/* 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 "ftnoir_tracker_pt_settings.h" using namespace pt_types; #include "compat/nan.hpp" #include #include #include #include constexpr unsigned PointModel::N_POINTS; static void get_row(const mat33& m, int i, vec3& v) { v[0] = m(i,0); v[1] = m(i,1); v[2] = m(i,2); } static void set_row(mat33& m, int i, const vec3& v) { m(i,0) = v[0]; m(i,1) = v[1]; m(i,2) = v[2]; } static bool d_vals_sort(const std::pair a, const std::pair b) { return a.first < b.first; } PointModel::PointModel(settings_pt& s) { set_model(s); // calculate u u = M01.cross(M02); u /= norm(u); // calculate projection matrix on M01,M02 plane f s11 = M01.dot(M01); f s12 = M01.dot(M02); f s22 = M02.dot(M02); P = 1/(s11*s22-s12*s12) * mat22(s22, -s12, -s12, s11); } void PointModel::set_model(settings_pt& s) { switch (s.active_model_panel) { case Clip: M01 = vec3(0, static_cast(s.clip_ty), -static_cast(s.clip_tz)); M02 = vec3(0, -static_cast(s.clip_by), -static_cast(s.clip_bz)); break; case Cap: M01 = vec3(-static_cast(s.cap_x), -static_cast(s.cap_y), -static_cast(s.cap_z)); M02 = vec3(static_cast(s.cap_x), -static_cast(s.cap_y), -static_cast(s.cap_z)); break; case Custom: M01 = vec3(s.m01_x, s.m01_y, s.m01_z); M02 = vec3(s.m02_x, s.m02_y, s.m02_z); break; } } void PointModel::get_d_order(const std::vector& points, int* d_order, const vec2& d) const { // fit line to orthographically projected points std::vector> d_vals; // get sort indices with respect to d scalar product for (unsigned i = 0; i < PointModel::N_POINTS; ++i) d_vals.push_back(std::pair(d.dot(points[i]), i)); std::sort(d_vals.begin(), d_vals.end(), d_vals_sort ); for (unsigned i = 0; i < PointModel::N_POINTS; ++i) d_order[i] = d_vals[i].second; } PointTracker::PointTracker() : init_phase(true) { } PointTracker::PointOrder PointTracker::find_correspondences_previous(const std::vector& points, const PointModel& model, f focal_length, int w, int h) { PointTracker::PointOrder p; p.points[0] = project(vec3(0,0,0), focal_length); p.points[1] = project(model.M01, focal_length); p.points[2] = project(model.M02, focal_length); const int diagonal = int(std::sqrt(w*w + h*h)); static constexpr int div = 100; const int max_dist = diagonal / div; // 8 pixels for 640x480 // set correspondences by minimum distance to projected model point bool point_taken[PointModel::N_POINTS]; for (unsigned i=0; i max_dist) return find_correspondences(points, model); // if one point is closest to more than one model point, fallback if (point_taken[min_idx]) { init_phase = true; return find_correspondences(points, model); } point_taken[min_idx] = true; p.points[i] = points[min_idx]; } return p; } void PointTracker::track(const std::vector& points, const PointModel& model, f focal_length, bool dynamic_pose, int init_phase_timeout, int w, int h) { PointOrder order; if (t.elapsed_ms() > init_phase_timeout) { t.start(); init_phase = true; } if (!dynamic_pose || init_phase) order = find_correspondences(points, model); else { order = find_correspondences_previous(points, model, focal_length, w, h); } POSIT(model, order, focal_length); init_phase = false; t.start(); } PointTracker::PointOrder PointTracker::find_correspondences(const std::vector& points, const PointModel& model) { // We do a simple freetrack-like sorting in the init phase... // sort points int point_d_order[PointModel::N_POINTS]; int model_d_order[PointModel::N_POINTS]; vec2 d(model.M01[0]-model.M02[0], model.M01[1]-model.M02[1]); model.get_d_order(points, point_d_order, d); // calculate d and d_order for simple freetrack-like point correspondence model.get_d_order(std::vector { vec2{0,0}, vec2(model.M01[0], model.M01[1]), vec2(model.M02[0], model.M02[1]) }, model_d_order, d); // set correspondences PointOrder p; for (unsigned i = 0; i < PointModel::N_POINTS; ++i) p.points[model_d_order[i]] = points[point_d_order[i]]; return p; } int PointTracker::POSIT(const PointModel& model, const PointOrder& order_, f focal_length) { // 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 mat33 R_expected = mat33::eye(); // initial pose = last (predicted) pose vec3 k; get_row(R_expected, 2, k); f Z0 = f(1000); f old_epsilon_1 = 0; f old_epsilon_2 = 0; f epsilon_1 = 1; f epsilon_2 = 1; vec3 I0, J0; vec2 I0_coeff, J0_coeff; vec3 I_1, J_1, I_2, J_2; mat33 R_1, R_2; mat33* R_current = &R_1; static constexpr int max_iter = 100; const vec2* order = order_.points; using std::sqrt; using std::atan; using std::cos; using std::sin; using std::fabs; int i=1; for (; i and vec2 I0_M0i(order[1][0]*(1 + epsilon_1) - order[0][0], order[2][0]*(1 + epsilon_2) - order[0][0]); vec2 J0_M0i(order[1][1]*(1 + epsilon_1) - order[0][1], order[2][1]*(1 + epsilon_2) - order[0][1]); // construct projection of I, J onto M0i plane: I0 and J0 I0_coeff = model.P * I0_M0i; J0_coeff = model.P * J0_M0i; I0 = I0_coeff[0]*model.M01 + I0_coeff[1]*model.M02; J0 = J0_coeff[0]*model.M01 + J0_coeff[1]*model.M02; // calculate u component of I, J f II0 = I0.dot(I0); f IJ0 = I0.dot(J0); f JJ0 = J0.dot(J0); f rho, theta; // CAVEAT don't change to comparison with an epsilon -sh 20160423 if (JJ0 == II0) { rho = sqrt(fabs(2*IJ0)); theta = -M_PI/4; if (IJ0<0) theta *= -1; } else { rho = sqrt(sqrt( (JJ0-II0)*(JJ0-II0) + 4*IJ0*IJ0 )); theta = atan( -2*IJ0 / (JJ0-II0) ); // avoid branch misprediction theta += (JJ0 - II0 < 0) * M_PI; theta *= f(.5); } // construct the two solutions I_1 = I0 + rho*cos(theta)*model.u; I_2 = I0 - rho*cos(theta)*model.u; J_1 = J0 + rho*sin(theta)*model.u; J_2 = J0 - rho*sin(theta)*model.u; f norm_const = 1/cv::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 * focal_length; // pick the rotation solution closer to the expected one // in simple metric d(A,B) = || I - A * B^T || f R_1_deviation = cv::norm(mat33::eye() - R_expected * R_1.t()); f R_2_deviation = cv::norm(mat33::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 const f delta = fabs(epsilon_1 - old_epsilon_1) + fabs(epsilon_2 - old_epsilon_2); if (!(delta > constants::eps)) break; old_epsilon_1 = epsilon_1; old_epsilon_2 = epsilon_2; } const f t[3] = { order[0][0] * Z0/focal_length, order[0][1] * Z0/focal_length, Z0 }; const mat33& r = *R_current; for (int i = 0; i < 3; i++) for (int j = 0; j < 3; j++) if (nanp(r(i, j))) { qDebug() << "posit nan"; return -1; } for (unsigned i = 0; i < 3; i++) if (nanp(t[i])) { qDebug() << "posit nan"; return -1; } // apply results X_CM.R = r; X_CM.t[0] = t[0]; X_CM.t[1] = t[1]; X_CM.t[2] = t[2]; //qDebug() << "iter:" << i; return i; } vec2 PointTracker::project(const vec3& v_M, f focal_length) { vec3 v_C = X_CM * v_M; return vec2(focal_length*v_C[0]/v_C[2], focal_length*v_C[1]/v_C[2]); }