void mrpt::vision::pnp::posit::POS()
{
Eigen::Vector3d I0, J0 , r1, r2, r3;
double I0_norm, J0_norm;
int i;
double scale;
for(i=0;i<3;i++)
{
I0(i)=obj_matrix.row(i).dot(img_vecs.col(0));
J0(i)=obj_matrix.row(i).dot(img_vecs.col(1));
}
I0_norm=I0.norm();
J0_norm=J0.norm();
scale=(I0_norm + J0_norm)/2;
/*Computing TRANSLATION */
t(0)=img_pts(0,0)/scale;
t(1)=img_pts(0,1)/scale;
t(2)=f/scale;
/* Computing ROTATION */
r1=I0/I0_norm;
r2=J0/J0_norm;
r3=r1.cross(r2);
R.row(0)=r1;
R.row(1)=r2;
R.row(2)=r3;
}
bool mrpt::vision::pnp::rpnp::compute_pose(Eigen::Ref<Eigen::Matrix3d> R_, Eigen::Ref<Eigen::Vector3d> t_)
{
// selecting an edge $P_{ i1 }P_{ i2 }$ by n random sampling
int i1 = 0, i2 = 1;
double lmin = Q(0, i1)*Q(0, i2) + Q(1, i1)*Q(1, i2) + Q(2, i1)*Q(2, i2);
Eigen::MatrixXi rij (n,2);
R_=Eigen::MatrixXd::Identity(3,3);
t_=Eigen::Vector3d::Zero();
for (int i = 0; i < n; i++)
for (int j = 0; j < 2; j++)
rij(i, j) = rand() % n;
for (int ii = 0; ii < n; ii++)
{
int i = rij(ii, 0), j = rij(ii,1);
if (i == j)
continue;
double l = Q(0, i)*Q(0, j) + Q(1, i)*Q(1, j) + Q(2, i)*Q(2, j);
if (l < lmin)
{
i1 = i;
i2 = j;
lmin = l;
}
}
// calculating the rotation matrix of $O_aX_aY_aZ_a$.
Eigen::Vector3d p1, p2, p0, x, y, z, dum_vec;
p1 = P.col(i1);
p2 = P.col(i2);
p0 = (p1 + p2) / 2;
x = p2 - p0; x /= x.norm();
if (abs(x(1)) < abs(x(2)) )
{
dum_vec << 0, 1, 0;
z = x.cross(dum_vec); z /= z.norm();
y = z.cross(x); y /= y.norm();
}
else
{
dum_vec << 0, 0, 1;
y = dum_vec.cross(x); y /= y.norm();
z = x.cross(y); x /= x.norm();
}
Eigen::Matrix3d R0;
R0.col(0) = x; R0.col(1) =y; R0.col(2) = z;
for (int i = 0; i < n; i++)
P.col(i) = R0.transpose() * (P.col(i) - p0);
// Dividing the n - point set into(n - 2) 3 - point subsets
// and setting up the P3P equations
Eigen::Vector3d v1 = Q.col(i1), v2 = Q.col(i2);
double cg1 = v1.dot(v2);
double sg1 = sqrt(1 - cg1*cg1);
double D1 = (P.col(i1) - P.col(i2)).norm();
Eigen::MatrixXd D4(n - 2, 5);
int j = 0;
Eigen::Vector3d vi;
Eigen::VectorXd rowvec(5);
for (int i = 0; i < n; i++)
{
if (i == i1 || i == i2)
continue;
vi = Q.col(i);
double cg2 = v1.dot(vi);
double cg3 = v2.dot(vi);
double sg2 = sqrt(1 - cg2*cg2);
double D2 = (P.col(i1) - P.col(i)).norm();
double D3 = (P.col(i) - P.col(i2)).norm();
// get the coefficients of the P3P equation from each subset.
rowvec = getp3p(cg1, cg2, cg3, sg1, sg2, D1, D2, D3);
D4.row(j) = rowvec;
j += 1;
if(j>n-3)
break;
}
Eigen::VectorXd D7(8), dumvec(8), dumvec1(5);
D7.setZero();
for (int i = 0; i < n-2; i++)
{
dumvec1 = D4.row(i);
dumvec= getpoly7(dumvec1);
D7 += dumvec;
}
Eigen::PolynomialSolver<double, 7> psolve(D7.reverse());
Eigen::VectorXcd comp_roots = psolve.roots().transpose();
Eigen::VectorXd real_comp, imag_comp;
real_comp = comp_roots.real();
imag_comp = comp_roots.imag();
Eigen::VectorXd::Index max_index;
double max_real= real_comp.cwiseAbs().maxCoeff(&max_index);
std::vector<double> act_roots_;
int cnt=0;
for (int i=0; i<imag_comp.size(); i++ )
{
if(abs(imag_comp(i))/max_real<0.001)
{
act_roots_.push_back(real_comp(i));
cnt++;
}
}
double* ptr = &act_roots_[0];
Eigen::Map<Eigen::VectorXd> act_roots(ptr, cnt);
if (cnt==0)
{
return false;
}
Eigen::VectorXd act_roots1(cnt);
act_roots1 << act_roots.segment(0,cnt);
std::vector<Eigen::Matrix3d> R_cum(cnt);
std::vector<Eigen::Vector3d> t_cum(cnt);
std::vector<double> err_cum(cnt);
for(int i=0; i<cnt; i++)
{
double root = act_roots(i);
// Compute the rotation matrix
double d2 = cg1 + root;
Eigen::Vector3d unitx, unity, unitz;
unitx << 1,0,0;
unity << 0,1,0;
unitz << 0,0,1;
x = v2*d2 -v1;
x/=x.norm();
if (abs(unity.dot(x)) < abs(unitz.dot(x)))
{
z = x.cross(unity);z/=z.norm();
y=z.cross(x); y/y.norm();
}
else
{
y=unitz.cross(x); y/=y.norm();
z = x.cross(y); z/=z.norm();
}
R.col(0)=x;
R.col(1)=y;
R.col(2)=z;
//calculating c, s, tx, ty, tz
Eigen::MatrixXd D(2 * n, 6);
D.setZero();
R0 = R.transpose();
Eigen::VectorXd r(Eigen::Map<Eigen::VectorXd>(R0.data(), R0.cols()*R0.rows()));
for (int j = 0; j<n; j++)
{
double ui = img_pts(j, 0), vi = img_pts(j, 1), xi = P(0, j), yi = P(1, j), zi = P(2, j);
D.row(2 * j) << -r(1)*yi + ui*(r(7)*yi + r(8)*zi) - r(2)*zi,
-r(2)*yi + ui*(r(8)*yi - r(7)*zi) + r(1)*zi,
-1,
0,
ui,
ui*r(6)*xi - r(0)*xi;
D.row(2 * j + 1) << -r(4)*yi + vi*(r(7)*yi + r(8)*zi) - r(5)*zi,
-r(5)*yi + vi*(r(8)*yi - r(7)*zi) + r(4)*zi,
0,
-1,
vi,
vi*r(6)*xi - r(3)*xi;
}
Eigen::MatrixXd DTD = D.transpose()*D;
Eigen::EigenSolver<Eigen::MatrixXd> es(DTD);
Eigen::VectorXd Diag = es.pseudoEigenvalueMatrix().diagonal();
Eigen::MatrixXd V_mat = es.pseudoEigenvectors();
Eigen::MatrixXd::Index min_index;
Diag.minCoeff(&min_index);
Eigen::VectorXd V = V_mat.col(min_index);
V /= V(5);
double c = V(0), s = V(1);
t << V(2), V(3), V(4);
//calculating the camera pose by 3d alignment
Eigen::VectorXd xi, yi, zi;
xi = P.row(0);
yi = P.row(1);
zi = P.row(2);
Eigen::MatrixXd XXcs(3, n), XXc(3,n);
XXc.setZero();
XXcs.row(0) = r(0)*xi + (r(1)*c + r(2)*s)*yi + (-r(1)*s + r(2)*c)*zi + t(0)*Eigen::VectorXd::Ones(n);
XXcs.row(1) = r(3)*xi + (r(4)*c + r(5)*s)*yi + (-r(4)*s + r(5)*c)*zi + t(1)*Eigen::VectorXd::Ones(n);
XXcs.row(2) = r(6)*xi + (r(7)*c + r(8)*s)*yi + (-r(7)*s + r(8)*c)*zi + t(2)*Eigen::VectorXd::Ones(n);
for (int ii = 0; ii < n; ii++)
XXc.col(ii) = Q.col(ii)*XXcs.col(ii).norm();
Eigen::Matrix3d R2;
Eigen::Vector3d t2;
Eigen::MatrixXd XXw = obj_pts.transpose();
calcampose(XXc, XXw, R2, t2);
R_cum[i] = R2;
t_cum[i] = t2;
for (int k = 0; k < n; k++)
XXc.col(k) = R2 * XXw.col(k) + t2;
Eigen::MatrixXd xxc(2, n);
xxc.row(0) = XXc.row(0).array() / XXc.row(2).array();
xxc.row(1) = XXc.row(1).array() / XXc.row(2).array();
double res = ((xxc.row(0) - img_pts.col(0).transpose()).norm() + (xxc.row(1) - img_pts.col(1).transpose()).norm()) / 2;
err_cum[i] = res;
}
int pos_cum = std::min_element(err_cum.begin(), err_cum.end()) - err_cum.begin();
R_ = R_cum[pos_cum];
t_ = t_cum[pos_cum];
return true;
}
bool Estimator::initialStructure()
{
TicToc t_sfm;
//check imu observibility
{
map<double, ImageFrame>::iterator frame_it;
Vector3d sum_g;
for (frame_it = all_image_frame.begin(), frame_it++; frame_it != all_image_frame.end(); frame_it++)
{
double dt = frame_it->second.pre_integration->sum_dt;
Vector3d tmp_g = frame_it->second.pre_integration->delta_v / dt;
sum_g += tmp_g;
}
Vector3d aver_g;
aver_g = sum_g * 1.0 / ((int)all_image_frame.size() - 1);
double var = 0;
for (frame_it = all_image_frame.begin(), frame_it++; frame_it != all_image_frame.end(); frame_it++)
{
double dt = frame_it->second.pre_integration->sum_dt;
Vector3d tmp_g = frame_it->second.pre_integration->delta_v / dt;
var += (tmp_g - aver_g).transpose() * (tmp_g - aver_g);
//cout << "frame g " << tmp_g.transpose() << endl;
}
var = sqrt(var / ((int)all_image_frame.size() - 1));
//ROS_WARN("IMU variation %f!", var);
if(var < 0.25)
{
ROS_INFO("IMU excitation not enouth!");
//return false;
}
}
// global sfm
Quaterniond Q[frame_count + 1];
Vector3d T[frame_count + 1];
map<int, Vector3d> sfm_tracked_points;
vector<SFMFeature> sfm_f;
for (auto &it_per_id : f_manager.feature)
{
int imu_j = it_per_id.start_frame - 1;
SFMFeature tmp_feature;
tmp_feature.state = false;
tmp_feature.id = it_per_id.feature_id;
for (auto &it_per_frame : it_per_id.feature_per_frame)
{
imu_j++;
Vector3d pts_j = it_per_frame.point;
tmp_feature.observation.push_back(make_pair(imu_j, Eigen::Vector2d{pts_j.x(), pts_j.y()}));
}
sfm_f.push_back(tmp_feature);
}
Matrix3d relative_R;
Vector3d relative_T;
int l;
if (!relativePose(relative_R, relative_T, l))
{
ROS_INFO("Not enough features or parallax; Move device around");
return false;
}
GlobalSFM sfm;
if(!sfm.construct(frame_count + 1, Q, T, l,
relative_R, relative_T,
sfm_f, sfm_tracked_points))
{
ROS_DEBUG("global SFM failed!");
marginalization_flag = MARGIN_OLD;
return false;
}
//solve pnp for all frame
map<double, ImageFrame>::iterator frame_it;
map<int, Vector3d>::iterator it;
frame_it = all_image_frame.begin( );
for (int i = 0; frame_it != all_image_frame.end( ); frame_it++)
{
// provide initial guess
cv::Mat r, rvec, t, D, tmp_r;
if((frame_it->first) == Headers[i].stamp.toSec())
{
frame_it->second.is_key_frame = true;
frame_it->second.R = Q[i].toRotationMatrix() * RIC[0].transpose();
frame_it->second.T = T[i];
i++;
continue;
}
if((frame_it->first) > Headers[i].stamp.toSec())
{
i++;
}
Matrix3d R_inital = (Q[i].inverse()).toRotationMatrix();
Vector3d P_inital = - R_inital * T[i];
cv::eigen2cv(R_inital, tmp_r);
cv::Rodrigues(tmp_r, rvec);
cv::eigen2cv(P_inital, t);
frame_it->second.is_key_frame = false;
vector<cv::Point3f> pts_3_vector;
vector<cv::Point2f> pts_2_vector;
for (auto &id_pts : frame_it->second.points)
{
int feature_id = id_pts.first;
//cout << "feature id " << feature_id;
for (auto &i_p : id_pts.second)
{
//cout << " pts image_frame " << (i_p.second.head<2>() * 460 ).transpose() << endl;
it = sfm_tracked_points.find(feature_id);
if(it != sfm_tracked_points.end())
{
Vector3d world_pts = it->second;
cv::Point3f pts_3(world_pts(0), world_pts(1), world_pts(2));
pts_3_vector.push_back(pts_3);
Vector2d img_pts = i_p.second.head<2>();
cv::Point2f pts_2(img_pts(0), img_pts(1));
pts_2_vector.push_back(pts_2);
}
}
}
cv::Mat K = (cv::Mat_<double>(3, 3) << 1, 0, 0, 0, 1, 0, 0, 0, 1);
if(pts_3_vector.size() < 6)
{
//cout << "pts_3_vector size " << pts_3_vector.size() << endl;
ROS_DEBUG("Not enough points for solve pnp !");
return false;
}
if (! cv::solvePnP(pts_3_vector, pts_2_vector, K, D, rvec, t, 1))
{
ROS_DEBUG("solve pnp fail!");
return false;
}
cv::Rodrigues(rvec, r);
MatrixXd R_pnp,tmp_R_pnp;
cv::cv2eigen(r, tmp_R_pnp);
R_pnp = tmp_R_pnp.transpose();
MatrixXd T_pnp;
cv::cv2eigen(t, T_pnp);
T_pnp = R_pnp * (-T_pnp);
frame_it->second.R = R_pnp * RIC[0].transpose();
frame_it->second.T = T_pnp;
}
if (visualInitialAlign())
return true;
else
{
ROS_INFO("misalign visual structure with IMU");
return false;
}
}
