long Route::initweights(int dumPlaces)
{
int i = 0;
vector<long> dumvec (dumPlaces);
for (i=0; i<dumPlaces; ++i) {
weights.push_back(dumvec);
}
return weights.size();
}
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;
}
vector<Point> Find_refer_point(vector<Point> contour_point)
{
int size = contour_point.size(); Point temp;
int i=0,j=0,k=0;
float x_sum=0,y_sum=0; float x_mean,y_mean;
float xx=0,xy=0,yx=0,yy=0; float xd,yd;
float A[2][2];
float maj1,maj2,min1,min2;
for(i=0;i<size;i++)
{
temp = contour_point[i];
x_sum = temp.x + x_sum;
y_sum = temp.y + x_sum;
}
x_mean = x_sum/(float)size; y_mean = y_sum/(float)size;
for(i=0;i<size;i++)
{
temp = contour_point[i];
xd = (float)temp.y - x_mean;
yd = (float)temp.x - y_mean;
xx = xx + (xd*xd)/(float)size;
xy = xy + (xd*yd)/(float)size;
yx = yx + (yd*xd)/(float)size;
yy = yy + (yd*yd)/(float)size;
}
A[0][0] = xx; A[0][1] = xy; A[1][0] = yx; A[1][1] = yy;
Mat CM(2,2,CV_32FC1,A);
Mat eival(2,1,CV_32FC1);
Mat eivec(2,2,CV_32FC1);
eigen(CM,eival,eivec);
maj1 = eivec.at<float>(0,0);
maj2 = eivec.at<float>(0,1);
min1 = eivec.at<float>(1,0);
min2 = eivec.at<float>(1,1);
float Head[2]={0,0}, Lfoot[2]={0,0}, Rfoot[2]={0,0};
float dummy_x, dummy_y;
float Rmin[2], Rmaj[2], Gmin[2], Gmaj[2];
Rmin[0] = (-1)*maj1; Rmin[1] = (-1)*maj2; Rmaj[0] = maj1; Rmaj[1] = maj2;
Gmin[0] = (-1)*min1; Gmin[1] = (-1)*min2; Gmaj[0] = min1; Gmaj[1] = min2;
Mat Ra(1,2,CV_32FC1,Rmin);
Mat Rb(1,2,CV_32FC1,Rmaj);
Mat Ga(1,2,CV_32FC1,Gmin);
Mat Gb(1,2,CV_32FC1,Gmaj);
Mat dumvec(1,2,CV_32FC1);
float Hmax=0,Lmax=0,Rmax=0,d_dum=0;
float dum1,dum2,dum3;
for (k = 0; k < size; k++)
{
temp = contour_point[k];
i = temp.y; j = temp.x;
dummy_x = (float)temp.y - x_mean; dummy_y = (float)temp.x - y_mean;
dumvec.at<float>(0, 0) = dummy_x;
dumvec.at<float>(0, 1) = dummy_y;
dum1 = Ra.dot(dumvec);
if (Hmax < dum1)
{
Hmax = dum1;
Head[0] = j; Head[1] = i;
}
dum2 = Ga.dot(dumvec);
if (dum2 > 0)
{
d_dum = Rb.dot(dumvec);
if (d_dum > 0)
{
if (Lmax < (d_dum + dum2))
{
Lmax = d_dum + dum2;
Lfoot[0] = j, Lfoot[1] = i;
}
}
}
dum3 = Gb.dot(dumvec);
if (dum3 > 0)
{
d_dum = Rb.dot(dumvec);
if (d_dum > 0)
{
if (Rmax < (d_dum + dum3))
{
Rmax = d_dum + dum3;
Rfoot[0] = j, Rfoot[1] = i;
}
}
}
}
vector<Point> Result(3);
Result[0].x = Head[0]; Result[0].y = Head[1];
Result[1].x = Lfoot[0]; Result[1].y = Lfoot[1];
Result[2].x = Rfoot[0]; Result[2].y = Rfoot[1];
return Result;
}
