38 #include <pcl/common/eigen.h>
60 accumulated_weight_ += weight;
61 float alpha = weight/accumulated_weight_;
63 Eigen::Vector3f diff1 = point - mean1_, diff2 = corresponding_point - mean2_;
64 covariance_ = (1.0f-alpha)*(covariance_ + alpha * (diff2 * diff1.transpose()));
66 mean1_ += alpha*(diff1);
67 mean2_ += alpha*(diff2);
71 inline Eigen::Affine3f
75 Eigen::JacobiSVD<Eigen::Matrix<float, 3, 3> > svd (covariance_, Eigen::ComputeFullU | Eigen::ComputeFullV);
76 const Eigen::Matrix<float, 3, 3>& u = svd.matrixU(),
78 Eigen::Matrix<float, 3, 3> s;
80 if (u.determinant()*v.determinant() < 0.0f)
83 Eigen::Matrix<float, 3, 3> r = u * s * v.transpose();
84 Eigen::Vector3f t = mean2_ - r*mean1_;
87 ret(0,0)=r(0,0); ret(0,1)=r(0,1); ret(0,2)=r(0,2); ret(0,3)=t(0);
88 ret(1,0)=r(1,0); ret(1,1)=r(1,1); ret(1,2)=r(1,2); ret(1,3)=t(1);
89 ret(2,0)=r(2,0); ret(2,1)=r(2,1); ret(2,2)=r(2,2); ret(2,3)=t(2);
90 ret(3,0)=0.0f; ret(3,1)=0.0f; ret(3,2)=0.0f; ret(3,3)=1.0f;
void reset()
Reset the object to work with a new data set.
unsigned int no_of_samples_
float accumulated_weight_
void add(const Eigen::Vector3f &point, const Eigen::Vector3f &corresponding_point, float weight=1.0)
Add a new sample.
Eigen::Affine3f getTransformation()
Calculate the transformation that will best transform the points into their correspondences.
Eigen::Matrix< float, 3, 3 > covariance_