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//
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//
// * 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
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// documentation and/or other materials provided with the distribution.
//
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// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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// 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 <vector>
#include <Eigen/Core>
#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<M_t> Estimate(const std::vector<X_t>& points1,
const std::vector<Y_t>& points2);
// Calculate the squared Sampson error between corresponding points.
static void Residuals(const std::vector<X_t>& points1,
const std::vector<Y_t>& points2, const M_t& proj_matrix,
std::vector<double>* residuals);
};
} // namespace colmap
EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION_CUSTOM(colmap::GR6PEstimator::X_t)
#endif // COLMAP_SRC_ESTIMATORS_GENERALIZED_RELATIVE_POSE_H_
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