template <typename PointT> inline unsigned int
pcl::computeCovarianceMatrix (const pcl::PointCloud<PointT> &cloud,
Eigen::Matrix3f &covariance_matrix)
{
// create the buffer on the stack which is much faster than using cloud.points[indices[i]] and centroid as a buffer
Eigen::Matrix<float, 1, 6, Eigen::RowMajor> accu = Eigen::Matrix<float, 1, 6, Eigen::RowMajor>::Zero ();
unsigned int point_count;
if (cloud.is_dense)
{
point_count = static_cast<unsigned int> (cloud.size ());
// For each point in the cloud
for (size_t i = 0; i < point_count; ++i)
{
accu [0] += cloud[i].x * cloud[i].x;
accu [1] += cloud[i].x * cloud[i].y;
accu [2] += cloud[i].x * cloud[i].z;
accu [3] += cloud[i].y * cloud[i].y;
accu [4] += cloud[i].y * cloud[i].z;
accu [5] += cloud[i].z * cloud[i].z;
}
}
else
{
point_count = 0;
for (size_t i = 0; i < cloud.points.size (); ++i)
{
if (!isFinite (cloud[i]))
continue;
accu [0] += cloud[i].x * cloud[i].x;
accu [1] += cloud[i].x * cloud[i].y;
accu [2] += cloud[i].x * cloud[i].z;
accu [3] += cloud[i].y * cloud[i].y;
accu [4] += cloud[i].y * cloud[i].z;
accu [5] += cloud[i].z * cloud[i].z;
++point_count;
}
}
if (point_count != 0)
{
accu /= static_cast<float> (point_count);
covariance_matrix.coeffRef (0) = accu [0];
covariance_matrix.coeffRef (1) = covariance_matrix.coeffRef (3) = accu [1];
covariance_matrix.coeffRef (2) = covariance_matrix.coeffRef (6) = accu [2];
covariance_matrix.coeffRef (4) = accu [3];
covariance_matrix.coeffRef (5) = covariance_matrix.coeffRef (7) = accu [4];
covariance_matrix.coeffRef (8) = accu [5];
}
return (point_count);
}
template <typename PointT> inline unsigned int
pcl::computeCovarianceMatrix (const pcl::PointCloud<PointT> &cloud,
const std::vector<int> &indices,
Eigen::Matrix3f &covariance_matrix)
{
Eigen::Matrix<float, 1, 6, Eigen::RowMajor> accu = Eigen::Matrix<float, 1, 6, Eigen::RowMajor>::Zero ();
unsigned int point_count;
if (cloud.is_dense)
{
point_count = static_cast<unsigned int> (indices.size ());
for (std::vector<int>::const_iterator iIt = indices.begin (); iIt != indices.end (); ++iIt)
{
//const PointT& point = cloud[*iIt];
accu [0] += cloud[*iIt].x * cloud[*iIt].x;
accu [1] += cloud[*iIt].x * cloud[*iIt].y;
accu [2] += cloud[*iIt].x * cloud[*iIt].z;
accu [3] += cloud[*iIt].y * cloud[*iIt].y;
accu [4] += cloud[*iIt].y * cloud[*iIt].z;
accu [5] += cloud[*iIt].z * cloud[*iIt].z;
}
}
else
{
point_count = 0;
for (std::vector<int>::const_iterator iIt = indices.begin (); iIt != indices.end (); ++iIt)
{
if (!isFinite (cloud[*iIt]))
continue;
++point_count;
accu [0] += cloud[*iIt].x * cloud[*iIt].x;
accu [1] += cloud[*iIt].x * cloud[*iIt].y;
accu [2] += cloud[*iIt].x * cloud[*iIt].z;
accu [3] += cloud[*iIt].y * cloud[*iIt].y;
accu [4] += cloud[*iIt].y * cloud[*iIt].z;
accu [5] += cloud[*iIt].z * cloud[*iIt].z;
}
}
if (point_count != 0)
{
accu /= static_cast<float> (point_count);
covariance_matrix.coeffRef (0) = accu [0];
covariance_matrix.coeffRef (1) = covariance_matrix.coeffRef (3) = accu [1];
covariance_matrix.coeffRef (2) = covariance_matrix.coeffRef (6) = accu [2];
covariance_matrix.coeffRef (4) = accu [3];
covariance_matrix.coeffRef (5) = covariance_matrix.coeffRef (7) = accu [4];
covariance_matrix.coeffRef (8) = accu [5];
}
return (point_count);
}
void
pcl::getCameraMatrixFromProjectionMatrix (
const Eigen::Matrix<float, 3, 4, Eigen::RowMajor>& projection_matrix,
Eigen::Matrix3f& camera_matrix)
{
Eigen::Matrix3f KR = projection_matrix.topLeftCorner <3, 3> ();
Eigen::Matrix3f KR_KRT = KR * KR.transpose ();
Eigen::Matrix3f cam = KR_KRT / KR_KRT.coeff (8);
memset (&(camera_matrix.coeffRef (0)), 0, sizeof (Eigen::Matrix3f::Scalar) * 9);
camera_matrix.coeffRef (8) = 1.0;
if (camera_matrix.Flags & Eigen::RowMajorBit)
{
camera_matrix.coeffRef (2) = cam.coeff (2);
camera_matrix.coeffRef (5) = cam.coeff (5);
camera_matrix.coeffRef (4) = static_cast<float> (std::sqrt (cam.coeff (4) - cam.coeff (5) * cam.coeff (5)));
camera_matrix.coeffRef (1) = (cam.coeff (1) - cam.coeff (2) * cam.coeff (5)) / camera_matrix.coeff (4);
camera_matrix.coeffRef (0) = static_cast<float> (std::sqrt (cam.coeff (0) - camera_matrix.coeff (1) * camera_matrix.coeff (1) - cam.coeff (2) * cam.coeff (2)));
}
else
{
camera_matrix.coeffRef (6) = cam.coeff (2);
camera_matrix.coeffRef (7) = cam.coeff (5);
camera_matrix.coeffRef (4) = static_cast<float> (std::sqrt (cam.coeff (4) - cam.coeff (5) * cam.coeff (5)));
camera_matrix.coeffRef (3) = (cam.coeff (1) - cam.coeff (2) * cam.coeff (5)) / camera_matrix.coeff (4);
camera_matrix.coeffRef (0) = static_cast<float> (std::sqrt (cam.coeff (0) - camera_matrix.coeff (3) * camera_matrix.coeff (3) - cam.coeff (2) * cam.coeff (2)));
}
}
template <typename PointT> inline unsigned int
pcl::computeMeanAndCovarianceMatrix (const pcl::PointCloud<PointT> &cloud,
const std::vector<int> &indices,
Eigen::Matrix3f &covariance_matrix,
Eigen::Vector4f ¢roid)
{
// create the buffer on the stack which is much faster than using cloud.points[indices[i]] and centroid as a buffer
Eigen::Matrix<float, 1, 9, Eigen::RowMajor> accu = Eigen::Matrix<float, 1, 9, Eigen::RowMajor>::Zero ();
size_t point_count;
if (cloud.is_dense)
{
point_count = indices.size ();
for (std::vector<int>::const_iterator iIt = indices.begin (); iIt != indices.end (); ++iIt)
{
//const PointT& point = cloud[*iIt];
accu [0] += cloud[*iIt].x * cloud[*iIt].x;
accu [1] += cloud[*iIt].x * cloud[*iIt].y;
accu [2] += cloud[*iIt].x * cloud[*iIt].z;
accu [3] += cloud[*iIt].y * cloud[*iIt].y;
accu [4] += cloud[*iIt].y * cloud[*iIt].z;
accu [5] += cloud[*iIt].z * cloud[*iIt].z;
accu [6] += cloud[*iIt].x;
accu [7] += cloud[*iIt].y;
accu [8] += cloud[*iIt].z;
}
}
else
{
point_count = 0;
for (std::vector<int>::const_iterator iIt = indices.begin (); iIt != indices.end (); ++iIt)
{
if (!isFinite (cloud[*iIt]))
continue;
++point_count;
accu [0] += cloud[*iIt].x * cloud[*iIt].x;
accu [1] += cloud[*iIt].x * cloud[*iIt].y;
accu [2] += cloud[*iIt].x * cloud[*iIt].z;
accu [3] += cloud[*iIt].y * cloud[*iIt].y; // 4
accu [4] += cloud[*iIt].y * cloud[*iIt].z; // 5
accu [5] += cloud[*iIt].z * cloud[*iIt].z; // 8
accu [6] += cloud[*iIt].x;
accu [7] += cloud[*iIt].y;
accu [8] += cloud[*iIt].z;
}
}
accu /= static_cast<float> (point_count);
//Eigen::Vector3f vec = accu.tail<3> ();
//centroid.head<3> () = vec;//= accu.tail<3> ();
//centroid.head<3> () = accu.tail<3> (); -- does not compile with Clang 3.0
centroid[0] = accu[6]; centroid[1] = accu[7]; centroid[2] = accu[8];
centroid[3] = 0;
covariance_matrix.coeffRef (0) = accu [0] - accu [6] * accu [6];
covariance_matrix.coeffRef (1) = accu [1] - accu [6] * accu [7];
covariance_matrix.coeffRef (2) = accu [2] - accu [6] * accu [8];
covariance_matrix.coeffRef (4) = accu [3] - accu [7] * accu [7];
covariance_matrix.coeffRef (5) = accu [4] - accu [7] * accu [8];
covariance_matrix.coeffRef (8) = accu [5] - accu [8] * accu [8];
covariance_matrix.coeffRef (3) = covariance_matrix.coeff (1);
covariance_matrix.coeffRef (6) = covariance_matrix.coeff (2);
covariance_matrix.coeffRef (7) = covariance_matrix.coeff (5);
return (static_cast<unsigned int> (point_count));
}
template <typename PointT> inline unsigned int
pcl::computeMeanAndCovarianceMatrix (const pcl::PointCloud<PointT> &cloud,
Eigen::Matrix3f &covariance_matrix,
Eigen::Vector4f ¢roid)
{
// create the buffer on the stack which is much faster than using cloud.points[indices[i]] and centroid as a buffer
Eigen::Matrix<float, 1, 9, Eigen::RowMajor> accu = Eigen::Matrix<float, 1, 9, Eigen::RowMajor>::Zero ();
unsigned point_count;
if (cloud.is_dense)
{
point_count = cloud.size ();
// For each point in the cloud
for (size_t i = 0; i < point_count; ++i)
{
accu [0] += cloud[i].x * cloud[i].x;
accu [1] += cloud[i].x * cloud[i].y;
accu [2] += cloud[i].x * cloud[i].z;
accu [3] += cloud[i].y * cloud[i].y; // 4
accu [4] += cloud[i].y * cloud[i].z; // 5
accu [5] += cloud[i].z * cloud[i].z; // 8
accu [6] += cloud[i].x;
accu [7] += cloud[i].y;
accu [8] += cloud[i].z;
}
}
else
{
point_count = 0;
for (size_t i = 0; i < cloud.points.size (); ++i)
{
if (!isFinite (cloud[i]))
continue;
accu [0] += cloud[i].x * cloud[i].x;
accu [1] += cloud[i].x * cloud[i].y;
accu [2] += cloud[i].x * cloud[i].z;
accu [3] += cloud[i].y * cloud[i].y;
accu [4] += cloud[i].y * cloud[i].z;
accu [5] += cloud[i].z * cloud[i].z;
accu [6] += cloud[i].x;
accu [7] += cloud[i].y;
accu [8] += cloud[i].z;
++point_count;
}
}
accu /= (float) point_count;
if (point_count != 0)
{
centroid.head<3> () = accu.tail<3> ();
centroid[3] = 0;
covariance_matrix.coeffRef (0) = accu [0] - accu [6] * accu [6];
covariance_matrix.coeffRef (1) = accu [1] - accu [6] * accu [7];
covariance_matrix.coeffRef (2) = accu [2] - accu [6] * accu [8];
covariance_matrix.coeffRef (4) = accu [3] - accu [7] * accu [7];
covariance_matrix.coeffRef (5) = accu [4] - accu [7] * accu [8];
covariance_matrix.coeffRef (8) = accu [5] - accu [8] * accu [8];
covariance_matrix.coeffRef (3) = covariance_matrix.coeff (1);
covariance_matrix.coeffRef (6) = covariance_matrix.coeff (2);
covariance_matrix.coeffRef (7) = covariance_matrix.coeff (5);
}
return (point_count);
}