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-rw-r--r--FTNoIR_Tracker_PT/point_tracker.cpp352
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diff --git a/FTNoIR_Tracker_PT/point_tracker.cpp b/FTNoIR_Tracker_PT/point_tracker.cpp
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--- a/FTNoIR_Tracker_PT/point_tracker.cpp
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-/* Copyright (c) 2012 Patrick Ruoff
- *
- * Permission to use, copy, modify, and/or distribute this software for any
- * purpose with or without fee is hereby granted, provided that the above
- * copyright notice and this permission notice appear in all copies.
- */
-
-#include "point_tracker.h"
-
-#include <vector>
-#include <algorithm>
-#include <cmath>
-
-#include <QDebug>
-
-using namespace cv;
-using namespace boost;
-using namespace std;
-
-const float PI = 3.14159265358979323846f;
-
-// ----------------------------------------------------------------------------
-static void get_row(const Matx33f& m, int i, Vec3f& v)
-{
- v[0] = m(i,0);
- v[1] = m(i,1);
- v[2] = m(i,2);
-}
-
-static void set_row(Matx33f& m, int i, const Vec3f& v)
-{
- m(i,0) = v[0];
- m(i,1) = v[1];
- m(i,2) = v[2];
-}
-
-// ----------------------------------------------------------------------------
-PointModel::PointModel(Vec3f M01, Vec3f M02)
- : M01(M01), M02(M02)
-{
- // calculate u
- u = M01.cross(M02);
- u /= norm(u);
-
- // calculate projection matrix on M01,M02 plane
- float s11 = M01.dot(M01);
- float s12 = M01.dot(M02);
- float s22 = M02.dot(M02);
- P = 1.0/(s11*s22-s12*s12) * Matx22f(s22, -s12,
- -s12, s11);
-
- // calculate d and d_order for simple freetrack-like point correspondence
- vector<Vec2f> points;
- points.push_back(Vec2f(0,0));
- points.push_back(Vec2f(M01[0], M01[1]));
- points.push_back(Vec2f(M02[0], M02[1]));
- // fit line to orthographically projected points
- // ERROR: yields wrong results with colinear points?!
- /*
- Vec4f line;
- fitLine(points, line, CV_DIST_L2, 0, 0.01, 0.01);
- d[0] = line[0]; d[1] = line[1];
- */
- // TODO: fix this
- d = Vec2f(M01[0]-M02[0], M01[1]-M02[1]);
-
- // sort model points
- get_d_order(points, d_order);
-}
-
-void PointModel::get_d_order(const std::vector<cv::Vec2f>& points, int d_order[]) const
-{
- // get sort indices with respect to d scalar product
- vector< pair<float,int> > d_vals;
- for (int i = 0; i<points.size(); ++i)
- d_vals.push_back(pair<float, int>(d.dot(points[i]), i));
-
- struct
- {
- bool operator()(const pair<float, int>& a, const pair<float, int>& b) { return a.first < b.first; }
- } comp;
- sort(d_vals.begin(), d_vals.end(), comp);
-
- for (int i = 0; i<points.size(); ++i)
- d_order[i] = d_vals[i].second;
-}
-
-
-// ----------------------------------------------------------------------------
-PointTracker::PointTracker() : init_phase(true), dt_valid(0), dt_reset(1), v_t(0,0,0), v_r(0,0,0), dynamic_pose_resolution(true)
-{
- X_CM.t[2] = 1000; // default position: 1 m away from cam;
-}
-
-void PointTracker::reset()
-{
- // enter init phase and reset velocities
- init_phase = true;
- dt_valid = 0;
- reset_velocities();
-}
-
-void PointTracker::reset_velocities()
-{
- v_t = Vec3f(0,0,0);
- v_r = Vec3f(0,0,0);
-}
-
-
-bool PointTracker::track(const vector<Vec2f>& points, float f, float dt)
-{
- if (!dynamic_pose_resolution) init_phase = true;
-
- dt_valid += dt;
- // if there was no valid tracking result for too long, do a reset
- if (dt_valid > dt_reset)
- {
- //qDebug()<<"dt_valid "<<dt_valid<<" > dt_reset "<<dt_reset;
- reset();
- }
-
- // if there is a pointtracking problem, reset the velocities
- if (!point_model || points.size() != PointModel::N_POINTS)
- {
- //qDebug()<<"Wrong number of points!";
- reset_velocities();
- return false;
- }
-
- X_CM_old = X_CM; // backup old transformation for velocity calculation
-
- if (!init_phase)
- predict(dt_valid);
-
- // if there is a point correspondence problem something has gone wrong, do a reset
- if (!find_correspondences(points, f))
- {
- //qDebug()<<"Error in finding point correspondences!";
- X_CM = X_CM_old; // undo prediction
- reset();
- return false;
- }
-
- int n_iter = POSIT(f);
- //qDebug()<<"Number of POSIT iterations: "<<n_iter;
-
- if (!init_phase)
- update_velocities(dt_valid);
-
- // we have a valid tracking result, leave init phase and reset time since valid result
- init_phase = false;
- dt_valid = 0;
- return true;
-}
-
-void PointTracker::predict(float dt)
-{
- // predict with constant velocity
- Matx33f R;
- Rodrigues(dt*v_r, R);
- X_CM.R = R*X_CM.R;
- X_CM.t += dt * v_t;
-}
-
-void PointTracker::update_velocities(float dt)
-{
- // update velocities
- Rodrigues(X_CM.R*X_CM_old.R.t(), v_r);
- v_r /= dt;
- v_t = (X_CM.t - X_CM_old.t)/dt;
-}
-
-bool PointTracker::find_correspondences(const vector<Vec2f>& points, float f)
-{
- if (init_phase) {
- // We do a simple freetrack-like sorting in the init phase...
- // sort points
- int point_d_order[PointModel::N_POINTS];
- point_model->get_d_order(points, point_d_order);
-
- // set correspondences
- for (int i=0; i<PointModel::N_POINTS; ++i)
- {
- p[point_model->d_order[i]] = points[point_d_order[i]];
- }
- }
- else {
- // ... otherwise we look at the distance to the projection of the expected model points
- // project model points under current pose
- p_exp[0] = project(Vec3f(0,0,0), f);
- p_exp[1] = project(point_model->M01, f);
- p_exp[2] = project(point_model->M02, f);
-
- // set correspondences by minimum distance to projected model point
- bool point_taken[PointModel::N_POINTS];
- for (int i=0; i<PointModel::N_POINTS; ++i)
- point_taken[i] = false;
-
- float min_sdist = 0;
- int min_idx = 0;
-
- for (int i=0; i<PointModel::N_POINTS; ++i)
- {
- // find closest point to projected model point i
- for (int j=0; j<PointModel::N_POINTS; ++j)
- {
- Vec2f d = p_exp[i]-points[j];
- float sdist = d.dot(d);
- if (sdist < min_sdist || j==0)
- {
- min_idx = j;
- min_sdist = sdist;
- }
- }
- // if one point is closest to more than one model point, abort
- if (point_taken[min_idx]) return false;
- point_taken[min_idx] = true;
- p[i] = points[min_idx];
- }
- }
- return true;
-}
-
-
-
-int PointTracker::POSIT(float f)
-{
- // POSIT algorithm for coplanar points as presented in
- // [Denis Oberkampf, Daniel F. DeMenthon, Larry S. Davis: "Iterative Pose Estimation Using Coplanar Feature Points"]
- // we use the same notation as in the paper here
-
- // The expected rotation used for resolving the ambiguity in POSIT:
- // In every iteration step the rotation closer to R_expected is taken
- Matx33f R_expected;
- if (init_phase)
- R_expected = Matx33f::eye(); // in the init phase, we want to be close to the default pose = no rotation
- else
- R_expected = X_CM.R; // later we want to be close to the last (predicted) rotation
-
- // initial pose = last (predicted) pose
- Vec3f k;
- get_row(X_CM.R, 2, k);
- float Z0 = X_CM.t[2];
-
- float old_epsilon_1 = 0;
- float old_epsilon_2 = 0;
- float epsilon_1 = 1;
- float epsilon_2 = 1;
-
- Vec3f I0, J0;
- Vec2f I0_coeff, J0_coeff;
-
- Vec3f I_1, J_1, I_2, J_2;
- Matx33f R_1, R_2;
- Matx33f* R_current;
-
- const int MAX_ITER = 100;
- const float EPS_THRESHOLD = 1e-4;
-
- int i=1;
- for (; i<MAX_ITER; ++i)
- {
- epsilon_1 = k.dot(point_model->M01)/Z0;
- epsilon_2 = k.dot(point_model->M02)/Z0;
-
- // vector of scalar products <I0, M0i> and <J0, M0i>
- Vec2f I0_M0i(p[1][0]*(1.0 + epsilon_1) - p[0][0],
- p[2][0]*(1.0 + epsilon_2) - p[0][0]);
- Vec2f J0_M0i(p[1][1]*(1.0 + epsilon_1) - p[0][1],
- p[2][1]*(1.0 + epsilon_2) - p[0][1]);
-
- // construct projection of I, J onto M0i plane: I0 and J0
- I0_coeff = point_model->P * I0_M0i;
- J0_coeff = point_model->P * J0_M0i;
- I0 = I0_coeff[0]*point_model->M01 + I0_coeff[1]*point_model->M02;
- J0 = J0_coeff[0]*point_model->M01 + J0_coeff[1]*point_model->M02;
-
- // calculate u component of I, J
- float II0 = I0.dot(I0);
- float IJ0 = I0.dot(J0);
- float JJ0 = J0.dot(J0);
- float rho, theta;
- if (JJ0 == II0) {
- rho = sqrt(abs(2*IJ0));
- theta = -PI/4;
- if (IJ0<0) theta *= -1;
- }
- else {
- rho = sqrt(sqrt( (JJ0-II0)*(JJ0-II0) + 4*IJ0*IJ0 ));
- theta = atan( -2*IJ0 / (JJ0-II0) );
- if (JJ0 - II0 < 0) theta += PI;
- theta /= 2;
- }
-
- // construct the two solutions
- I_1 = I0 + rho*cos(theta)*point_model->u;
- I_2 = I0 - rho*cos(theta)*point_model->u;
-
- J_1 = J0 + rho*sin(theta)*point_model->u;
- J_2 = J0 - rho*sin(theta)*point_model->u;
-
- float norm_const = 1.0/norm(I_1); // all have the same norm
-
- // create rotation matrices
- I_1 *= norm_const; J_1 *= norm_const;
- I_2 *= norm_const; J_2 *= norm_const;
-
- set_row(R_1, 0, I_1);
- set_row(R_1, 1, J_1);
- set_row(R_1, 2, I_1.cross(J_1));
-
- set_row(R_2, 0, I_2);
- set_row(R_2, 1, J_2);
- set_row(R_2, 2, I_2.cross(J_2));
-
- // the single translation solution
- Z0 = norm_const * f;
-
- // pick the rotation solution closer to the expected one
- // in simple metric d(A,B) = || I - A * B^T ||
- float R_1_deviation = norm(Matx33f::eye() - R_expected * R_1.t());
- float R_2_deviation = norm(Matx33f::eye() - R_expected * R_2.t());
-
- if (R_1_deviation < R_2_deviation)
- R_current = &R_1;
- else
- R_current = &R_2;
-
- get_row(*R_current, 2, k);
-
- // check for convergence condition
- if (abs(epsilon_1 - old_epsilon_1) + abs(epsilon_2 - old_epsilon_2) < EPS_THRESHOLD)
- break;
- old_epsilon_1 = epsilon_1;
- old_epsilon_2 = epsilon_2;
- }
-
- // apply results
- X_CM.R = *R_current;
- X_CM.t[0] = p[0][0] * Z0/f;
- X_CM.t[1] = p[0][1] * Z0/f;
- X_CM.t[2] = Z0;
-
- return i;
-
- //Rodrigues(X_CM.R, r);
- //qDebug()<<"iter: "<<i;
- //qDebug()<<"t: "<<X_CM.t[0]<<' '<<X_CM.t[1]<<' '<<X_CM.t[2];
- //Vec3f r;
- //
- //qDebug()<<"r: "<<r[0]<<' '<<r[1]<<' '<<r[2]<<'\n';
-}