0; i < solutions; i++)
{
double factor_d1 = 1.0 / d_inv1;
Mat rvec_decomp;
Rodrigues(Rs_decomp[i], rvec_decomp);
cout << "Solution " << i << ":" << endl;
cout << "rvec from homography decomposition: " << rvec_decomp.t() << endl;
cout << "rvec from camera displacement: " << rvec_1to2.t() << endl;
cout << "tvec from homography decomposition: " << ts_decomp[i].t() << " and scaled by d: " << factor_d1 * ts_decomp[i].t() << endl;
cout << "tvec from camera displacement: " << t_1to2.t() << endl;
cout << "plane normal from homography decomposition: " << normals_decomp[i].t() << endl;
cout << "plane normal at camera 1 pose: " << normal1.t() << endl << endl;
}
Mat H = findHomography(corners1, corners2);
solutions = decomposeHomographyMat(H, cameraMatrix, Rs_decomp, ts_decomp, normals_decomp);
cout << "Decompose homography matrix estimated by findHomography():" << endl << endl;
for (int i = 0; i < solutions; i++)
{
double factor_d1 = 1.0 / d_inv1;
Mat rvec_decomp;
Rodrigues(Rs_decomp[i], rvec_decomp);
cout << "Solution " << i << ":" << endl;
cout << "rvec from homography decomposition: " << rvec_decomp.t() << endl;
cout << "rvec from camera displacement: " << rvec_1to2.t() << endl;
cout << "tvec from homography decomposition: " << ts_decomp[i].t() << " and scaled by d: " << factor_d1 * ts_decomp[i].t() << endl;
cout << "tvec from camera displacement: " << t_1to2.t() << endl;
cout << "plane normal from homography decomposition: " << normals_decomp[i].t() << endl;
cout << "plane normal at camera 1 pose: " << normal1.t() << endl << endl;
}
}
const char* params
= "{ help h | | print usage }"
"{ image1 | left02.jpg | path to the source chessboard image }"
"{ image2 | left01.jpg | path to the desired chessboard image }"
"{ intrinsics | left_intrinsics.yml | path to camera intrinsics }"
"{ width bw | 9 | chessboard width }"
"{ height bh | 6 | chessboard height }"
"{ square_size | 0.025 | chessboard square size }";
}
int main(int argc, char *argv[])
{
CommandLineParser parser(argc, argv, params);
if ( parser.has("help") )
{
parser.about( "Code for homography tutorial.\n"
"Example 4: decompose the homography matrix.\n" );
parser.printMessage();
return 0;
}
Size patternSize(parser.get<int>("width"), parser.get<int>("height"));
float squareSize = (float) parser.get<double>("square_size");
decomposeHomography(parser.get<String>("image1"),
parser.get<String>("image2"),
patternSize, squareSize,
parser.get<String>("intrinsics"));
return 0;
}