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Removed also from this file the deprecated dependencies from linalg. NOW EVERY PIECE OF THE VCG relies on eigen for linalgebra.

This commit is contained in:
Paolo Cignoni 2013-03-20 08:32:53 +00:00
parent 72d67f4a11
commit 12543d68a2
1 changed files with 85 additions and 73 deletions
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76
vcg/complex/algorithms/create/extended_marching_cubes.h
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@ -30,8 +30,6 @@
#include <assert.h> #include <assert.h>
#include <vector> #include <vector>
#include <vcg/math/base.h> #include <vcg/math/base.h>
#include <vcg/math/matrix.h>
#include <vcg/math/lin_algebra.h>
#include <vcg/simplex/face/topology.h> #include <vcg/simplex/face/topology.h>
#include <vcg/complex/algorithms/update/normal.h> #include <vcg/complex/algorithms/update/normal.h>
#include <vcg/complex/algorithms/update/topology.h> #include <vcg/complex/algorithms/update/topology.h>
@ -39,6 +37,7 @@
#include <vcg/complex/algorithms/clean.h> #include <vcg/complex/algorithms/clean.h>
#include <vcg/space/point3.h> #include <vcg/space/point3.h>
#include "emc_lookup_table.h" #include "emc_lookup_table.h"
#include <eigenlib/Eigen/SVD>
namespace vcg namespace vcg
{ {
@ -336,45 +335,58 @@ namespace vcg
rank = (c > cos(_featureAngle) ? 2 : 3); rank = (c > cos(_featureAngle) ? 2 : 3);
// setup linear system (find intersection of tangent planes) // setup linear system (find intersection of tangent planes)
vcg::ndim::Matrix<double> A((unsigned int) vertices_num, 3); //--vcg::ndim::Matrix<double> A((unsigned int) vertices_num, 3);
double *b = new double[ vertices_num ]; Eigen::MatrixXd A(vertices_num,3);
//--double *b = new double[ vertices_num ];
Eigen::MatrixXd b(vertices_num,1);
for (i=0; i<vertices_num; ++i) for (i=0; i<vertices_num; ++i)
{ {
A[i][0] = normals[i][0]; //--A[i][0] = normals[i][0];
A[i][1] = normals[i][1]; //--A[i][1] = normals[i][1];
A[i][2] = normals[i][2]; //--A[i][2] = normals[i][2];
b[i] = (points[i] * normals[i]); //--b[i] = (points[i] * normals[i]);
A(i,0) = normals[i][0];
A(i,0) = normals[i][1];
A(i,0) = normals[i][2];
b(i) = (points[i] * normals[i]);
} }
// SVD of matrix A // SVD of matrix A
vcg::ndim::Matrix<double> V(3, 3); Eigen::JacobiSVD<Eigen::MatrixXd> svd(A);
double *w = new double[vertices_num]; Eigen::MatrixXd sol(3,1);
vcg::SingularValueDecomposition< typename vcg::ndim::Matrix<double> > (A, w, V, LeaveUnsorted, 100); sol=svd.solve(b);
// vcg::ndim::Matrix<double> V(3, 3);
// double *w = new double[vertices_num];
// vcg::SingularValueDecomposition< typename vcg::ndim::Matrix<double> > (A, w, V, LeaveUnsorted, 100);
// rank == 2 -> suppress smallest singular value // rank == 2 -> suppress smallest singular value
if (rank == 2) // if (rank == 2)
{ // {
double smin = DBL_MAX; // the max value, as defined in <float.h> // double smin = DBL_MAX; // the max value, as defined in <float.h>
unsigned int sminid = 0; // unsigned int sminid = 0;
unsigned int srank = std::min< unsigned int >(vertices_num, 3u); // unsigned int srank = std::min< unsigned int >(vertices_num, 3u);
for (i=0; i<srank; ++i) // for (i=0; i<srank; ++i)
{ // {
if (w[i] < smin) // if (w[i] < smin)
{ // {
smin = w[i]; // smin = w[i];
sminid = i; // sminid = i;
} // }
} // }
w[sminid] = 0.0; // w[sminid] = 0.0;
} // }
//
// SVD backsubstitution -> least squares, least norm solution x // // SVD backsubstitution -> least squares, least norm solution x
double *x = new double[3]; // double *x = new double[3];
vcg::SingularValueBacksubstitution< vcg::ndim::Matrix<double> >(A, w, V, x, b); // vcg::SingularValueBacksubstitution< vcg::ndim::Matrix<double> >(A, w, V, x, b);
// transform x to world coords // transform x to world coords
CoordType point((ScalarType) x[0], (ScalarType) x[1], (ScalarType) x[2]); //--CoordType point((ScalarType) x[0], (ScalarType) x[1], (ScalarType) x[2]);
CoordType point((ScalarType) sol[0], (ScalarType) sol[1], (ScalarType) sol[2]);
point += center; point += center;
// Safety check if the feature point found by svd is // Safety check if the feature point found by svd is
@ -386,7 +398,7 @@ namespace vcg
mean_point->SetUserBit(_featureFlag); mean_point->SetUserBit(_featureFlag);
mean_point->P() = point; mean_point->P() = point;
mean_point->N().SetZero(); mean_point->N().SetZero();
delete []x; // delete []x;
delete []points; delete []points;
delete []normals; delete []normals;
return mean_point; return mean_point;