ceres-solver-v1 / colmap /src /estimators /essential_matrix.h
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// Copyright (c) 2022, ETH Zurich and UNC Chapel Hill.
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// Author: Johannes L. Schoenberger (jsch-at-demuc-dot-de)
#ifndef COLMAP_SRC_ESTIMATORS_ESSENTIAL_MATRIX_H_
#define COLMAP_SRC_ESTIMATORS_ESSENTIAL_MATRIX_H_
#include <vector>
#include <Eigen/Core>
#include <ceres/ceres.h>
#include "util/alignment.h"
#include "util/types.h"
namespace colmap {
// Essential matrix estimator from corresponding normalized point pairs.
//
// This algorithm solves the 5-Point problem based on the following paper:
//
// D. Nister, An efficient solution to the five-point relative pose problem,
// IEEE-T-PAMI, 26(6), 2004.
// http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.86.8769
class EssentialMatrixFivePointEstimator {
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 = 5;
// Estimate up to 10 possible essential matrix solutions from a set of
// corresponding points.
//
// The number of corresponding points must be at least 5.
//
// @param points1 First set of corresponding points.
// @param points2 Second set of corresponding points.
//
// @return Up to 10 solutions as a vector of 3x3 essential 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
// essential matrix.
//
// Residuals are defined as the squared Sampson error.
//
// @param points1 First set of corresponding points.
// @param points2 Second set of corresponding points.
// @param E 3x3 essential 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& E,
std::vector<double>* residuals);
};
// Essential matrix estimator from corresponding normalized 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 EssentialMatrixEightPointEstimator {
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 essential matrix solutions from 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.
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
// essential matrix.
//
// Residuals are defined as the squared Sampson error.
//
// @param points1 First set of corresponding points.
// @param points2 Second set of corresponding points.
// @param E 3x3 essential 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& E,
std::vector<double>* residuals);
};
} // namespace colmap
#endif // COLMAP_SRC_ESTIMATORS_ESSENTIAL_MATRIX_H_