void Noob_Position_Filter::filter_impossible_positions(std::vector<Position >& suggestions)
{
for(int i = 0; i < suggestions.size(); ++i)
{
Position& position = suggestions[i];
//x position in row 0
position(0,0) = std::max(std::min(position(0,0), position(0,1)), (float)-3.7);
position(0,1) = std::min(std::max(position(0,0), position(0,1)), (float)3.7);
//y position in row 1
position(1,0) = std::max(std::min(position(1,0), position(1,1)), (float)-2.7);
position(1,1) = std::min(std::max(position(1,0), position(1,1)), (float)2.7);
bool invalid = position(0,0) == 3.7 || position(0,1) == -3.7
|| position(1,0) == 2.7 || position(1,1) == -2.7;
//When there is no information, no overlay should be false, otherwise true
bool no_overlay = position_information.size() > 0;
if(!invalid)
{
foreach(const Eigen::Matrix2f& info, position_information)
{
Eigen::Matrix2f overlay;
overlay.row(0) = find_overlay(info.row(0), position.row(0) + Eigen::Matrix<float, 1, 2>(-way_moved(0), -way_moved(0)));
overlay.row(1) = find_overlay(info.row(1), position.row(1) + Eigen::Matrix<float, 1, 2>(-way_moved(1), -way_moved(1)));
if( overlay(0,0) >= info(0,0) - overlay_tolerance &&
overlay(1,0) >= info(1,0) - overlay_tolerance )
{
no_overlay = false;
break;
}
}
}
/**
Kreis an die Punkte (2xN-Array) anfitten.
*/
Eigen::Vector3f fit_circle(const Eigen::Array2Xf& points) {
Eigen::Array2f mean = points.rowwise().mean();
Eigen::Array2Xf uv(points.colwise() - mean);
Eigen::Array2f Sp2 = uv.square().rowwise().sum();
Eigen::Array2f Sp3 = uv.cube().rowwise().sum();
float Suv = (uv.row(0) * uv.row(1)).sum();
float Suvv = (uv.row(0) * uv.row(1).square()).sum();
float Svuu = (uv.row(0).square() * uv.row(1)).sum();
// Rechte Seite berechnen
Eigen::Vector2f b((Sp3 + Eigen::Array2f(Suvv, Svuu)) / 2);
// Linke Seite berechnen
Eigen::Matrix2f A;
A << Sp2(0), Suv, Suv, Sp2(1);
// Gleichungssystem Lösen
Eigen::Array2f mid = A.inverse() * b;
// Quadrat des Radius berechnen
float radius = sqrt(mid.square().sum() + Sp2.sum() / points.cols());
return (Eigen::Vector3f() << (mid + mean), radius).finished();
}
void FindObjectOnPlane::generateAngles(
const cv::Mat& blob_image, const cv::Point2f& test_point,
std::vector<double>& angles,
std::vector<double>& max_x,
std::vector<double>& max_y,
const image_geometry::PinholeCameraModel& model,
const jsk_recognition_utils::Plane::Ptr& plane)
{
angles.clear();
const double angle_step = 3;
std::vector<cv::Point> indices;
for (int j = 0; j < blob_image.rows; j++) {
for (int i = 0; i < blob_image.cols; i++) {
if (blob_image.at<uchar>(j, i) != 0) { // need to check
indices.push_back(cv::Point(i, j));
}
}
}
for (double angle = -180; angle < 180; angle += angle_step) {
Eigen::Vector2f ux(cos(angle/180*M_PI), sin(angle/180*M_PI));
//Eigen::Vector2f uy(sin(angle/180*M_PI), -cos(angle/180*M_PI));
cv::Point2d uy_end = getUyEnd(test_point, cv::Point2d(test_point.x + ux[0], test_point.y + ux[1]),
model,
plane);
Eigen::Vector2f uy(uy_end.x - test_point.x, uy_end.y - test_point.y);
Eigen::Matrix2f A;
A << ux[0], uy[0],
ux[1], uy[1];
bool excluded = false;
double max_alpha = -DBL_MAX;
double max_beta = -DBL_MAX;
for (size_t i = 0; i < indices.size(); i++) {
Eigen::Vector2f p_q = Eigen::Vector2f(indices[i].x, indices[i].y) - Eigen::Vector2f(test_point.x, test_point.y);
Eigen::Vector2f a_b = A.inverse() * p_q;
double alpha = a_b[0];
double beta = a_b[1];
if (alpha < 0 || beta < 0) {
excluded = true;
break;
}
if (alpha > max_alpha) {
max_alpha = alpha;
}
if (beta > max_beta) {
max_beta = beta;
}
}
if (!excluded) {
angles.push_back(angle);
max_x.push_back(max_alpha);
max_y.push_back(max_beta);
}
}
}
/** \brief Resets the FeatureWarping.
*
*/
void reset(){
affineTransform_.setIdentity();
valid_pixelCorners_ = false;
valid_bearingCorners_ = false;
valid_affineTransform_ = true;
isIdentity_ = true;
}
float PoseWithCovarianceStampedToGaussianPointCloud::gaussian(const Eigen::Vector2f& input,
const Eigen::Vector2f& mean,
const Eigen::Matrix2f& S,
const Eigen::Matrix2f& S_inv)
{
Eigen::Vector2f diff = input - mean;
if (normalize_method_ == "normalize_area") {
return normalize_value_ * 1 / (2 * M_PI * sqrt(S.determinant())) * exp(- 0.5 * (diff.transpose() * S_inv * diff)[0]);
}
else if (normalize_method_ == "normalize_height") {
return normalize_value_ * exp(- 0.5 * (diff.transpose() * S_inv * diff)[0]);
}
}
auto match(vfloat2 p, vfloat2 tr_prediction,
F A, F B, GD Ag,
const int winsize,
const float min_ev_th,
const int max_interations,
const float convergence_delta)
{
typedef typename F::value_type V;
int WS = winsize;
int ws = winsize;
int hws = ws/2;
// Gradient matrix
Eigen::Matrix2f G = Eigen::Matrix2f::Zero();
int cpt = 0;
for(int r = -hws; r <= hws; r++)
for(int c = -hws; c <= hws; c++)
{
vfloat2 n = p + vfloat2(r, c);
if (A.has(n.cast<int>()))
{
Eigen::Matrix2f m;
auto g = Ag.linear_interpolate(n);
float gx = g[0];
float gy = g[1];
m <<
gx * gx, gx * gy,
gx * gy, gy * gy;
G += m;
cpt++;
}
}
// Check minimum eigenvalue.
float min_ev = 99999.f;
auto ev = (G / cpt).eigenvalues();
for (int i = 0; i < ev.size(); i++)
if (fabs(ev[i].real()) < min_ev) min_ev = fabs(ev[i].real());
if (min_ev < min_ev_th)
return std::pair<vfloat2, float>(vfloat2(-1,-1), FLT_MAX);
Eigen::Matrix2f G1 = G.inverse();
// Precompute gs and as.
vfloat2 prediction_ = p + tr_prediction;
vfloat2 v = prediction_;
Eigen::Vector2f nk = Eigen::Vector2f::Ones();
char gs_buffer[WS * WS * sizeof(vfloat2)];
vfloat2* gs = (vfloat2*) gs_buffer;
// was: vfloat2 gs[WS * WS];
typedef plus_promotion<V> S;
char as_buffer[WS * WS * sizeof(S)];
S* as = (S*) as_buffer;
// was: S as[WS * WS];
{
for(int i = 0, r = -hws; r <= hws; r++)
{
for(int c = -hws; c <= hws; c++)
{
vfloat2 n = p + vfloat2(r, c);
if (Ag.has(n.cast<int>()))
{
gs[i] = Ag.linear_interpolate(n).template cast<float>();
as[i] = cast<S>(A.linear_interpolate(n));
}
i++;
}
}
}
auto domain = B.domain();// - border(hws + 1);
// Gradient descent
for (int k = 0; k <= max_interations && nk.norm() >= convergence_delta; k++)
{
Eigen::Vector2f bk = Eigen::Vector2f::Zero();
// Temporal difference.
int i = 0;
for(int r = -hws; r <= hws; r++)
{
for(int c = -hws; c <= hws; c++)
{
vfloat2 n = p + vfloat2(r, c);
if (Ag.has(n.cast<int>()))
{
vfloat2 n2 = v + vfloat2(r, c);
auto g = gs[i];
float dt = (cast<float>(as[i]) - cast<float>(B.linear_interpolate(n2)));
bk += Eigen::Vector2f{g[0] * dt, g[1] * dt};
}
i++;
}
}
nk = G1 * bk;
v += vfloat2{nk[0], nk[1]};
if (!domain.has(v.cast<int>()))
return std::pair<vfloat2, float>(vfloat2(0, 0), FLT_MAX);
}
// Compute the SSD.
float err = 0;
for(int r = -hws; r <= hws; r++)
for(int c = -hws; c <= hws; c++)
{
vfloat2 n2 = v + vfloat2(r, c);
int i = (r+hws) * ws + (c+hws);
{
err += fabs(cast<float>(as[i] - cast<S>(B.linear_interpolate(n2))));
cpt++;
}
}
return std::pair<vfloat2, float>(v - p, err / (cpt));
}
// Test isPatchInFrame
TEST_F(PatchTesting, isPatchInFrameWithWarping) {
Eigen::Matrix2f aff;
aff.setIdentity();
warp_.set_affineTransfrom(aff);
c_.set_c(cv::Point2f(0,0));
ASSERT_EQ(p_.isPatchInFrame(img1_,c_.get_c(),warp_.get_affineTransform(&c_)),false);
c_.set_c(cv::Point2f(patchSize_/2-0.1,patchSize_/2-0.1));
ASSERT_EQ(p_.isPatchInFrame(img1_,c_.get_c(),warp_.get_affineTransform(&c_)),false);
c_.set_c(cv::Point2f(patchSize_/2,patchSize_/2));
ASSERT_EQ(p_.isPatchInFrame(img1_,c_.get_c(),warp_.get_affineTransform(&c_)),true);
c_.set_c(cv::Point2f(patchSize_/2+0.1,patchSize_/2+0.1));
ASSERT_EQ(p_.isPatchInFrame(img1_,c_.get_c(),warp_.get_affineTransform(&c_)),true);
c_.set_c(cv::Point2f(imgSize_-patchSize_/2-0.1,imgSize_-patchSize_/2-0.1));
ASSERT_EQ(p_.isPatchInFrame(img1_,c_.get_c(),warp_.get_affineTransform(&c_)),true);
c_.set_c(cv::Point2f(imgSize_-patchSize_/2,imgSize_-patchSize_/2));
ASSERT_EQ(p_.isPatchInFrame(img1_,c_.get_c(),warp_.get_affineTransform(&c_)),true);
c_.set_c(cv::Point2f(imgSize_-patchSize_/2+0.1,imgSize_-patchSize_/2+0.1));
ASSERT_EQ(p_.isPatchInFrame(img1_,c_.get_c(),warp_.get_affineTransform(&c_)),false);
c_.set_c(cv::Point2f(imgSize_,imgSize_));
ASSERT_EQ(p_.isPatchInFrame(img1_,c_.get_c(),warp_.get_affineTransform(&c_)),false);
c_.set_c(cv::Point2f(0,0));
ASSERT_EQ(p_.isPatchInFrame(img1_,c_.get_c(),warp_.get_affineTransform(&c_),true),false);
c_.set_c(cv::Point2f(patchSize_/2+1-0.1,patchSize_/2+1-0.1));
ASSERT_EQ(p_.isPatchInFrame(img1_,c_.get_c(),warp_.get_affineTransform(&c_),true),false);
c_.set_c(cv::Point2f(patchSize_/2+1,patchSize_/2+1));
ASSERT_EQ(p_.isPatchInFrame(img1_,c_.get_c(),warp_.get_affineTransform(&c_),true),true);
c_.set_c(cv::Point2f(patchSize_/2+1+0.1,patchSize_/2+1+0.1));
ASSERT_EQ(p_.isPatchInFrame(img1_,c_.get_c(),warp_.get_affineTransform(&c_),true),true);
c_.set_c(cv::Point2f(imgSize_-patchSize_/2-1-0.1,imgSize_-patchSize_/2-1-0.1));
ASSERT_EQ(p_.isPatchInFrame(img1_,c_.get_c(),warp_.get_affineTransform(&c_),true),true);
c_.set_c(cv::Point2f(imgSize_-patchSize_/2-1,imgSize_-patchSize_/2-1));
ASSERT_EQ(p_.isPatchInFrame(img1_,c_.get_c(),warp_.get_affineTransform(&c_),true),true);
c_.set_c(cv::Point2f(imgSize_-patchSize_/2-1+0.1,imgSize_-patchSize_/2-1+0.1));
ASSERT_EQ(p_.isPatchInFrame(img1_,c_.get_c(),warp_.get_affineTransform(&c_),true),false);
c_.set_c(cv::Point2f(imgSize_,imgSize_));
ASSERT_EQ(p_.isPatchInFrame(img1_,c_.get_c(),warp_.get_affineTransform(&c_),true),false);
aff << 0, -1, 1, 0;
warp_.set_affineTransfrom(aff);
c_.set_c(cv::Point2f(0,0));
ASSERT_EQ(p_.isPatchInFrame(img1_,c_.get_c(),warp_.get_affineTransform(&c_)),false);
c_.set_c(cv::Point2f(patchSize_/2-0.1,patchSize_/2-0.1));
ASSERT_EQ(p_.isPatchInFrame(img1_,c_.get_c(),warp_.get_affineTransform(&c_)),false);
c_.set_c(cv::Point2f(patchSize_/2,patchSize_/2));
ASSERT_EQ(p_.isPatchInFrame(img1_,c_.get_c(),warp_.get_affineTransform(&c_)),true);
c_.set_c(cv::Point2f(patchSize_/2+0.1,patchSize_/2+0.1));
ASSERT_EQ(p_.isPatchInFrame(img1_,c_.get_c(),warp_.get_affineTransform(&c_)),true);
c_.set_c(cv::Point2f(imgSize_-patchSize_/2-0.1,imgSize_-patchSize_/2-0.1));
ASSERT_EQ(p_.isPatchInFrame(img1_,c_.get_c(),warp_.get_affineTransform(&c_)),true);
c_.set_c(cv::Point2f(imgSize_-patchSize_/2,imgSize_-patchSize_/2));
ASSERT_EQ(p_.isPatchInFrame(img1_,c_.get_c(),warp_.get_affineTransform(&c_)),true);
c_.set_c(cv::Point2f(imgSize_-patchSize_/2+0.1,imgSize_-patchSize_/2+0.1));
ASSERT_EQ(p_.isPatchInFrame(img1_,c_.get_c(),warp_.get_affineTransform(&c_)),false);
c_.set_c(cv::Point2f(imgSize_,imgSize_));
ASSERT_EQ(p_.isPatchInFrame(img1_,c_.get_c(),warp_.get_affineTransform(&c_)),false);
c_.set_c(cv::Point2f(0,0));
ASSERT_EQ(p_.isPatchInFrame(img1_,c_.get_c(),warp_.get_affineTransform(&c_),true),false);
c_.set_c(cv::Point2f(patchSize_/2+1-0.1,patchSize_/2+1-0.1));
ASSERT_EQ(p_.isPatchInFrame(img1_,c_.get_c(),warp_.get_affineTransform(&c_),true),false);
c_.set_c(cv::Point2f(patchSize_/2+1,patchSize_/2+1));
ASSERT_EQ(p_.isPatchInFrame(img1_,c_.get_c(),warp_.get_affineTransform(&c_),true),true);
c_.set_c(cv::Point2f(patchSize_/2+1+0.1,patchSize_/2+1+0.1));
ASSERT_EQ(p_.isPatchInFrame(img1_,c_.get_c(),warp_.get_affineTransform(&c_),true),true);
c_.set_c(cv::Point2f(imgSize_-patchSize_/2-1-0.1,imgSize_-patchSize_/2-1-0.1));
ASSERT_EQ(p_.isPatchInFrame(img1_,c_.get_c(),warp_.get_affineTransform(&c_),true),true);
c_.set_c(cv::Point2f(imgSize_-patchSize_/2-1,imgSize_-patchSize_/2-1));
ASSERT_EQ(p_.isPatchInFrame(img1_,c_.get_c(),warp_.get_affineTransform(&c_),true),true);
c_.set_c(cv::Point2f(imgSize_-patchSize_/2-1+0.1,imgSize_-patchSize_/2-1+0.1));
ASSERT_EQ(p_.isPatchInFrame(img1_,c_.get_c(),warp_.get_affineTransform(&c_),true),false);
c_.set_c(cv::Point2f(imgSize_,imgSize_));
ASSERT_EQ(p_.isPatchInFrame(img1_,c_.get_c(),warp_.get_affineTransform(&c_),true),false);
aff << cos(M_PI/6.0), -sin(M_PI/6.0), sin(M_PI/6.0), cos(M_PI/6.0);
warp_.set_affineTransfrom(aff);
c_.set_c(cv::Point2f((sin(M_PI/6.0)+cos(M_PI/6.0))*patchSize_/2+1e-6,(sin(M_PI/6.0)+cos(M_PI/6.0))*patchSize_/2+1e-6));
ASSERT_EQ(p_.isPatchInFrame(img1_,c_.get_c(),warp_.get_affineTransform(&c_)),true);
c_.set_c(cv::Point2f((sin(M_PI/6.0)+cos(M_PI/6.0))*patchSize_/2+1e-6,(sin(M_PI/6.0)+cos(M_PI/6.0))*patchSize_/2-1e-6));
ASSERT_EQ(p_.isPatchInFrame(img1_,c_.get_c(),warp_.get_affineTransform(&c_)),false);
c_.set_c(cv::Point2f((sin(M_PI/6.0)+cos(M_PI/6.0))*patchSize_/2-1e-6,(sin(M_PI/6.0)+cos(M_PI/6.0))*patchSize_/2+1e-6));
ASSERT_EQ(p_.isPatchInFrame(img1_,c_.get_c(),warp_.get_affineTransform(&c_)),false);
}
void PoseWithCovarianceStampedToGaussianPointCloud::convert(const geometry_msgs::PoseWithCovarianceStamped::ConstPtr& msg)
{
boost::mutex::scoped_lock lock(mutex_);
pcl::PointCloud<pcl::PointXYZ>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZ>);
Eigen::Vector2f mean;
Eigen::Matrix2f S;
if (cut_plane_ == "xy" || cut_plane_ == "flipped_xy") {
mean = Eigen::Vector2f(msg->pose.pose.position.x, msg->pose.pose.position.y);
S << msg->pose.covariance[0], msg->pose.covariance[1],
msg->pose.covariance[6], msg->pose.covariance[7];
}
else if (cut_plane_ == "yz" || cut_plane_ == "flipped_yz") {
mean = Eigen::Vector2f(msg->pose.pose.position.y, msg->pose.pose.position.z);
S << msg->pose.covariance[7], msg->pose.covariance[8],
msg->pose.covariance[13], msg->pose.covariance[14];
}
else if (cut_plane_ == "zx" || cut_plane_ == "flipped_zx") {
mean = Eigen::Vector2f(msg->pose.pose.position.z, msg->pose.pose.position.x);
S << msg->pose.covariance[14], msg->pose.covariance[12],
msg->pose.covariance[0], msg->pose.covariance[2];
}
double max_sigma = 0;
for (size_t i = 0; i < 2; i++) {
for (size_t j = 0; j < 2; j++) {
double sigma = sqrt(S(i, j));
if (max_sigma < sigma) {
max_sigma = sigma;
}
}
}
Eigen::Matrix2f S_inv = S.inverse();
double dx = 6.0 * max_sigma / sampling_num_;
double dy = 6.0 * max_sigma / sampling_num_;
for (double x = - 3.0 * max_sigma; x <= 3.0 * max_sigma; x += dx) {
for (double y = - 3.0 * max_sigma; y <= 3.0 * max_sigma; y += dy) {
Eigen::Vector2f diff(x, y);
Eigen::Vector2f input = diff + mean;
float z = gaussian(input, mean, S, S_inv);
pcl::PointXYZ p;
if (cut_plane_ == "xy") {
p.x = input[0];
p.y = input[1];
p.z = z + msg->pose.pose.position.z;
}
else if (cut_plane_ == "yz") {
p.y = input[0];
p.z = input[1];
p.x = z + msg->pose.pose.position.x;
}
else if (cut_plane_ == "zx") {
p.z = input[0];
p.x = input[1];
p.y = z + msg->pose.pose.position.y;
}
else if (cut_plane_ == "flipped_xy") {
p.x = input[0];
p.y = input[1];
p.z = -z + msg->pose.pose.position.z;
}
else if (cut_plane_ == "flipped_yz") {
p.y = input[0];
p.z = input[1];
p.x = -z + msg->pose.pose.position.x;
}
else if (cut_plane_ == "flipped_zx") {
p.z = input[0];
p.x = input[1];
p.y = -z + msg->pose.pose.position.y;
}
cloud->points.push_back(p);
}
}
sensor_msgs::PointCloud2 ros_cloud;
pcl::toROSMsg(*cloud, ros_cloud);
ros_cloud.header = msg->header;
pub_.publish(ros_cloud);
}
template <typename PointT> void
pcl16::approximatePolygon2D (const typename pcl16::PointCloud<PointT>::VectorType &polygon,
typename pcl16::PointCloud<PointT>::VectorType &approx_polygon,
float threshold, bool refine, bool closed)
{
approx_polygon.clear ();
if (polygon.size () < 3)
return;
std::vector<std::pair<unsigned, unsigned> > intervals;
std::pair<unsigned,unsigned> interval (0, 0);
if (closed)
{
float max_distance = .0f;
for (unsigned idx = 1; idx < polygon.size (); ++idx)
{
float distance = (polygon [0].x - polygon [idx].x) * (polygon [0].x - polygon [idx].x) +
(polygon [0].y - polygon [idx].y) * (polygon [0].y - polygon [idx].y);
if (distance > max_distance)
{
max_distance = distance;
interval.second = idx;
}
}
for (unsigned idx = 1; idx < polygon.size (); ++idx)
{
float distance = (polygon [interval.second].x - polygon [idx].x) * (polygon [interval.second].x - polygon [idx].x) +
(polygon [interval.second].y - polygon [idx].y) * (polygon [interval.second].y - polygon [idx].y);
if (distance > max_distance)
{
max_distance = distance;
interval.first = idx;
}
}
if (max_distance < threshold * threshold)
return;
intervals.push_back (interval);
std::swap (interval.first, interval.second);
intervals.push_back (interval);
}
else
{
interval.first = 0;
interval.second = static_cast<unsigned int> (polygon.size ()) - 1;
intervals.push_back (interval);
}
std::vector<unsigned> result;
// recursively refine
while (!intervals.empty ())
{
std::pair<unsigned, unsigned>& currentInterval = intervals.back ();
float line_x = polygon [currentInterval.first].y - polygon [currentInterval.second].y;
float line_y = polygon [currentInterval.second].x - polygon [currentInterval.first].x;
float line_d = polygon [currentInterval.first].x * polygon [currentInterval.second].y - polygon [currentInterval.first].y * polygon [currentInterval.second].x;
float linelen = 1.0f / sqrt (line_x * line_x + line_y * line_y);
line_x *= linelen;
line_y *= linelen;
line_d *= linelen;
float max_distance = 0.0;
unsigned first_index = currentInterval.first + 1;
unsigned max_index = 0;
// => 0-crossing
if (currentInterval.first > currentInterval.second)
{
for (unsigned idx = first_index; idx < polygon.size(); idx++)
{
float distance = fabsf (line_x * polygon[idx].x + line_y * polygon[idx].y + line_d);
if (distance > max_distance)
{
max_distance = distance;
max_index = idx;
}
}
first_index = 0;
}
for (unsigned int idx = first_index; idx < currentInterval.second; idx++)
{
float distance = fabsf (line_x * polygon[idx].x + line_y * polygon[idx].y + line_d);
if (distance > max_distance)
{
max_distance = distance;
max_index = idx;
}
}
if (max_distance > threshold)
{
std::pair<unsigned, unsigned> interval (max_index, currentInterval.second);
currentInterval.second = max_index;
intervals.push_back (interval);
}
else
{
result.push_back (currentInterval.second);
intervals.pop_back ();
}
}
approx_polygon.reserve (result.size ());
if (refine)
{
std::vector<Eigen::Vector3f> lines (result.size ());
std::reverse (result.begin (), result.end ());
for (unsigned rIdx = 0; rIdx < result.size (); ++rIdx)
{
unsigned nIdx = rIdx + 1;
if (nIdx == result.size ())
nIdx = 0;
Eigen::Vector2f centroid = Eigen::Vector2f::Zero ();
Eigen::Matrix2f covariance = Eigen::Matrix2f::Zero ();
unsigned pIdx = result[rIdx];
unsigned num_points = 0;
if (pIdx > result[nIdx])
{
num_points = static_cast<unsigned> (polygon.size ()) - pIdx;
for (; pIdx < polygon.size (); ++pIdx)
{
covariance.coeffRef (0) += polygon [pIdx].x * polygon [pIdx].x;
covariance.coeffRef (1) += polygon [pIdx].x * polygon [pIdx].y;
covariance.coeffRef (3) += polygon [pIdx].y * polygon [pIdx].y;
centroid [0] += polygon [pIdx].x;
centroid [1] += polygon [pIdx].y;
}
pIdx = 0;
}
num_points += result[nIdx] - pIdx;
for (; pIdx < result[nIdx]; ++pIdx)
{
covariance.coeffRef (0) += polygon [pIdx].x * polygon [pIdx].x;
covariance.coeffRef (1) += polygon [pIdx].x * polygon [pIdx].y;
covariance.coeffRef (3) += polygon [pIdx].y * polygon [pIdx].y;
centroid [0] += polygon [pIdx].x;
centroid [1] += polygon [pIdx].y;
}
covariance.coeffRef (2) = covariance.coeff (1);
float norm = 1.0f / float (num_points);
centroid *= norm;
covariance *= norm;
covariance.coeffRef (0) -= centroid [0] * centroid [0];
covariance.coeffRef (1) -= centroid [0] * centroid [1];
covariance.coeffRef (3) -= centroid [1] * centroid [1];
float eval;
Eigen::Vector2f normal;
eigen22 (covariance, eval, normal);
// select the one which is more "parallel" to the original line
Eigen::Vector2f direction;
direction [0] = polygon[result[nIdx]].x - polygon[result[rIdx]].x;
direction [1] = polygon[result[nIdx]].y - polygon[result[rIdx]].y;
direction.normalize ();
if (fabs (direction.dot (normal)) > float(M_SQRT1_2))
{
std::swap (normal [0], normal [1]);
normal [0] = -normal [0];
}
// needs to be on the left side of the edge
if (direction [0] * normal [1] < direction [1] * normal [0])
normal *= -1.0;
lines [rIdx].head<2> () = normal;
lines [rIdx] [2] = -normal.dot (centroid);
}
float threshold2 = threshold * threshold;
for (unsigned rIdx = 0; rIdx < lines.size (); ++rIdx)
{
unsigned nIdx = rIdx + 1;
if (nIdx == result.size ())
nIdx = 0;
Eigen::Vector3f vertex = lines [rIdx].cross (lines [nIdx]);
vertex /= vertex [2];
vertex [2] = 0.0;
PointT point;
// test whether we need another edge since the intersection point is too far away from the original vertex
Eigen::Vector3f pq = polygon [result[nIdx]].getVector3fMap () - vertex;
pq [2] = 0.0;
float distance = pq.squaredNorm ();
if (distance > threshold2)
{
// test whether the old point is inside the new polygon or outside
if ((pq [0] * lines [rIdx] [0] + pq [1] * lines [rIdx] [1] < 0.0) &&
(pq [0] * lines [nIdx] [0] + pq [1] * lines [nIdx] [1] < 0.0) )
{
float distance1 = lines [rIdx] [0] * polygon[result[nIdx]].x + lines [rIdx] [1] * polygon[result[nIdx]].y + lines [rIdx] [2];
float distance2 = lines [nIdx] [0] * polygon[result[nIdx]].x + lines [nIdx] [1] * polygon[result[nIdx]].y + lines [nIdx] [2];
point.x = polygon[result[nIdx]].x - distance1 * lines [rIdx] [0];
point.y = polygon[result[nIdx]].y - distance1 * lines [rIdx] [1];
approx_polygon.push_back (point);
vertex [0] = polygon[result[nIdx]].x - distance2 * lines [nIdx] [0];
vertex [1] = polygon[result[nIdx]].y - distance2 * lines [nIdx] [1];
}
}
point.getVector3fMap () = vertex;
approx_polygon.push_back (point);
}
}
else
{
// we have a new polygon in results, but inverted (clockwise <-> counter-clockwise)
for (std::vector<unsigned>::reverse_iterator it = result.rbegin (); it != result.rend (); ++it)
approx_polygon.push_back (polygon [*it]);
}
}
