// Copyright (c) 2022, ETH Zurich and UNC Chapel Hill.
// All rights reserved.
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// Author: Johannes L. Schoenberger (jsch-at-demuc-dot-de)

#ifndef COLMAP_SRC_ESTIMATORS_FUNDAMENTAL_MATRIX_H_
#define COLMAP_SRC_ESTIMATORS_FUNDAMENTAL_MATRIX_H_

#include <vector>

#include <Eigen/Core>

#include "estimators/homography_matrix.h"
#include "util/alignment.h"
#include "util/types.h"

namespace colmap {

// Fundamental matrix estimator from corresponding point pairs.
//
// This algorithm solves the 7-Point problem and is based on the following
// paper:
//
//    Zhengyou Zhang and T. Kanade, Determining the Epipolar Geometry and its
//    Uncertainty: A Review, International Journal of Computer Vision, 1998.
//    http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.33.4540
class FundamentalMatrixSevenPointEstimator {
 public:
  typedef Eigen::Vector2d X_t;
  typedef Eigen::Vector2d Y_t;
  typedef Eigen::Matrix3d M_t;

  // The minimum number of samples needed to estimate a model.
  static const int kMinNumSamples = 7;

  // Estimate either 1 or 3 possible fundamental matrix solutions from a set of
  // corresponding points.
  //
  // The number of corresponding points must be exactly 7.
  //
  // @param points1  First set of corresponding points.
  // @param points2  Second set of corresponding points
  //
  // @return         Up to 4 solutions as a vector of 3x3 fundamental matrices.
  static std::vector<M_t> Estimate(const std::vector<X_t>& points1,
                                   const std::vector<Y_t>& points2);

  // Calculate the residuals of a set of corresponding points and a given
  // fundamental matrix.
  //
  // Residuals are defined as the squared Sampson error.
  //
  // @param points1    First set of corresponding points as Nx2 matrix.
  // @param points2    Second set of corresponding points as Nx2 matrix.
  // @param F          3x3 fundamental matrix.
  // @param residuals  Output vector of residuals.
  static void Residuals(const std::vector<X_t>& points1,
                        const std::vector<Y_t>& points2, const M_t& F,
                        std::vector<double>* residuals);
};

// Fundamental matrix estimator from corresponding point pairs.
//
// This algorithm solves the 8-Point problem based on the following paper:
//
//    Hartley and Zisserman, Multiple View Geometry, algorithm 11.1, page 282.
class FundamentalMatrixEightPointEstimator {
 public:
  typedef Eigen::Vector2d X_t;
  typedef Eigen::Vector2d Y_t;
  typedef Eigen::Matrix3d M_t;

  // The minimum number of samples needed to estimate a model.
  static const int kMinNumSamples = 8;

  // Estimate fundamental matrix solutions from a set of corresponding points.
  //
  // The number of corresponding points must be at least 8.
  //
  // @param points1  First set of corresponding points.
  // @param points2  Second set of corresponding points
  //
  // @return         Single solution as a vector of 3x3 fundamental matrices.
  static std::vector<M_t> Estimate(const std::vector<X_t>& points1,
                                   const std::vector<Y_t>& points2);

  // Calculate the residuals of a set of corresponding points and a given
  // fundamental matrix.
  //
  // Residuals are defined as the squared Sampson error.
  //
  // @param points1    First set of corresponding points as Nx2 matrix.
  // @param points2    Second set of corresponding points as Nx2 matrix.
  // @param F          3x3 fundamental matrix.
  // @param residuals  Output vector of residuals.
  static void Residuals(const std::vector<X_t>& points1,
                        const std::vector<Y_t>& points2, const M_t& F,
                        std::vector<double>* residuals);
};

}  // namespace colmap

#endif  // COLMAP_SRC_ESTIMATORS_FUNDAMENTAL_MATRIX_H_