本文整理汇总了C++中MatrixXf::determinant方法的典型用法代码示例。如果您正苦于以下问题：C++ MatrixXf::determinant方法的具体用法？C++ MatrixXf::determinant怎么用？C++ MatrixXf::determinant使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类MatrixXf的用法示例。
在下文中一共展示了MatrixXf::determinant方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C++代码示例。
示例1: execute
void IterativeClosestPoint::execute() {
float error = std::numeric_limits<float>::max(), previousError;
uint iterations = 0;
// Get access to the two point sets
PointSetAccess::pointer accessFixedSet = ((PointSet::pointer)getStaticInputData<PointSet>(0))->getAccess(ACCESS_READ);
PointSetAccess::pointer accessMovingSet = ((PointSet::pointer)getStaticInputData<PointSet>(1))->getAccess(ACCESS_READ);
// Get transformations of point sets
AffineTransformation::pointer fixedPointTransform2 = SceneGraph::getAffineTransformationFromData(getStaticInputData<PointSet>(0));
Eigen::Affine3f fixedPointTransform;
fixedPointTransform.matrix() = fixedPointTransform2->matrix();
AffineTransformation::pointer initialMovingTransform2 = SceneGraph::getAffineTransformationFromData(getStaticInputData<PointSet>(1));
Eigen::Affine3f initialMovingTransform;
initialMovingTransform.matrix() = initialMovingTransform2->matrix();
// These matrices are Nx3
MatrixXf fixedPoints = accessFixedSet->getPointSetAsMatrix();
MatrixXf movingPoints = accessMovingSet->getPointSetAsMatrix();
Eigen::Affine3f currentTransformation = Eigen::Affine3f::Identity();
// Want to choose the smallest one as moving
bool invertTransform = false;
if(false && fixedPoints.cols() < movingPoints.cols()) {
reportInfo() << "switching fixed and moving" << Reporter::end;
// Switch fixed and moving
MatrixXf temp = fixedPoints;
fixedPoints = movingPoints;
movingPoints = temp;
invertTransform = true;
// Apply initial transformations
//currentTransformation = fixedPointTransform.getTransform();
movingPoints = fixedPointTransform*movingPoints.colwise().homogeneous();
fixedPoints = initialMovingTransform*fixedPoints.colwise().homogeneous();
} else {
// Apply initial transformations
//currentTransformation = initialMovingTransform.getTransform();
movingPoints = initialMovingTransform*movingPoints.colwise().homogeneous();
fixedPoints = fixedPointTransform*fixedPoints.colwise().homogeneous();
}
do {
previousError = error;
MatrixXf movedPoints = currentTransformation*(movingPoints.colwise().homogeneous());
// Match closest points using current transformation
MatrixXf rearrangedFixedPoints = rearrangeMatrixToClosestPoints(
fixedPoints, movedPoints);
// Get centroids
Vector3f centroidFixed = getCentroid(rearrangedFixedPoints);
//reportInfo() << "Centroid fixed: " << Reporter::end;
//reportInfo() << centroidFixed << Reporter::end;
Vector3f centroidMoving = getCentroid(movedPoints);
//reportInfo() << "Centroid moving: " << Reporter::end;
//reportInfo() << centroidMoving << Reporter::end;
Eigen::Transform<float, 3, Eigen::Affine> updateTransform = Eigen::Transform<float, 3, Eigen::Affine>::Identity();
if(mTransformationType == IterativeClosestPoint::RIGID) {
// Create correlation matrix H of the deviations from centroid
MatrixXf H = (movedPoints.colwise() - centroidMoving)*
(rearrangedFixedPoints.colwise() - centroidFixed).transpose();
// Do SVD on H
Eigen::JacobiSVD<Eigen::MatrixXf> svd(H, Eigen::ComputeFullU | Eigen::ComputeFullV);
// Estimate rotation as R=V*U.transpose()
MatrixXf temp = svd.matrixV()*svd.matrixU().transpose();
Matrix3f d = Matrix3f::Identity();
d(2,2) = sign(temp.determinant());
Matrix3f R = svd.matrixV()*d*svd.matrixU().transpose();
// Estimate translation
Vector3f T = centroidFixed - R*centroidMoving;
updateTransform.linear() = R;
updateTransform.translation() = T;
} else {
// Only translation
Vector3f T = centroidFixed - centroidMoving;
updateTransform.translation() = T;
}
// Update current transformation
currentTransformation = updateTransform*currentTransformation;
// Calculate RMS error
MatrixXf distance = rearrangedFixedPoints - currentTransformation*(movingPoints.colwise().homogeneous());
error = 0;
for(uint i = 0; i < distance.cols(); i++) {
error += pow(distance.col(i).norm(),2);
}
error = sqrt(error / distance.cols());
iterations++;
reportInfo() << "Error: " << error << Reporter::end;
// To continue, change in error has to be above min error change and nr of iterations less than max iterations
} while(previousError-error > mMinErrorChange && iterations < mMaxIterations);
//.........这里部分代码省略.........