void ConvexPolygon::calculateMatrixForm() {
//every two adjacent endpoints define a line -> inequality constraint
//first, resize A and b. x and b are column vectors
this->A = Eigen::MatrixXd (this->endpoints.size(),2);
this->b = Eigen::VectorXd (this->endpoints.size());
Eigen::Vector2d normal;
for(size_t i=1; i<endpoints.size(); i++) {
//to define the correct line direction, we also need a point on the inside of the constraint - the seed
normal(0) = endpoints[i-1](1) - endpoints[i](1);
normal(1) = endpoints[i](0) - endpoints[i-1](0);
if(normal.dot(seed) > 0) { //we want the outward pointing normal, so n.dot(s) < 0
normal = -normal;
}
normal.normalize();
b(i-1) = -endpoints[i].dot(normal); //endpoints[i];
A(i-1,0) = normal(0);
A(i-1,1) = normal(1);
}
normal(0) = endpoints.back()(1) - endpoints.front()(1);
normal(1) = endpoints.front()(0) - endpoints.back()(0);
if(normal.dot(seed) > 0) { //we want the outward pointing normal, so n.dot(s) < 0
normal = -normal;
}
normal.normalize();
b(endpoints.size()-1) = -endpoints.front().dot(normal); //endpoints[i];
A(endpoints.size()-1,0) = normal(0);
A(endpoints.size()-1,1) = normal(1);
}
void
LaserSensorModel2D::setInformationForVertexPoint(EdgeSE2PointXYCov*& edge, VertexPointXYCov*& point, LaserSensorParams& params)
{
double beamAngle = atan2(edge->measurement()(1), edge->measurement()(0));
///calculate incidence angle in point frame
Eigen::Vector2d beam = edge->measurement();
Eigen::Vector2d normal = point->normal();
beam = beam.normalized();
normal = normal.normalized();
double incidenceAngle = 0.0;
if(point->covariance() != Eigen::Matrix2d::Identity())
incidenceAngle = acos(normal.dot(beam));
double d = (tan(params.angularResolution * 0.5) * edge->measurement().norm());
///uncertainty of the surface measurement in direction of the beam
double dk = fabs(params.scale * (d / cos(incidenceAngle)));
edge->information().setIdentity();
edge->information()(0,0) = 1.0 / ((dk + params.sensorPrecision) * (dk + params.sensorPrecision));
double cError = 0.001 * edge->measurement().norm();
edge->information()(1,1) = 1.0 / (cError * cError);
Eigen::Rotation2Dd rot(beamAngle);
Eigen::Matrix2d mrot = rot.toRotationMatrix();
edge->information() = mrot * edge->information() * mrot.transpose();
}
bool ProbabilisticStereoTriangulator<CAMERA_GEOMETRY_T>::computeReprojectionError4(
const std::shared_ptr<okvis::MultiFrame>& frame, size_t camId,
size_t keypointId, const Eigen::Vector4d& homogeneousPoint,
double& outError) const {
OKVIS_ASSERT_LT_DBG(Exception, keypointId, frame->numKeypoints(camId),
"Index out of bounds");
Eigen::Vector2d y;
okvis::cameras::CameraBase::ProjectionStatus status = frame
->geometryAs<CAMERA_GEOMETRY_T>(camId)->projectHomogeneous(
homogeneousPoint, &y);
if (status == okvis::cameras::CameraBase::ProjectionStatus::Successful) {
Eigen::Vector2d k;
Eigen::Matrix2d inverseCov = Eigen::Matrix2d::Identity();
double keypointStdDev;
frame->getKeypoint(camId, keypointId, k);
frame->getKeypointSize(camId, keypointId, keypointStdDev);
keypointStdDev = 0.8 * keypointStdDev / 12.0;
inverseCov *= 1.0 / (keypointStdDev * keypointStdDev);
y -= k;
outError = y.dot(inverseCov * y);
return true;
} else
return false;
}
std::vector<cv::DMatch> Registrator3P::getInliers(const ptam::KeyFrame& kfa, const ptam::KeyFrame& kfb,
const std::vector<cv::DMatch>& matches,
const Sophus::SE3d& relPoseAB,
double threshold,
std::vector<Observation>& obs)
{
Sophus::SE3d relPoseBA = relPoseAB.inverse();
std::vector<cv::DMatch> inliers;
double thresh2 = threshold*threshold;
for (uint i = 0; i < matches.size(); i++) {
const cv::DMatch& m = matches[i];
const Eigen::Vector3d& mpa = cs_geom::toEigenVec(kfa.mapPoints[m.queryIdx]->v3RelativePos);
cv::Point2f imbcv;
int scale = 1;// << kfb.keypoints[m.trainIdx].octave;
imbcv.x = kfb.keypoints[m.trainIdx].pt.x * scale;
imbcv.y = kfb.keypoints[m.trainIdx].pt.y * scale;
Eigen::Vector2d ipb(imbcv.x, imbcv.y);
Eigen::Vector2d err = cam_[kfb.nSourceCamera].project3DtoPixel(relPoseBA*mpa) - ipb;;
if (err.dot(err) < thresh2) {
inliers.push_back(m);
obs.push_back(Observation(mpa, cam_[kfb.nSourceCamera].unprojectPixel(ipb)));
}
}
return inliers;
}
double GeometryUtils::angleLike(const Eigen::Vector2d & u, const Eigen::Vector2d & v)
{
// assume u and v are unitary
/*
double lu = length(u);
if(lu>0) u = 1/lu * u;
double lv=length(v);
if(lv>0) v = 1/lv * v;
*/
double dot_ = u.dot(v);
double det_ = u[0]*v[1] - u[1]*v[0];
double signDet = 1;
if(det_ < 0) signDet = -1;
return 2 - signDet*(dot_+1);
}
/**
Eigen::Vector2d internal_ray_lens_intersection( const Eigen::Vector2d &direction_of_internal, const Eigen::Vector2d &origin_of_internal, const Eigen::Vector2d ¢erpoint_of_sphere, double radius_of_sphere)
{
//https://people.cs.clemson.edu/~dhouse/courses/405/notes/raycast.pdf
Eigen::Vector2d return_intersection;
Eigen::Vector2d direction_of_internal_normalized = direction_of_internal.normalized();
Eigen::Vector2d o_minus_c = origin_of_internal-centerpoint_of_sphere;
double discriminant = (direction_of_internal_normalized.dot(o_minus_c))*(direction_of_internal_normalized.dot(o_minus_c))-o_minus_c.norm()*o_minus_c.norm()+radius_of_sphere*radius_of_sphere;
if (discriminant < 0)
{
throw 30;
}
else
{
double d_1 = -1*(direction_of_internal_normalized.dot(o_minus_c))+sqrt((direction_of_internal_normalized.dot(o_minus_c))*(direction_of_internal_normalized.dot(o_minus_c))-o_minus_c.norm()*o_minus_c.norm()+radius_of_sphere*radius_of_sphere);
double d_2 = -1*(direction_of_internal_normalized.dot(o_minus_c))-sqrt((direction_of_internal_normalized.dot(o_minus_c))*(direction_of_internal_normalized.dot(o_minus_c))-o_minus_c.norm()*o_minus_c.norm()+radius_of_sphere*radius_of_sphere);
if (d_2=d_1)
{
return_intersection = origin_of_internal+d_2*direction_of_internal_normalized;
}
else
{
Eigen::Vector2d return_intersection_1 = origin_of_internal+d_1*direction_of_internal_normalized;
Eigen::Vector2d return_intersection_2 = origin_of_internal+d_2*direction_of_internal_normalized;
if (return_intersection_1.y()<return_intersection_2.y())
{
return_intersection = return_intersection_1;
}
else
{
return_intersection = return_intersection_2;
}
}
cout << "lens choice 1: " << d_1 << endl;
cout << "lens choice 2: " << d_2 << endl;
}
return return_intersection;
}
**/
Eigen::Vector2d internal_ray_lens_intersection( const Eigen::Vector2d &direction_of_internal, const Eigen::Vector2d &origin_of_internal, const Eigen::Vector2d ¢erpoint_of_sphere, double radius_of_sphere)
{
// https://people.cs.clemson.edu/~dhouse/courses/405/notes/raycast.pdf
Eigen::Vector2d return_intersection;
Eigen::Vector2d direction_of_internal_normalized = direction_of_internal.normalized();
Eigen::Vector2d o_minus_c = origin_of_internal-centerpoint_of_sphere;
double t_close = direction_of_internal.dot(centerpoint_of_sphere-origin_of_internal);
Eigen::Vector2d x_close = origin_of_internal + t_close*direction_of_internal;
double discriminant = (x_close-centerpoint_of_sphere).norm();
if (discriminant < radius_of_sphere)
{
double a = sqrt(radius_of_sphere*radius_of_sphere-discriminant*discriminant);
return_intersection = origin_of_internal + (t_close-a)*direction_of_internal;
//cout << "Centerpoint of sphere : " << centerpoint_of_sphere << endl;
//cout << "radius of sphere : " << radius_of_sphere << endl;
}
else
{
throw 30;
}
return return_intersection;
}
unsigned
NurbsTools::getClosestPoint (const Eigen::Vector2d &p, const Eigen::Vector2d &dir, const vector_vec2d &data,
unsigned &idxcp)
{
if (data.empty ())
throw std::runtime_error ("[NurbsTools::getClosestPoint(2d)] Data empty.\n");
size_t idx = 0;
idxcp = 0;
double dist2 (0.0);
double dist2cp (DBL_MAX);
for (size_t i = 0; i < data.size (); i++)
{
Eigen::Vector2d v = (data[i] - p);
double d2 = v.squaredNorm ();
if (d2 < dist2cp)
{
idxcp = i;
dist2cp = d2;
}
if (d2 == 0.0)
return i;
v.normalize ();
double d1 = dir.dot (v);
if (d1 / d2 > dist2)
{
idx = i;
dist2 = d1 / d2;
}
}
return idx;
}
/*------------------------------------------------------------------------------*/
FM_INLINE
FastMarchingVertex * UnfoldTriangle(const Eigen::MatrixXd &V, const Eigen::MatrixXi &F,
const Eigen::MatrixXi &TT, const Eigen::MatrixXi &TTi,
std::vector<struct FastMarchingVertex> &vertices,
int f, int v, int v1, int v2,
FM_Float& dist, FM_Float& dot1, FM_Float& dot2)
{
const Eigen::Vector3d& p = V.row(v);// vert.GetPosition();
const Eigen::Vector3d& p1 = V.row(v1);//vert1.GetPosition();
const Eigen::Vector3d& p2 = V.row(v2);//vert2.GetPosition();
Eigen::Vector3d e1 = p1 - p;
FM_Float rNorm1 = e1.norm(); //~e1
e1.normalize(); // e1 /= rNorm1;
Eigen::Vector3d e2 = p2 - p;
FM_Float rNorm2 = e2.norm(); // ~e2;
e2.normalize(); // e2 /= rNorm2;
FM_Float dot = e1.adjoint()*e2;// e1*e2;
FM_ASSERT(dot < 0);
/* the equation of the lines defining the unfolding region [e.g. line 1 : {x ; <x,eq1>=0} ]*/
Eigen::Vector2d eq1 = Eigen::Vector2d(dot, sqrt(1 - dot*dot));
Eigen::Vector2d eq2 = Eigen::Vector2d(1, 0);
/* position of the 2 points on the unfolding plane */
Eigen::Vector2d x1(rNorm1, 0);
Eigen::Vector2d x2 = eq1*rNorm2;
/* keep track of the starting point */
Eigen::Vector2d xstart1 = x1;
Eigen::Vector2d xstart2 = x2;
FastMarchingVertex* pV1 = &(vertices[v1]);
FastMarchingVertex* pV2 = &(vertices[v2]);
int cur_f, cur_v;
get_oppisite_f_v(F, TT,TTi, f,v, cur_f, cur_v);
//FM_GeodesicFace* pCurFace = (FM_GeodesicFace*)CurFace.GetFaceNeighbor(vert);
int nNum = 0;
while (nNum < 50 && cur_f != -1) // NULL)
{
// FastMarchingVertex* pV = (FastMarchingVertex*)pCurFace->GetVertex(*pV1, *pV2); //opposite vertex to face and edge(pV1,pV2)
// FM_ASSERT(pV != NULL);
FastMarchingVertex* pV = &(vertices[cur_v]); //opposite vertex to face and vert
/*
e1 = pV2->GetPosition() - pV1->GetPosition();
FM_Float rNorm1 = ~e1;
e1 /= rNorm1;
e2 = pV->GetPosition() - pV1->GetPosition();
FM_Float rNorm2 = ~e2;
e2 /= rNorm2;
*/
Eigen::Vector3d e1 = V.row(pV2->vid) - V.row(pV1->vid);
FM_Float rNorm1 = e1.norm(); //~e1
e1.normalize(); // e1 /= rNorm1;
Eigen::Vector3d e2 = V.row(pV->vid) - V.row(pV1->vid);
FM_Float rNorm2 = e2.norm(); // ~e2;
e2.normalize(); // e2 /= rNorm2;
/* compute the position of the new point x on the unfolding plane (via a rotation of -alpha on (x2-x1)/rNorm1 )
| cos(alpha) sin(alpha)|
x = |-sin(alpha) cos(alpha)| * [x2-x1]*rNorm2/rNorm1 + x1 where cos(alpha)=dot
*/
Eigen::Vector2d vv = (x2 - x1)*rNorm2 / rNorm1;
dot = e1.adjoint()*e2; //e1*e2;
// Eigen::Vector2d x = vv.Rotate2D();////vv.Rotate(-acos(dot)) + x1;
Eigen::Rotation2D<double> rot2(-acos(dot));
Eigen::Vector2d x = rot2*vv + x1; //dhw to check
/* compute the intersection points.
We look for x=x1+lambda*(x-x1) or x=x2+lambda*(x-x2) with <x,eqi>=0, so */
FM_Float lambda11 = -(x1.dot(eq1)) / ((x - x1).dot(eq1)); //-(x1*eq1) / ((x - x1)*eq1); // left most
FM_Float lambda12 = -(x1.dot(eq2)) / ((x - x1).dot(eq2)); //-(x1*eq2) / ((x - x1)*eq2); // right most
FM_Float lambda21 = -(x2.dot(eq1)) / ((x - x2).dot(eq1)); //-(x2*eq1) / ((x - x2)*eq1); // left most
FM_Float lambda22 = -(x2.dot(eq2)) / ((x - x2).dot(eq2)); //-(x2*eq2) / ((x - x2)*eq2); // right most
bool bIntersect11 = (lambda11 >= 0) && (lambda11 <= 1);
bool bIntersect12 = (lambda12 >= 0) && (lambda12 <= 1);
bool bIntersect21 = (lambda21 >= 0) && (lambda21 <= 1);
bool bIntersect22 = (lambda22 >= 0) && (lambda22 <= 1);
if (bIntersect11 && bIntersect12)
{
// FM_ASSERT( !bIntersect21 && !bIntersect22 );
/* we should unfold on edge [x x1] */
// pCurFace = (FM_GeodesicFace*)pCurFace->GetFaceNeighbor(*pV2);
f = cur_f;
get_oppisite_f_v(F, TT,TTi, f, pV2->vid, cur_f, cur_v);
pV2 = pV;
x2 = x;
}
else if (bIntersect21 && bIntersect22)
{
// FM_ASSERT( !bIntersect11 && !bIntersect12 );
/* we should unfold on edge [x x2] */
// pCurFace = (FM_GeodesicFace*)pCurFace->GetFaceNeighbor(*pV1);
f = cur_f;
get_oppisite_f_v(F, TT,TTi, f, pV1->vid, cur_f, cur_v);
pV1 = pV;
x1 = x;
}
else
{
FM_ASSERT(bIntersect11 && !bIntersect12 &&
!bIntersect21 && bIntersect22);
/* that's it, we have found the point */
dist = x.norm(); // ~x;
dot1 = x.dot(xstart1) / (dist * xstart1.norm());// ~xstart1);
dot2 = x.dot(xstart2) / (dist * xstart2.norm());// ~xstart2);
return pV;
}
nNum++;
}
return NULL;
}
void KeyEdge::prepareSculptPreserveTangents_()
{
const bool preserveTangentEdges = false;
if (!preserveTangentEdges)
return;
// find instant edges where tangency must be preserved
sculpt_beginLeftDer_ = geometry()->der(0);
sculpt_beginRightDer_ = geometry()->der(geometry()->length());
sculpt_keepRightAsLeft_.clear();
sculpt_keepLeftAsLeft_.clear();
sculpt_keepLeftAsRight_.clear();
sculpt_keepRightAsRight_.clear();
sculpt_keepMyselfTangent_ = false;
if (preserveTangentEdges)
{
double dotThreshold = 0.9;
if(startVertex_)
{
KeyEdgeSet leftEdges = startVertex_->spatialStar();
leftEdges.remove(this);
foreach(KeyEdge * ie, leftEdges)
{
if(ie->endVertex_ == startVertex_)
{
Eigen::Vector2d rightDer = ie->geometry()->der(ie->geometry()->length());
double dot = rightDer.dot(sculpt_beginLeftDer_);
if(dot > dotThreshold)
sculpt_keepRightAsLeft_ << ie;
}
if(ie->startVertex_ == startVertex_)
{
Eigen::Vector2d rightDer = - ie->geometry()->der(0);
double dot = rightDer.dot(sculpt_beginLeftDer_);
if(dot > dotThreshold)
sculpt_keepLeftAsLeft_ << ie;
}
}
}
if(endVertex_)
{
KeyEdgeSet rightEdges = endVertex_->spatialStar();
rightEdges.remove(this);
foreach(KeyEdge * ie, rightEdges)
{
// For now, disabling tangent preservation for 0-edge loops
if(ie == this)
continue;
if(ie->startVertex_ == endVertex_)
{
Eigen::Vector2d leftDer = ie->geometry()->der(0);
double dot = leftDer.dot(sculpt_beginRightDer_);
if(dot > dotThreshold)
sculpt_keepLeftAsRight_ << ie;
}
if(ie->endVertex_ == endVertex_)
{
Eigen::Vector2d leftDer = - ie->geometry()->der(ie->geometry()->length());
double dot = leftDer.dot(sculpt_beginRightDer_);
if(dot > dotThreshold)
sculpt_keepRightAsRight_ << ie;
}
}
}
if(endVertex_ && (endVertex_ == startVertex_))
{
// For now, disabling tangent preservation for 0-edge loops
// What's below doesn't work, because continueSculpt assume
// no resampling has occured since prepareSculpt
//double dot = sculpt_beginRightDer_.dot(sculpt_beginLeftDer_);
//if(dot > dotThreshold)
//{
// sculpt_keepMyselfTangent_ = true;
//}
}
}
}
Sophus::SE3d Registrator3P::solve(const ptam::KeyFrame& kfa, const ptam::KeyFrame& kfb,
const std::vector<cv::DMatch>& matches)
{
if (matches.size() < 5)
return Sophus::SE3d();
// Generate nHyp_ hypotheses:
std::vector<Hypothesis3P> hyp;
nHyp_ = matches.size() * N_SAMPLES;
while (hyp.size() < nHyp_) {
std::vector<int> sampleInd;
// choose x random matches
randSampleNoReplacement(matches.size(), N_SAMPLES, sampleInd);
std::vector<cv::Point3f> mapPointsA(N_SAMPLES);
std::vector<cv::Point2f> imagePointsB(N_SAMPLES);
for (int i = 0; i < N_SAMPLES; i++) {
int ind = sampleInd[i];
const Eigen::Vector3d& mpa = cs_geom::toEigenVec(kfa.mapPoints[matches[ind].queryIdx]->v3RelativePos);
mapPointsA[i] = cv::Point3f(mpa[0], mpa[1], mpa[2]);
int scale = 1;// << kfb.keypoints[matches[ind].trainIdx].octave;
imagePointsB[i].x = kfb.keypoints[matches[ind].trainIdx].pt.x;// * scale;
imagePointsB[i].y = kfb.keypoints[matches[ind].trainIdx].pt.y;// * scale;
}
cv::Mat rvec(3,1,cv::DataType<double>::type);
cv::Mat tvec(3,1,cv::DataType<double>::type);
/// here we need the model of camera B!
int camNum = kfb.nSourceCamera;
// cout << "cv::solvePnP... cam " << camNum << endl;
if (cv::solvePnP(mapPointsA, imagePointsB, cam_[camNum].K(), cam_[camNum].D(), rvec, tvec, false, cv::EPNP)) {
Sophus::SE3d se3;
Eigen::Vector3d r;
cv::cv2eigen(rvec, r);
cv::cv2eigen(tvec, se3.translation());
se3.so3() = Sophus::SO3d::exp(r);
hyp.push_back(Hypothesis3P(se3));
}
// cout << "cv::solvePnP finish..." << endl;
}
if (!hyp.size())
return Sophus::SE3d();
// Preemptive scoring
// determine the order in which observations will be evaluated
std::vector<int> oInd;
randPerm(matches.size(),oInd);
// start preemptive scoring
int i = 0;
int pr = preemption(i, nHyp_, blockSize_);
while (i < nMaxObs_ && i < (int) matches.size() && pr > 1) {
// observation oInd(i) consists of one pair of points:
const cv::DMatch& match = matches[oInd[i]];
const Eigen::Vector3d& mpa = cs_geom::toEigenVec(kfa.mapPoints[match.queryIdx]->v3RelativePos);
const cv::Point2f& imbcv = kfb.keypoints[match.trainIdx].pt;
int scale = 1;// << kfb.keypoints[match.trainIdx].octave;
Eigen::Vector2d imb(imbcv.x * scale, imbcv.y * scale);
// update score for all hypotheses w.r.t. observation oInd(i)
for (int h = 0; h < (int) hyp.size(); h++) {
Eigen::Vector2d err = cam_[kfb.nSourceCamera].project3DtoPixel(hyp[h].relPose*mpa) - imb;
hyp[h].score -= log(1.0 + err.dot(err));
// hyp[h].score += err.dot(err) < 3.0;
}
i++;
int prnext = preemption(i, nHyp_, blockSize_);
if (prnext != pr) {
// select best hypotheses
std::nth_element(hyp.begin(), hyp.begin() + prnext, hyp.end(), Hypothesis3P::compare);
// now the first prnext elements of h contain the best hypotheses, erase the rest
hyp.erase(hyp.begin() + prnext, hyp.end());
}
pr = prnext;
}
// preemptive scoring is done
// select the single best hypothesis of possibly more than one remaining
std::nth_element(hyp.begin(),hyp.begin() + 1, hyp.end(), Hypothesis3P::compare);
// std::cout << "preemptive scoring using " << i << " observations done." << std::endl;
// std::cout << hyp[0].relPose.inverse().matrix();
return hyp[0].relPose.inverse();
}
void
FittingCurve2dSDM::assembleInterior (double wInt, double sigma2, unsigned &row)
{
unsigned nInt = m_data->interior.size ();
bool wFunction (true);
double ds = 1.0 / (2.0 * sigma2);
m_data->interior_line_start.clear ();
m_data->interior_line_end.clear ();
m_data->interior_error.clear ();
m_data->interior_normals.clear ();
unsigned updateTNR (false);
if (m_data->interior_ncps_prev != m_nurbs.CVCount ())
{
if (!m_quiet)
printf ("[FittingCurve2dSDM::assembleInterior] updating T, N, rho\n");
m_data->interior_tangents.clear ();
m_data->interior_normals.clear ();
m_data->interior_rho.clear ();
m_data->interior_ncps_prev = m_nurbs.CVCount ();
updateTNR = true;
}
unsigned i1 (0);
unsigned i2 (0);
for (unsigned p = 0; p < nInt; p++)
{
Eigen::Vector2d &pcp = m_data->interior[p];
// inverse mapping
double param;
Eigen::Vector2d pt, t, n;
double error;
if (p < m_data->interior_param.size ())
{
param = inverseMapping (m_nurbs, pcp, m_data->interior_param[p], error, pt, t, in_max_steps, in_accuracy);
m_data->interior_param[p] = param;
}
else
{
param = findClosestElementMidPoint (m_nurbs, pcp);
param = inverseMapping (m_nurbs, pcp, param, error, pt, t, in_max_steps, in_accuracy);
m_data->interior_param.push_back (param);
}
m_data->interior_error.push_back (error);
double dt, kappa, rho, rho_prev;
Eigen::Vector2d n_prev, t_prev;
double pointAndTangents[6];
m_nurbs.Evaluate (param, 2, 2, pointAndTangents);
pt (0) = pointAndTangents[0];
pt (1) = pointAndTangents[1];
t (0) = pointAndTangents[2];
t (1) = pointAndTangents[3];
n (0) = pointAndTangents[4];
n (1) = pointAndTangents[5];
dt = t.norm ();
t /= dt;
Eigen::Vector2d in (t (1), -t (0));
n /= dt; // TODO something is wrong with the normal from nurbs.Evaluate(...)
n = in * in.dot (n);
kappa = n.norm ();
rho = (1.0 / kappa);
n *= rho;
if (!updateTNR)
{
if (m_data->interior_rho.size () != nInt)
{
printf ("[FittingCurve2dSDM::assembleInterior] ERROR: size does not match\n");
}
else
{
n_prev = m_data->interior_normals[p];
t_prev = m_data->interior_tangents[p];
rho_prev = m_data->interior_rho[p];
// m_data->interior_normals[p] = n;
// m_data->interior_tangents[p] = t;
// m_data->interior_rho[p] = rho;
}
}
else
{
m_data->interior_tangents.push_back (t);
m_data->interior_normals.push_back (n);
m_data->interior_rho.push_back (rho);
n_prev = n;
t_prev = t;
rho_prev = rho;
}
double d;
if ((pcp - pt).dot (n) >= 0.0)
{
d = (pcp - pt).norm ();
i1++;
}
else
{
d = -(pcp - pt).norm ();
i2++;
}
// evaluate if point lies inside or outside the closed curve
Eigen::Vector3d a (pcp (0) - pt (0), pcp (1) - pt (1), 0.0);
Eigen::Vector3d b (t (0), t (1), 0.0);
Eigen::Vector3d z = a.cross (b);
if (p < m_data->interior_weight.size ())
wInt = m_data->interior_weight[p];
if (p < m_data->interior_weight_function.size ())
wFunction = m_data->interior_weight_function[p];
m_data->interior_line_start.push_back (pt);
m_data->interior_line_end.push_back (pcp);
double w (wInt);
if (z (2) > 0.0 && wFunction)
w = wInt * exp (-(error * error) * ds);
if (w > 1e-6) // avoids ill-conditioned matrix
addPointConstraint (m_data->interior_param[p], m_data->interior[p], n_prev, t_prev, rho_prev, d, w, row);
}
// printf("[FittingCurve2dSDM::assembleInterior] d>0: %d d<0: %d\n", i1, i2);
}
double
FittingCurve2d::inverseMapping (const ON_NurbsCurve &nurbs, const Eigen::Vector2d &pt, const double &hint,
double &error, Eigen::Vector2d &p, Eigen::Vector2d &t, double rScale, int maxSteps,
double accuracy, bool quiet)
{
if (nurbs.Order () == 2)
return inverseMappingO2 (nurbs, pt, error, p, t);
int cp_red = (nurbs.m_order - 2);
int ncpj = (nurbs.m_cv_count - 2 * cp_red);
double pointAndTangents[4];
double current, delta;
Eigen::Vector2d r;
std::vector<double> elements = getElementVector (nurbs);
double minU = elements[0];
double maxU = elements[elements.size () - 1];
current = hint;
for (int k = 0; k < maxSteps; k++)
{
nurbs.Evaluate (current, 1, 2, pointAndTangents);
p (0) = pointAndTangents[0];
p (1) = pointAndTangents[1];
t (0) = pointAndTangents[2];
t (1) = pointAndTangents[3];
r = p - pt;
// step width control
int E = findElement (current, elements);
double e = elements[E + 1] - elements[E];
delta = -(0.5 * e * rScale) * r.dot (t) / t.norm (); // A.ldlt().solve(b);
// e = 0.5 * std::abs<double> (e);
// if (delta > e)
// delta = e;
// if (delta < -e)
// delta = -e;
if (std::abs<double> (delta) < accuracy)
{
error = r.norm ();
return current;
}
else
{
current = current + delta;
if (current < minU)
current = maxU - (minU - current);
else if (current > maxU)
current = minU + (current - maxU);
}
}
error = r.norm ();
if (!quiet)
{
printf ("[FittingCurve2d::inverseMapping] Warning: Method did not converge (%e %d).\n", accuracy, maxSteps);
printf ("[FittingCurve2d::inverseMapping] hint: %f current: %f delta: %f error: %f\n", hint, current, delta, error);
}
return current;
}
Eigen::Vector2d final_ray_scene_intersection( const Eigen::Vector2d &scene_point, const Eigen::Vector2d &final_ray_normalized, const Eigen::Vector2d &intersection_point_on_curved_surface)
{
double d = (scene_point-intersection_point_on_curved_surface).dot(Eigen::Vector2d(0,-1))/(final_ray_normalized.dot(Eigen::Vector2d(0,-1)));
return final_ray_normalized*d+intersection_point_on_curved_surface;
}
