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// David Eberly, Geometric Tools, Redmond WA 98052
// Copyright (c) 1998-2021
// Distributed under the Boost Software License, Version 1.0.
// https://www.boost.org/LICENSE_1_0.txt
// https://www.geometrictools.com/License/Boost/LICENSE_1_0.txt
// Version: 4.0.2019.08.13
#pragma once
#include <Mathematics/ApprQuery.h>
#include <Mathematics/Line.h>
#include <Mathematics/SymmetricEigensolver3x3.h>
#include <Mathematics/Vector3.h>
// Least-squares fit of a line to (x,y,z) data by using distance measurements
// orthogonal to the proposed line. The return value is 'true' if and only if
// the fit is unique (always successful, 'true' when a minimum eigenvalue is
// unique). The mParameters value is a line with (P,D) = (origin,direction).
// The error for S = (x0,y0,z0) is (S-P)^T*(I - D*D^T)*(S-P).
namespace gte
{
template <typename Real>
class ApprOrthogonalLine3 : public ApprQuery<Real, Vector3<Real>>
{
public:
// Initialize the model parameters to zero.
ApprOrthogonalLine3()
:
mParameters(Vector3<Real>::Zero(), Vector3<Real>::Zero())
{
}
// Basic fitting algorithm. See ApprQuery.h for the various Fit(...)
// functions that you can call.
virtual bool FitIndexed(
size_t numPoints, Vector3<Real> const* points,
size_t numIndices, int const* indices) override
{
if (this->ValidIndices(numPoints, points, numIndices, indices))
{
// Compute the mean of the points.
Vector3<Real> mean = Vector3<Real>::Zero();
int const* currentIndex = indices;
for (size_t i = 0; i < numIndices; ++i)
{
mean += points[*currentIndex++];
}
Real invSize = (Real)1 / (Real)numIndices;
mean *= invSize;
if (std::isfinite(mean[0]) && std::isfinite(mean[1]))
{
// Compute the covariance matrix of the points.
Real covar00 = (Real)0, covar01 = (Real)0, covar02 = (Real)0;
Real covar11 = (Real)0, covar12 = (Real)0, covar22 = (Real)0;
currentIndex = indices;
for (size_t i = 0; i < numIndices; ++i)
{
Vector3<Real> diff = points[*currentIndex++] - mean;
covar00 += diff[0] * diff[0];
covar01 += diff[0] * diff[1];
covar02 += diff[0] * diff[2];
covar11 += diff[1] * diff[1];
covar12 += diff[1] * diff[2];
covar22 += diff[2] * diff[2];
}
covar00 *= invSize;
covar01 *= invSize;
covar02 *= invSize;
covar11 *= invSize;
covar12 *= invSize;
covar22 *= invSize;
// Solve the eigensystem.
SymmetricEigensolver3x3<Real> es;
std::array<Real, 3> eval;
std::array<std::array<Real, 3>, 3> evec;
es(covar00, covar01, covar02, covar11, covar12, covar22,
false, +1, eval, evec);
// The line direction is the eigenvector in the direction
// of largest variance of the points.
mParameters.origin = mean;
mParameters.direction = evec[2];
// The fitted line is unique when the maximum eigenvalue
// has multiplicity 1.
return eval[1] < eval[2];
}
}
mParameters = Line3<Real>(Vector3<Real>::Zero(), Vector3<Real>::Zero());
return false;
}
// Get the parameters for the best fit.
Line3<Real> const& GetParameters() const
{
return mParameters;
}
virtual size_t GetMinimumRequired() const override
{
return 2;
}
virtual Real Error(Vector3<Real> const& point) const override
{
Vector3<Real> diff = point - mParameters.origin;
Real sqrlen = Dot(diff, diff);
Real dot = Dot(diff, mParameters.direction);
Real error = std::fabs(sqrlen - dot * dot);
return error;
}
virtual void CopyParameters(ApprQuery<Real, Vector3<Real>> const* input) override
{
auto source = dynamic_cast<ApprOrthogonalLine3<Real> const*>(input);
if (source)
{
*this = *source;
}
}
private:
Line3<Real> mParameters;
};
}