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Commit 6d263b10 authored by Angel Santamaria-Navarro's avatar Angel Santamaria-Navarro
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WIP on trifocal tensor

parent b82f3b21
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......@@ -44,13 +44,61 @@ void TrifocalTensor::fillTensor(const Eigen::VectorXd& tensorVector)
}
}
void TrifocalTensor::computeTensor(const Eigen::MatrixXd& list1, const Eigen::MatrixXd& list2, const Eigen::MatrixXd& list3)
void TrifocalTensor::getRandomCandidates(const int& min_points, const Eigen::MatrixXd& list1, const Eigen::MatrixXd& list2, const Eigen::MatrixXd& list3, Eigen::MatrixXd& l1, Eigen::MatrixXd& l2, Eigen::MatrixXd& l3)
{
std::random_device rd; //Will be used to obtain a seed for the random number engine
std::mt19937 gen(rd()); //Standard mersenne_twister_engine seeded with rd()
std::uniform_int_distribution<> dis(0, min_points-1);
Eigen::VectorXd idx = Eigen::VectorXd::Zero(min_points);
for (int n=0; n<min_points; ++n)
{
int num = dis(gen);
idx(n) = num;
for (int ii=0; ii<n; ++ii)
{
if (idx(ii)==num)
{
n = n-1;
break;
}
}
}
l1 = Eigen::MatrixXd::Zero(min_points,3);
l2 = Eigen::MatrixXd::Zero(min_points,3);
l3 = Eigen::MatrixXd::Zero(min_points,3);
for (int ii=0; ii<l1.rows(); ++ii)
{
l1.row(ii) = list1.row(idx(ii));
l2.row(ii) = list2.row(idx(ii));
l3.row(ii) = list3.row(idx(ii));
}
}
bool TrifocalTensor::computeTensor(const Eigen::MatrixXd& list1, const Eigen::MatrixXd& list2, const Eigen::MatrixXd& list3)
{
//int min_points = list1.rows();
int min_points = 8;
if (list1.rows()<min_points || list2.rows()<min_points || list3.rows()<min_points)
return false;
Eigen::MatrixXd l1(min_points,3), l2(min_points,3), l3(min_points,3);
getRandomCandidates(min_points, list1, list2, list3, l1, l2, l3);
Eigen::MatrixXd A;
computeMatrixA(list1, list2, list3, A);
computeMatrixA(l1, l2, l3, A);
// resolve equation : A*t = 0 where t is unknown
Eigen::VectorXd tensorVector = resolveEquationWithSVD(A, 26);
fillTensor(tensorVector);
Eigen::VectorXd tensorVector;
if ( resolveEquationWithSVD(A, tensorVector) )
{
fillTensor(tensorVector);
return true;
}
else
return false;
}
void TrifocalTensor::computeMatrixA(const Eigen::MatrixXd& list1, const Eigen::MatrixXd& list2, const Eigen::MatrixXd& list3, Eigen::MatrixXd& A)
......@@ -75,19 +123,25 @@ void TrifocalTensor::computeMatrixA(const Eigen::MatrixXd& list1, const Eigen::M
}
}
Eigen::VectorXd TrifocalTensor::resolveEquationWithSVD(Eigen::MatrixXd& A, size_t indexOfLastColumnOfV)
bool TrifocalTensor::resolveEquationWithSVD(Eigen::MatrixXd& A, Eigen::VectorXd& tensorVector)
{
Eigen::JacobiSVD<Eigen::MatrixXd> svd(A, Eigen::ComputeThinU | Eigen::ComputeThinV);
// Ensure that a poor choice of points are not selected to compute the Trifocal Tensor.
// The check is based on the condition number of the matrices involved in computing the trifocal tensor
double cond = svd.singularValues()(0) / svd.singularValues()(svd.singularValues().size()-1);
if (std::isnan(cond) || cond < 1e-6)
return false;
const Eigen::MatrixXd U = svd.matrixU();
const Eigen::VectorXd D_diag = svd.singularValues();
Eigen::MatrixXd V = svd.matrixV();
Eigen::VectorXd tensorVector;
tensorVector.Zero(27);
tensorVector = V.col(indexOfLastColumnOfV);
tensorVector = V.col(26);
return tensorVector;
return true;
}
......
......@@ -3,6 +3,8 @@
#include <Eigen/Dense>
#include <random>
// vision utils includes
#include "../vision_utils.h"
......@@ -29,7 +31,7 @@ public:
/**
* \brief Compute trifocal tensor
*/
void computeTensor(const Eigen::MatrixXd& list1, const Eigen::MatrixXd& list2, const Eigen::MatrixXd& list3);
bool computeTensor(const Eigen::MatrixXd& list1, const Eigen::MatrixXd& list2, const Eigen::MatrixXd& list3);
/**
* \brief Compute the coordinates of the point p3 on third img corresponding to p1 and p2 of others images
......@@ -58,7 +60,7 @@ private:
/**
* \brief Resolve equation by finding tensor in A*tensor = 0 excluding the solution t = 0 with SVD decomposition
*/
Eigen::VectorXd resolveEquationWithSVD(Eigen::MatrixXd& A, size_t indexOfLastColumnOfV);
bool resolveEquationWithSVD(Eigen::MatrixXd& A, Eigen::VectorXd& tensorVector);
/**
* \brief Fill elements of the tensor with the solution found
......@@ -70,6 +72,10 @@ private:
*/
void computeMatrixB(const Eigen::Vector3d& p1, const Eigen::Vector3d& p2, Eigen::MatrixXd& B, Eigen::VectorXd& b);
/**
* \brief Get random candidates
*/
void getRandomCandidates(const int& min_points, const Eigen::MatrixXd& list1, const Eigen::MatrixXd& list2, const Eigen::MatrixXd& list3, Eigen::MatrixXd& l1, Eigen::MatrixXd& l2, Eigen::MatrixXd& l3);
};
} /* namespace vision_utils */
......
......@@ -260,7 +260,8 @@ TEST(TrifocalTensor, ComputeTensorSynthetic)
list3.row(8) << 247.6911, 244.6778, 1.0;
vision_utils::TrifocalTensor tensor;
tensor.computeTensor(list1, list2, list3);
bool tensor_ok = tensor.computeTensor(list1, list2, list3);
ASSERT_TRUE(tensor_ok);
KeyPointVector kpts_tensor_in3;
for (int ii=0;ii<list1.rows(); ++ii)
......@@ -274,9 +275,9 @@ TEST(TrifocalTensor, ComputeTensorSynthetic)
for (int ii=0;ii<kpts_tensor_in3.size(); ++ii)
{
// std::cout << "TODO: debug tensor with gtest_trifocaltensor" << std::endl;
// std::cout << std::sqrt(std::pow(kpts_tensor_in3[ii].pt.x-list3(ii,0),2) + std::pow(kpts_tensor_in3[ii].pt.y-list3(ii,1),2)) << std::endl;
ASSERT_TRUE(std::sqrt(std::pow(kpts_tensor_in3[ii].pt.x-list3(ii,0),2) + std::pow(kpts_tensor_in3[ii].pt.y-list3(ii,1),2))<=1e-3);
std::cout << "TODO: debug tensor with gtest_trifocaltensor" << std::endl;
std::cout << std::sqrt(std::pow(kpts_tensor_in3[ii].pt.x-list3(ii,0),2) + std::pow(kpts_tensor_in3[ii].pt.y-list3(ii,1),2)) << std::endl;
ASSERT_TRUE(std::sqrt(std::pow(kpts_tensor_in3[ii].pt.x-list3(ii,0),2) + std::pow(kpts_tensor_in3[ii].pt.y-list3(ii,1),2))<=1e-1);
}
}
......@@ -413,7 +414,8 @@ TEST(TrifocalTensor, ComputeTensorReal)
Eigen::MatrixXd list3 = vision_utils::KeyPointVecToEigenMat(kpts_good_in3);
vision_utils::TrifocalTensor tensor;
tensor.computeTensor(list1, list2, list3);
bool tensor_ok = tensor.computeTensor(list1, list2, list3);
ASSERT_TRUE(tensor_ok);
KeyPointVector kpts_tensor_in3;
for (int ii=0;ii<list1.rows(); ++ii)
......
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