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PnPsolver.h
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/**
* This file is part of ORB-SLAM.
* This is a modified version of EPnP <http://cvlab.epfl.ch/EPnP/index.php> including a RANSAC scheme
*
* Copyright (C) 2014 Raúl Mur-Artal <raulmur at unizar dot es> (University of Zaragoza)
* For more information see <http://webdiis.unizar.es/~raulmur/orbslam/>
*
* ORB-SLAM is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* ORB-SLAM is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with ORB-SLAM. If not, see <http://www.gnu.org/licenses/>.
*/
#ifndef PNPSOLVER_H
#define PNPSOLVER_H
#include <opencv/cv.h>
#include "MapPoint.h"
#include "Frame.h"
namespace ORB_SLAM
{
class PnPsolver {
public:
PnPsolver(const Frame &F, const vector<MapPoint*> &vpMapPointMatches);
~PnPsolver();
void SetRansacParameters(double probability = 0.99, int minInliers = 8 , int maxIterations = 300, int minSet = 4, float epsilon = 0.4,
float th2 = 5.991);
cv::Mat find(vector<bool> &vbInliers, int &nInliers);
cv::Mat iterate(int nIterations, bool &bNoMore, vector<bool> &vbInliers, int &nInliers);
private:
void CheckInliers();
bool Refine();
// Functions from the original EPnP code
void set_maximum_number_of_correspondences(const int n);
void reset_correspondences(void);
void add_correspondence(const double X, const double Y, const double Z,
const double u, const double v);
double compute_pose(double R[3][3], double T[3]);
void relative_error(double & rot_err, double & transl_err,
const double Rtrue[3][3], const double ttrue[3],
const double Rest[3][3], const double test[3]);
void print_pose(const double R[3][3], const double t[3]);
double reprojection_error(const double R[3][3], const double t[3]);
void choose_control_points(void);
void compute_barycentric_coordinates(void);
void fill_M(CvMat * M, const int row, const double * alphas, const double u, const double v);
void compute_ccs(const double * betas, const double * ut);
void compute_pcs(void);
void solve_for_sign(void);
void find_betas_approx_1(const CvMat * L_6x10, const CvMat * Rho, double * betas);
void find_betas_approx_2(const CvMat * L_6x10, const CvMat * Rho, double * betas);
void find_betas_approx_3(const CvMat * L_6x10, const CvMat * Rho, double * betas);
void qr_solve(CvMat * A, CvMat * b, CvMat * X);
double dot(const double * v1, const double * v2);
double dist2(const double * p1, const double * p2);
void compute_rho(double * rho);
void compute_L_6x10(const double * ut, double * l_6x10);
void gauss_newton(const CvMat * L_6x10, const CvMat * Rho, double current_betas[4]);
void compute_A_and_b_gauss_newton(const double * l_6x10, const double * rho,
double cb[4], CvMat * A, CvMat * b);
double compute_R_and_t(const double * ut, const double * betas,
double R[3][3], double t[3]);
void estimate_R_and_t(double R[3][3], double t[3]);
void copy_R_and_t(const double R_dst[3][3], const double t_dst[3],
double R_src[3][3], double t_src[3]);
void mat_to_quat(const double R[3][3], double q[4]);
double uc, vc, fu, fv;
double * pws, * us, * alphas, * pcs;
int maximum_number_of_correspondences;
int number_of_correspondences;
double cws[4][3], ccs[4][3];
double cws_determinant;
vector<MapPoint*> mvpMapPointMatches;
// 2D Points
vector<cv::Point2f> mvP2D;
vector<float> mvSigma2;
// 3D Points
vector<cv::Point3f> mvP3Dw;
// Index in Frame
vector<size_t> mvKeyPointIndices;
// Current Estimation
double mRi[3][3];
double mti[3];
cv::Mat mTcwi;
vector<bool> mvbInliersi;
int mnInliersi;
// Current Ransac State
int mnIterations;
vector<bool> mvbBestInliers;
int mnBestInliers;
cv::Mat mBestTcw;
// Refined
cv::Mat mRefinedTcw;
vector<bool> mvbRefinedInliers;
int mnRefinedInliers;
// Number of Correspondences
int N;
// Indices for random selection [0 .. N-1]
vector<size_t> mvAllIndices;
// RANSAC probability
double mRansacProb;
// RANSAC min inliers
int mRansacMinInliers;
// RANSAC max iterations
int mRansacMaxIts;
// RANSAC expected inliers/total ratio
float mRansacEpsilon;
// RANSAC Threshold inlier/outlier. Max error e = dist(P1,T_12*P2)^2
float mRansacTh;
// RANSAC Minimun Set used at each iteration
int mRansacMinSet;
// Max square error associated with scale level. Max error = th*th*sigma(level)*sigma(level)
vector<float> mvMaxError;
};
} //namespace ORB_SLAM
#endif //PNPSOLVER_H