// Copyright (c) 2022, ETH Zurich and UNC Chapel Hill. // All rights reserved. // // Redistribution and use in source and binary forms, with or without // modification, are permitted provided that the following conditions are met: // // * Redistributions of source code must retain the above copyright // notice, this list of conditions and the following disclaimer. // // * Redistributions in binary form must reproduce the above copyright // notice, this list of conditions and the following disclaimer in the // documentation and/or other materials provided with the distribution. // // * Neither the name of ETH Zurich and UNC Chapel Hill nor the names of // its contributors may be used to endorse or promote products derived // from this software without specific prior written permission. // // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" // AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE // ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR CONTRIBUTORS BE // LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR // CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF // SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS // INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN // CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) // ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE // POSSIBILITY OF SUCH DAMAGE. // // Author: Johannes L. Schoenberger (jsch-at-demuc-dot-de) #ifndef COLMAP_SRC_ESTIMATORS_GENERALIZED_RELATIVE_POSE_H_ #define COLMAP_SRC_ESTIMATORS_GENERALIZED_RELATIVE_POSE_H_ #include #include #include "util/alignment.h" #include "util/types.h" namespace colmap { // Solver for the Generalized Relative Pose problem using a minimal of 8 2D-2D // correspondences. This implementation is based on: // // "Efficient Computation of Relative Pose for Multi-Camera Systems", // Kneip and Li. CVPR 2014. // // Note that the solution to this problem is degenerate in the case of pure // translation and when all correspondences are observed from the same cameras. // // The implementation is a modified and improved version of Kneip's original // implementation in OpenGV licensed under the BSD license. class GR6PEstimator { public: // The generalized image observations of the left camera, which is composed of // the relative pose of the specific camera in the generalized camera and its // image observation. struct X_t { EIGEN_MAKE_ALIGNED_OPERATOR_NEW // The relative transformation from the generalized camera to the camera // frame of the observation. Eigen::Matrix3x4d rel_tform; // The 2D image feature observation. Eigen::Vector2d xy; }; // The normalized image feature points in the left camera. typedef X_t Y_t; // The relative transformation between the two generalized cameras. typedef Eigen::Matrix3x4d M_t; // The minimum number of samples needed to estimate a model. Note that in // theory the minimum required number of samples is 6 but Laurent Kneip showed // in his paper that using 8 samples is more stable. static const int kMinNumSamples = 8; // Estimate the most probable solution of the GR6P problem from a set of // six 2D-2D point correspondences. static std::vector Estimate(const std::vector& points1, const std::vector& points2); // Calculate the squared Sampson error between corresponding points. static void Residuals(const std::vector& points1, const std::vector& points2, const M_t& proj_matrix, std::vector* residuals); }; } // namespace colmap EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION_CUSTOM(colmap::GR6PEstimator::X_t) #endif // COLMAP_SRC_ESTIMATORS_GENERALIZED_RELATIVE_POSE_H_