| // Copyright (c) 2022, ETH Zurich and UNC Chapel Hill. | |
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| // Author: Johannes L. Schoenberger (jsch-at-demuc-dot-de) | |
| namespace colmap { | |
| // Decompose an homography matrix into the possible rotations, translations, | |
| // and plane normal vectors, according to: | |
| // | |
| // Malis, Ezio, and Manuel Vargas. "Deeper understanding of the homography | |
| // decomposition for vision-based control." (2007): 90. | |
| // | |
| // The first pose is assumed to be P = [I | 0]. Note that the homography is | |
| // plane-induced if `R.size() == t.size() == n.size() == 4`. If `R.size() == | |
| // t.size() == n.size() == 1` the homography is pure-rotational. | |
| // | |
| // @param H 3x3 homography matrix. | |
| // @param K 3x3 calibration matrix. | |
| // @param R Possible 3x3 rotation matrices. | |
| // @param t Possible translation vectors. | |
| // @param n Possible normal vectors. | |
| void DecomposeHomographyMatrix(const Eigen::Matrix3d& H, | |
| const Eigen::Matrix3d& K1, | |
| const Eigen::Matrix3d& K2, | |
| std::vector<Eigen::Matrix3d>* R, | |
| std::vector<Eigen::Vector3d>* t, | |
| std::vector<Eigen::Vector3d>* n); | |
| // Recover the most probable pose from the given homography matrix. | |
| // | |
| // The pose of the first image is assumed to be P = [I | 0]. | |
| // | |
| // @param H 3x3 homography matrix. | |
| // @param K1 3x3 calibration matrix of first camera. | |
| // @param K2 3x3 calibration matrix of second camera. | |
| // @param points1 First set of corresponding points. | |
| // @param points2 Second set of corresponding points. | |
| // @param inlier_mask Only points with `true` in the inlier mask are | |
| // considered in the cheirality test. Size of the | |
| // inlier mask must match the number of points N. | |
| // @param R Most probable 3x3 rotation matrix. | |
| // @param t Most probable 3x1 translation vector. | |
| // @param n Most probable 3x1 normal vector. | |
| // @param points3D Triangulated 3D points infront of camera | |
| // (only if homography is not pure-rotational). | |
| void PoseFromHomographyMatrix(const Eigen::Matrix3d& H, | |
| const Eigen::Matrix3d& K1, | |
| const Eigen::Matrix3d& K2, | |
| const std::vector<Eigen::Vector2d>& points1, | |
| const std::vector<Eigen::Vector2d>& points2, | |
| Eigen::Matrix3d* R, Eigen::Vector3d* t, | |
| Eigen::Vector3d* n, | |
| std::vector<Eigen::Vector3d>* points3D); | |
| // Compose homography matrix from relative pose. | |
| // | |
| // @param K1 3x3 calibration matrix of first camera. | |
| // @param K2 3x3 calibration matrix of second camera. | |
| // @param R Most probable 3x3 rotation matrix. | |
| // @param t Most probable 3x1 translation vector. | |
| // @param n Most probable 3x1 normal vector. | |
| // @param d Orthogonal distance from plane. | |
| // | |
| // @return 3x3 homography matrix. | |
| Eigen::Matrix3d HomographyMatrixFromPose(const Eigen::Matrix3d& K1, | |
| const Eigen::Matrix3d& K2, | |
| const Eigen::Matrix3d& R, | |
| const Eigen::Vector3d& t, | |
| const Eigen::Vector3d& n, | |
| const double d); | |
| } // namespace colmap | |