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|
| | #define TEST_NAME "base/essential_matrix" |
| | #include "util/testing.h" |
| |
|
| | #include <Eigen/Geometry> |
| |
|
| | #include "base/essential_matrix.h" |
| | #include "base/pose.h" |
| | #include "base/projection.h" |
| |
|
| | using namespace colmap; |
| |
|
| | BOOST_AUTO_TEST_CASE(TestDecomposeEssentialMatrix) { |
| | const Eigen::Matrix3d R = EulerAnglesToRotationMatrix(0, 1, 1); |
| | const Eigen::Vector3d t = Eigen::Vector3d(0.5, 1, 1).normalized(); |
| | const Eigen::Matrix3d E = EssentialMatrixFromPose(R, t); |
| |
|
| | Eigen::Matrix3d R1; |
| | Eigen::Matrix3d R2; |
| | Eigen::Vector3d tt; |
| | DecomposeEssentialMatrix(E, &R1, &R2, &tt); |
| |
|
| | BOOST_CHECK((R1 - R).norm() < 1e-10 || (R2 - R).norm() < 1e-10); |
| | BOOST_CHECK((tt - t).norm() < 1e-10 || (tt + t).norm() < 1e-10); |
| | } |
| |
|
| | BOOST_AUTO_TEST_CASE(TestEssentialMatrixFromPose) { |
| | BOOST_CHECK_EQUAL( |
| | EssentialMatrixFromPose(EulerAnglesToRotationMatrix(0, 0, 0), |
| | Eigen::Vector3d(0, 0, 1)), |
| | (Eigen::MatrixXd(3, 3) << 0, -1, 0, 1, 0, 0, 0, 0, 0).finished()); |
| | BOOST_CHECK_EQUAL( |
| | EssentialMatrixFromPose(EulerAnglesToRotationMatrix(0, 0, 0), |
| | Eigen::Vector3d(0, 0, 2)), |
| | (Eigen::MatrixXd(3, 3) << 0, -1, 0, 1, 0, 0, 0, 0, 0).finished()); |
| | } |
| |
|
| | BOOST_AUTO_TEST_CASE(TestEssentialMatrixFromPoses) { |
| | const Eigen::Matrix3d R1 = EulerAnglesToRotationMatrix(0, 0, 0); |
| | const Eigen::Matrix3d R2 = EulerAnglesToRotationMatrix(0, 1, 2); |
| | const Eigen::Vector3d t1(0, 0, 0); |
| | const Eigen::Vector3d t2 = Eigen::Vector3d(0.5, 1, 1).normalized(); |
| |
|
| | const Eigen::Matrix3d E1 = EssentialMatrixFromPose(R2, t2); |
| | const Eigen::Matrix3d E2 = EssentialMatrixFromAbsolutePoses( |
| | ComposeProjectionMatrix(R1, t1), ComposeProjectionMatrix(R2, t2)); |
| |
|
| | BOOST_CHECK_CLOSE((E1 - E2).norm(), 0, 1e-6); |
| | } |
| |
|
| | BOOST_AUTO_TEST_CASE(TestPoseFromEssentialMatrix) { |
| | const Eigen::Matrix3d R = EulerAnglesToRotationMatrix(0, 0, 0); |
| | const Eigen::Vector3d t = Eigen::Vector3d(1, 0, 0).normalized(); |
| | const Eigen::Matrix3d E = EssentialMatrixFromPose(R, t); |
| |
|
| | const Eigen::Matrix3x4d proj_matrix1 = Eigen::Matrix3x4d::Identity(); |
| | const Eigen::Matrix3x4d proj_matrix2 = ComposeProjectionMatrix(R, t); |
| |
|
| | std::vector<Eigen::Vector3d> points3D(4); |
| | points3D[0] = Eigen::Vector3d(0, 0, 1); |
| | points3D[1] = Eigen::Vector3d(0, 0.1, 1); |
| | points3D[2] = Eigen::Vector3d(0.1, 0, 1); |
| | points3D[3] = Eigen::Vector3d(0.1, 0.1, 1); |
| |
|
| | std::vector<Eigen::Vector2d> points1(4); |
| | std::vector<Eigen::Vector2d> points2(4); |
| | for (size_t i = 0; i < points3D.size(); ++i) { |
| | const Eigen::Vector3d point1 = proj_matrix1 * points3D[i].homogeneous(); |
| | points1[i] = point1.hnormalized(); |
| | const Eigen::Vector3d point2 = proj_matrix2 * points3D[i].homogeneous(); |
| | points2[i] = point2.hnormalized(); |
| | } |
| |
|
| | points3D.clear(); |
| |
|
| | Eigen::Matrix3d RR; |
| | Eigen::Vector3d tt; |
| | PoseFromEssentialMatrix(E, points1, points2, &RR, &tt, &points3D); |
| |
|
| | BOOST_CHECK_EQUAL(points3D.size(), 4); |
| |
|
| | BOOST_CHECK(RR.isApprox(R)); |
| | BOOST_CHECK(tt.isApprox(t)); |
| | } |
| |
|
| | BOOST_AUTO_TEST_CASE(TestFindOptimalImageObservations) { |
| | const Eigen::Matrix3d R = EulerAnglesToRotationMatrix(0, 0, 0); |
| | const Eigen::Vector3d t = Eigen::Vector3d(1, 0, 0).normalized(); |
| | const Eigen::Matrix3d E = EssentialMatrixFromPose(R, t); |
| |
|
| | const Eigen::Matrix3x4d proj_matrix1 = Eigen::Matrix3x4d::Identity(); |
| | const Eigen::Matrix3x4d proj_matrix2 = ComposeProjectionMatrix(R, t); |
| |
|
| | std::vector<Eigen::Vector3d> points3D(4); |
| | points3D[0] = Eigen::Vector3d(0, 0, 1); |
| | points3D[1] = Eigen::Vector3d(0, 0.1, 1); |
| | points3D[2] = Eigen::Vector3d(0.1, 0, 1); |
| | points3D[3] = Eigen::Vector3d(0.1, 0.1, 1); |
| |
|
| | |
| | for (size_t i = 0; i < points3D.size(); ++i) { |
| | const Eigen::Vector3d point1_homogeneous = |
| | proj_matrix1 * points3D[i].homogeneous(); |
| | const Eigen::Vector2d point1 = point1_homogeneous.hnormalized(); |
| | const Eigen::Vector3d point2_homogeneous = |
| | proj_matrix2 * points3D[i].homogeneous(); |
| | const Eigen::Vector2d point2 = point2_homogeneous.hnormalized(); |
| | Eigen::Vector2d optimal_point1; |
| | Eigen::Vector2d optimal_point2; |
| | FindOptimalImageObservations(E, point1, point2, &optimal_point1, |
| | &optimal_point2); |
| | BOOST_CHECK(point1.isApprox(optimal_point1)); |
| | BOOST_CHECK(point2.isApprox(optimal_point2)); |
| | } |
| | } |
| |
|
| | BOOST_AUTO_TEST_CASE(TestEpipoleFromEssentialMatrix) { |
| | const Eigen::Matrix3d R = EulerAnglesToRotationMatrix(0, 0, 0); |
| | const Eigen::Vector3d t = Eigen::Vector3d(0, 0, -1).normalized(); |
| | const Eigen::Matrix3d E = EssentialMatrixFromPose(R, t); |
| |
|
| | const Eigen::Vector3d left_epipole = EpipoleFromEssentialMatrix(E, true); |
| | const Eigen::Vector3d right_epipole = EpipoleFromEssentialMatrix(E, false); |
| | BOOST_CHECK(left_epipole.isApprox(Eigen::Vector3d(0, 0, 1))); |
| | BOOST_CHECK(right_epipole.isApprox(Eigen::Vector3d(0, 0, 1))); |
| | } |
| |
|
| | BOOST_AUTO_TEST_CASE(TestInvertEssentialMatrix) { |
| | for (size_t i = 1; i < 10; ++i) { |
| | const Eigen::Matrix3d R = EulerAnglesToRotationMatrix(0, 0.1, 0); |
| | const Eigen::Vector3d t = Eigen::Vector3d(0, 0, i).normalized(); |
| | const Eigen::Matrix3d E = EssentialMatrixFromPose(R, t); |
| | const Eigen::Matrix3d inv_inv_E = |
| | InvertEssentialMatrix(InvertEssentialMatrix(E)); |
| | BOOST_CHECK(E.isApprox(inv_inv_E)); |
| | } |
| | } |
| |
|
| | BOOST_AUTO_TEST_CASE(TestRefineEssentialMatrix) { |
| | const Eigen::Matrix3d R = EulerAnglesToRotationMatrix(0, 0, 0); |
| | const Eigen::Vector3d t = Eigen::Vector3d(1, 0, 0).normalized(); |
| | const Eigen::Matrix3d E = EssentialMatrixFromPose(R, t); |
| |
|
| | const Eigen::Matrix3x4d proj_matrix1 = Eigen::Matrix3x4d::Identity(); |
| | const Eigen::Matrix3x4d proj_matrix2 = ComposeProjectionMatrix(R, t); |
| |
|
| | std::vector<Eigen::Vector3d> points3D(150); |
| | for (size_t i = 0; i < points3D.size() / 3; ++i) { |
| | points3D[3 * i + 0] = Eigen::Vector3d(i * 0.01, 0, 1); |
| | points3D[3 * i + 1] = Eigen::Vector3d(0, i * 0.01, 1); |
| | points3D[3 * i + 2] = Eigen::Vector3d(i * 0.01, i * 0.01, 1); |
| | } |
| |
|
| | std::vector<Eigen::Vector2d> points1(points3D.size()); |
| | std::vector<Eigen::Vector2d> points2(points3D.size()); |
| | for (size_t i = 0; i < points3D.size(); ++i) { |
| | const Eigen::Vector3d point1 = proj_matrix1 * points3D[i].homogeneous(); |
| | points1[i] = point1.hnormalized(); |
| | const Eigen::Vector3d point2 = proj_matrix2 * points3D[i].homogeneous(); |
| | points2[i] = point2.hnormalized(); |
| | } |
| |
|
| | const Eigen::Matrix3d R_pertubated = EulerAnglesToRotationMatrix(0, 0, 0); |
| | const Eigen::Vector3d t_pertubated = |
| | Eigen::Vector3d(1.02, 0.02, 0.02).normalized(); |
| | const Eigen::Matrix3d E_pertubated = |
| | EssentialMatrixFromPose(R_pertubated, t_pertubated); |
| |
|
| | Eigen::Matrix3d E_refined = E_pertubated; |
| | ceres::Solver::Options options; |
| | RefineEssentialMatrix(options, points1, points2, |
| | std::vector<char>(points1.size(), true), &E_refined); |
| |
|
| | BOOST_CHECK_LE((E - E_refined).norm(), (E - E_pertubated).norm()); |
| | } |
| |
|