diff options
Diffstat (limited to 'ftnoir_tracker_pt/point_tracker.cpp')
| -rw-r--r-- | ftnoir_tracker_pt/point_tracker.cpp | 309 |
1 files changed, 154 insertions, 155 deletions
diff --git a/ftnoir_tracker_pt/point_tracker.cpp b/ftnoir_tracker_pt/point_tracker.cpp index cedf1979..924b75de 100644 --- a/ftnoir_tracker_pt/point_tracker.cpp +++ b/ftnoir_tracker_pt/point_tracker.cpp @@ -15,19 +15,18 @@ const float PI = 3.14159265358979323846f; -// ---------------------------------------------------------------------------- static void get_row(const cv::Matx33f& m, int i, cv::Vec3f& v) { - v[0] = m(i,0); - v[1] = m(i,1); - v[2] = m(i,2); + v[0] = m(i,0); + v[1] = m(i,1); + v[2] = m(i,2); } static void set_row(cv::Matx33f& m, int i, const cv::Vec3f& v) { - m(i,0) = v[0]; - m(i,1) = v[1]; - m(i,2) = v[2]; + m(i,0) = v[0]; + m(i,1) = v[1]; + m(i,2) = v[2]; } static bool d_vals_sort(const std::pair<float,int> a, const std::pair<float,int> b) @@ -67,31 +66,31 @@ PointTracker::PointOrder PointTracker::find_correspondences_previous(const std:: // 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; + point_taken[i] = false; for (int i=0; i<PointModel::N_POINTS; ++i) { - float min_sdist = 0; - int min_idx = 0; - // find closest point to projected model point i - for (int j=0; j<PointModel::N_POINTS; ++j) + float min_sdist = 0; + int min_idx = 0; + // find closest point to projected model point i + for (int j=0; j<PointModel::N_POINTS; ++j) + { + cv::Vec2f d = p.points[i]-points[j]; + float sdist = d.dot(d); + if (sdist < min_sdist || j==0) { - cv::Vec2f d = p.points[i]-points[j]; - float sdist = d.dot(d); - if (sdist < min_sdist || j==0) - { - min_idx = j; - min_sdist = sdist; - } + min_idx = j; + min_sdist = sdist; } - // 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]; + } + // 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; } @@ -100,19 +99,19 @@ void PointTracker::track(const std::vector<cv::Vec2f>& points, const PointModel& { PointOrder order; - if (t.elapsed_ms() > init_phase_timeout) - { - t.start(); - init_phase = true; - } + 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, f); - + else + order = find_correspondences_previous(points, model, f); + POSIT(model, order, f); - init_phase = false; + init_phase = false; t.start(); } @@ -142,127 +141,127 @@ PointTracker::PointOrder PointTracker::find_correspondences(const std::vector<cv int PointTracker::POSIT(const PointModel& model, const PointOrder& order_, float 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 - cv::Matx33f R_expected = cv::Matx33f::eye(); - - // initial pose = last (predicted) pose - cv::Vec3f k; - get_row(R_expected, 2, k); - float Z0 = 1000.f; - - float old_epsilon_1 = 0; - float old_epsilon_2 = 0; - float epsilon_1 = 1; - float epsilon_2 = 1; - - cv::Vec3f I0, J0; - cv::Vec2f I0_coeff, J0_coeff; - - cv::Vec3f I_1, J_1, I_2, J_2; - cv::Matx33f R_1, R_2; - cv::Matx33f* R_current; - - const int MAX_ITER = 100; - const float EPS_THRESHOLD = 1e-4; - - const cv::Vec2f* order = order_.points; - - int i=1; - for (; i<MAX_ITER; ++i) - { - epsilon_1 = k.dot(model.M01)/Z0; - epsilon_2 = k.dot(model.M02)/Z0; - - // vector of scalar products <I0, M0i> and <J0, M0i> - cv::Vec2f I0_M0i(order[1][0]*(1.0 + epsilon_1) - order[0][0], - order[2][0]*(1.0 + epsilon_2) - order[0][0]); - cv::Vec2f J0_M0i(order[1][1]*(1.0 + epsilon_1) - order[0][1], - order[2][1]*(1.0 + 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 - float II0 = I0.dot(I0); - float IJ0 = I0.dot(J0); - float JJ0 = J0.dot(J0); - float rho, theta; - if (JJ0 == II0) { - rho = std::sqrt(std::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)*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; - - float norm_const = 1.0/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 || - float R_1_deviation = cv::norm(cv::Matx33f::eye() - R_expected * R_1.t()); - float R_2_deviation = cv::norm(cv::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 (std::abs(epsilon_1 - old_epsilon_1) + std::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] = order[0][0] * Z0/focal_length; - X_CM.t[1] = order[0][1] * Z0/focal_length; - X_CM.t[2] = Z0; - - //qDebug() << "iter:" << i; - - return i; + // 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 + cv::Matx33f R_expected = cv::Matx33f::eye(); + + // initial pose = last (predicted) pose + cv::Vec3f k; + get_row(R_expected, 2, k); + float Z0 = 1000.f; + + float old_epsilon_1 = 0; + float old_epsilon_2 = 0; + float epsilon_1 = 1; + float epsilon_2 = 1; + + cv::Vec3f I0, J0; + cv::Vec2f I0_coeff, J0_coeff; + + cv::Vec3f I_1, J_1, I_2, J_2; + cv::Matx33f R_1, R_2; + cv::Matx33f* R_current; + + const int MAX_ITER = 100; + const float EPS_THRESHOLD = 1e-4; + + const cv::Vec2f* order = order_.points; + + int i=1; + for (; i<MAX_ITER; ++i) + { + epsilon_1 = k.dot(model.M01)/Z0; + epsilon_2 = k.dot(model.M02)/Z0; + + // vector of scalar products <I0, M0i> and <J0, M0i> + cv::Vec2f I0_M0i(order[1][0]*(1.0 + epsilon_1) - order[0][0], + order[2][0]*(1.0 + epsilon_2) - order[0][0]); + cv::Vec2f J0_M0i(order[1][1]*(1.0 + epsilon_1) - order[0][1], + order[2][1]*(1.0 + 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 + float II0 = I0.dot(I0); + float IJ0 = I0.dot(J0); + float JJ0 = J0.dot(J0); + float rho, theta; + if (JJ0 == II0) { + rho = std::sqrt(std::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)*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; + + float norm_const = 1.0/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 || + float R_1_deviation = cv::norm(cv::Matx33f::eye() - R_expected * R_1.t()); + float R_2_deviation = cv::norm(cv::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 (std::abs(epsilon_1 - old_epsilon_1) + std::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] = order[0][0] * Z0/focal_length; + X_CM.t[1] = order[0][1] * Z0/focal_length; + X_CM.t[2] = Z0; + + //qDebug() << "iter:" << i; + + return i; } cv::Vec2f PointTracker::project(const cv::Vec3f& v_M, float f) { - cv::Vec3f v_C = X_CM * v_M; - return cv::Vec2f(f*v_C[0]/v_C[2], f*v_C[1]/v_C[2]); + cv::Vec3f v_C = X_CM * v_M; + return cv::Vec2f(f*v_C[0]/v_C[2], f*v_C[1]/v_C[2]); } |