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/*=========================================================================
Program: Visualization Toolkit
Module: TestLandmarkTransform.cxx
Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen
All rights reserved.
See Copyright.txt or http://www.kitware.com/Copyright.htm for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
PURPOSE. See the above copyright notice for more information.
=========================================================================*/
#include "vtkMath.h"
#include "vtkMatrix4x4.h"
#include "vtkNew.h"
#include "vtkPoints.h"
#include "vtkThinPlateSplineTransform.h"
#include "vtkTransform.h"
#include <iostream>
#include <sstream>
struct Conditions
{
bool regularizeBulkTransform;
int npoints;
double noiseSigma;
int sourceDimensionality;
double sourceRotX;
double sourceRotY;
double sourceRotZ;
double sourceScaleX;
double sourceScaleY;
double sourceScaleZ;
double sourceTransX;
double sourceTransY;
double sourceTransZ;
int targetDimensionality;
double targetRotX;
double targetRotY;
double targetRotZ;
double targetScaleX;
double targetScaleY;
double targetScaleZ;
double targetTransX;
double targetTransY;
double targetTransZ;
bool testForwardTransform;
bool testInverseTransform;
};
static void SetTransform(vtkTransform* transform, int dimensionality, double rotX, double rotY,
double rotZ, double scaleX, double scaleY, double scaleZ, double transX, double transY,
double transZ)
{
transform->Translate(transX, transY, transZ);
transform->RotateX(rotX);
transform->RotateY(rotY);
transform->RotateZ(rotZ);
transform->Scale(scaleX, scaleY, scaleZ);
switch (dimensionality)
{
case 0:
transform->Scale(0.0, 0.0, 0.0);
break;
case 1:
transform->Scale(1.0, 0.0, 0.0);
break;
case 2:
transform->Scale(1.0, 1.0, 0.0);
break;
}
}
static int TestTransform(Conditions c)
{
int errorCode = 0; // will be set to 1 if failure
std::ostringstream errstream;
int npoints = (c.npoints > 20 ? 20 : c.npoints);
const double landmarkPointCoords[20][3] = {
{ -0.8316301300814422, -0.06992580859519772, -1.6034524068257419 },
{ -2.151893827785692, 0.38244721645095636, -0.9275967632551845 },
{ 0.8147291118075928, -0.7016483698682392, 0.15003863332602096 },
{ 0.918239421266975, 0.5515514723709805, -1.0230600499321258 },
{ -0.4977939747967184, 1.5000786176083494, 0.892455159403953 },
{ 2.137759080794324, -0.7876029858279091, 0.23676951564894347 },
{ 0.07659657475437548, 0.37528421293358666, 1.061745743663681 },
{ -0.7908820649026604, 1.4270955106455065, 2.2665387247459576 },
{ -0.5663930529602919, 1.9402635876094498, 1.1531767242062774 },
{ 0.22529528853908187, -1.5938090446587108, -0.7004997748768814 },
{ 0.6165064084492409, -0.2761336076050157, -0.7930056820043028 },
{ -1.6122391974605947, -1.4200010952872733, 1.0567292903013055 },
{ 0.17993263043615856, -0.9038514957133562, -2.1611068227229695 },
{ -1.4186794357559613, 0.85026116269838, -1.7600646313947719 },
{ 0.9690209792801024, 0.7018737798529897, 0.3923799957082836 },
{ -0.6586203767750309, -2.1468680342265904, 0.762954972139701 },
{ 1.2872860659137344, 0.8557080868402649, 0.3905931440107816 },
{ -0.18996464681200217, 0.8315184491297033, -1.0227889589485941 },
{ 1.0636210067525393, -0.24736478911115908, -0.7581101375259237 },
{ -0.09448165336394657, -1.1381967760924927, -0.7171168342666931 },
};
const double landmarkPointNoise[20][3] = {
{ 1.5137019295427425, 0.6858246680960894, 0.07331883771349512 },
{ -0.34081703057234036, 0.47987804772801446, 0.982197518178181 },
{ -0.1106079068591361, 1.0523148414328571, 0.17910578196163454 },
{ 0.05724784633562011, -0.08459760939107724, -0.7665637643588622 },
{ -0.4333381262791796, 0.018412807528038692, 0.6889623031683394 },
{ -1.1692454358073843, -0.6875830563599973, 0.9077463799204326 },
{ -1.9329042505569662, 1.0529789607437061, -0.29738186972471486 },
{ -0.12079407626315326, 0.9261998453458427, 1.0938543547601083 },
{ -0.6384715430732077, -0.2606527602354865, 1.417882645305744 },
{ -0.10127708027623447, -0.7470111486643078, 0.726100633329295 },
{ 0.36659507636859245, 1.4194144006017144, 0.41878644928947467 },
{ 1.0325034539790547, -0.2291631905797599, -1.3490582933020208 },
{ -0.7186165872334461, 0.4613954758072554, -1.1318559861004829 },
{ 2.455035378196603, -0.01476716688473253, -0.0890030227805104 },
{ 1.6498918075463915, 2.7557006973876508, -0.6466098561563114 },
{ 1.16764314555201, -1.5226214641344893, 0.13000979083980121 },
{ -0.9640219699623079, 1.3071375444488553, 0.5668689159057715 },
{ 0.40366181757487013, 2.308315254377135, 0.8202651493656881 },
{ -1.0267515231555335, -0.2853656137629097, -1.1599391275129292 },
{ -0.09199656043877075, 0.35274602605225164, 2.5626579880899327 },
};
// There can be some inaccuracies in forward computation when all points are coplanar.
const double forwardErrorTolerance =
(c.sourceDimensionality == 3 && c.targetDimensionality == 3 ? 0.0 : 0.001);
// There can always be some inaccuracies in inverse computation.
const double inverseErrorTolerance = 0.001;
vtkNew<vtkTransform> sourceTransform;
SetTransform(sourceTransform, c.sourceDimensionality, c.sourceRotX, c.sourceRotY, c.sourceRotZ,
c.sourceScaleX, c.sourceScaleY, c.sourceScaleZ, c.sourceTransX, c.sourceTransY, c.sourceTransZ);
// generate the transform we want to recover
vtkNew<vtkTransform> targetTransform;
SetTransform(targetTransform, c.targetDimensionality, c.targetRotX, c.targetRotY, c.targetRotZ,
c.targetScaleX, c.targetScaleY, c.targetScaleZ, c.targetTransX, c.targetTransY, c.targetTransZ);
// create the two point sets
vtkNew<vtkPoints> sourcePoints;
vtkNew<vtkPoints> targetPoints;
double psigma = c.noiseSigma / sqrt(3.0);
for (int i = 0; i < npoints; i++)
{
double sourcePoint[3] = { landmarkPointCoords[i][0], landmarkPointCoords[i][1],
landmarkPointCoords[i][2] };
sourceTransform->TransformPoint(sourcePoint, sourcePoint);
sourcePoints->InsertNextPoint(sourcePoint);
double targetPoint[3] = { landmarkPointCoords[i][0], landmarkPointCoords[i][1],
landmarkPointCoords[i][2] };
targetTransform->TransformPoint(targetPoint, targetPoint);
targetPoint[0] += psigma * landmarkPointNoise[i][0];
targetPoint[1] += psigma * landmarkPointNoise[i][1];
targetPoint[2] += psigma * landmarkPointNoise[i][2];
targetPoints->InsertNextPoint(targetPoint);
}
vtkNew<vtkThinPlateSplineTransform> ltrans;
ltrans->SetBasisToR();
ltrans->SetRegularizeBulkTransform(c.regularizeBulkTransform);
ltrans->SetSourceLandmarks(sourcePoints);
ltrans->SetTargetLandmarks(targetPoints);
ltrans->Update();
if (c.testForwardTransform)
{
vtkNew<vtkPoints> transformedSourcePoints;
ltrans->TransformPoints(sourcePoints, transformedSourcePoints);
double dsum = 0.0;
double dmax = 0.0;
for (int i = 0; i < npoints; i++)
{
double targetPoint[3] = { 0.0 };
targetPoints->GetPoint(i, targetPoint);
double transformedSourcePoint[3] = { 0.0 };
transformedSourcePoints->GetPoint(i, transformedSourcePoint);
double d = vtkMath::Distance2BetweenPoints(targetPoint, transformedSourcePoint);
dmax = (dmax > d ? dmax : d);
dsum += d;
}
// we expect average error to be close to noiseSigma
double r = (npoints > 0 ? sqrt(dsum / npoints) : 0.0);
if (r > 1.1 * c.noiseSigma + forwardErrorTolerance)
{
errorCode = 1;
errstream << "Forward transform average error is too high: "
<< "r = " << r << " vs. noiseSigma " << c.noiseSigma << ". " << std::endl;
}
// we expect the max error to be around 2 noiseSigma
double e = sqrt(dmax);
if (e > 2.5 * c.noiseSigma + forwardErrorTolerance)
{
errorCode = 1;
errstream << "Forward transform maximum error is too high: "
<< "e = " << e << " vs. noiseSigma " << c.noiseSigma << ". " << std::endl;
}
}
// Test inverse transform
if (c.testInverseTransform)
{
ltrans->Inverse();
vtkNew<vtkPoints> transformedTargetPoints;
ltrans->TransformPoints(targetPoints, transformedTargetPoints);
double dsum = 0.0;
double dmax = 0.0;
for (int i = 0; i < npoints; i++)
{
double sourcePoint[3] = { 0.0 };
sourcePoints->GetPoint(i, sourcePoint);
double transformedTargetPoint[3] = { 0.0 };
transformedTargetPoints->GetPoint(i, transformedTargetPoint);
double d = vtkMath::Distance2BetweenPoints(sourcePoint, transformedTargetPoint);
dmax = (dmax > d ? dmax : d);
dsum += d;
}
// we expect average error to be close to noiseSigma
double r = (npoints > 0 ? sqrt(dsum / npoints) : 0.0);
if (r > 1.1 * c.noiseSigma + inverseErrorTolerance)
{
errorCode = 1;
errstream << "Inverse transform average error is too high: "
<< "r = " << r << " vs. noiseSigma " << c.noiseSigma << ". " << std::endl;
}
// we expect the max error to be around 2 noiseSigma
double e = sqrt(dmax);
if (e > 2.5 * c.noiseSigma + inverseErrorTolerance)
{
errorCode = 1;
errstream << "Inverse transform maximum error is too high: "
<< "e = " << e << " vs. noiseSigma " << c.noiseSigma << ". " << std::endl;
}
}
if (errorCode != 0)
{
std::cerr << "Error for test case with " << npoints
<< " points, regularizeBulkTransform = " << c.regularizeBulkTransform << std::endl
<< " Source: dimensionality = " << c.sourceDimensionality << std::endl
<< " rotation = " << c.sourceRotX << " " << c.sourceRotY << " "
<< c.sourceRotZ << std::endl
<< " scale = " << c.sourceScaleX << " " << c.sourceScaleY << " "
<< c.sourceScaleZ << std::endl
<< " translation = " << c.sourceTransX << " " << c.sourceTransY << " "
<< c.sourceTransZ << std::endl
<< " Target: dimensionality = " << c.targetDimensionality << std::endl
<< " rotation = " << c.targetRotX << " " << c.targetRotY << " "
<< c.targetRotZ << std::endl
<< " scale = " << c.targetScaleX << " " << c.targetScaleY << " "
<< c.targetScaleZ << std::endl
<< " translation = " << c.targetTransX << " " << c.targetTransY << " "
<< c.targetTransZ << std::endl
<< " noiseSigma = " << c.noiseSigma << std::endl
<< "Details:" << std::endl
<< errstream.str() << std::endl;
}
return errorCode;
}
// The registration should be robust even if the points are poorly arranged.
// So we test with:
// 1) a full volumetric spread of points,
// 2) with a coplanar set of points,
// 3) with a colinear set of points,
// 4) and with a coincident set of points (all points at same position).
// Also, the registration should give sensible results even if there are
// only 1, 2, 3 or even no input points.
int TestThinPlateSplineTransform(int, char*[])
{
Conditions condition;
condition.regularizeBulkTransform = true;
condition.npoints = 20;
condition.noiseSigma = 0.0;
condition.sourceDimensionality = 3;
condition.sourceRotX = condition.sourceRotY = condition.sourceRotZ = 0.0;
condition.sourceScaleX = 20.0;
condition.sourceScaleY = 30.0;
condition.sourceScaleZ = 40.0;
condition.sourceTransX = condition.sourceTransY = condition.sourceTransZ = 0.0;
condition.targetDimensionality = 3;
condition.targetRotX = condition.targetRotY = condition.targetRotZ = 0.0;
condition.targetScaleX = condition.sourceScaleX;
condition.targetScaleY = condition.sourceScaleY;
condition.targetScaleZ = condition.sourceScaleZ;
condition.targetTransX = condition.targetTransY = condition.targetTransZ = 0.0;
condition.testForwardTransform = true;
condition.testInverseTransform = true;
int numberOfErrors = 0;
// Test with and without bulk transform regularization
for (int regularizeBulkTransform = 0; regularizeBulkTransform < 2; regularizeBulkTransform++)
{
condition.regularizeBulkTransform = (regularizeBulkTransform != 0);
// Test with target points distributed in a 3D cube, plane, and line
for (int targetDimensionality = 3; targetDimensionality >= 1; targetDimensionality--)
{
condition.targetDimensionality = targetDimensionality;
// Test with source points distributed in a 3D cube, plane, and line
for (int sourceDimensionality = 3; sourceDimensionality >= 1; sourceDimensionality--)
{
condition.sourceDimensionality = sourceDimensionality;
// Test with noise of 0.0, 5.0, and 10.0
for (int noise = 0; noise < 3; noise++)
{
condition.noiseSigma = double(noise) * 5.0;
// Test with and without source translation
for (int sourceTranslated = 0; sourceTranslated < 2; sourceTranslated++)
{
if (sourceTranslated)
{
condition.sourceTransX = 21.5;
condition.sourceTransY = -11.5;
condition.sourceTransZ = 41.5;
}
else
{
condition.sourceTransX = 0.0;
condition.sourceTransY = 0.0;
condition.sourceTransZ = 0.0;
}
// Test with and without target translation
for (int targetTranslated = 0; targetTranslated < 2; targetTranslated++)
{
if (targetTranslated)
{
condition.targetTransX = 42.1;
condition.targetTransY = 25.3;
condition.targetTransZ = 31.9;
}
else
{
condition.targetTransX = 0.0;
condition.targetTransY = 0.0;
condition.targetTransZ = 0.0;
}
// Test with various source rotations
// Test when points are rotated exactly by 90deg.
// These can cause singularities in the bulk transformation matrix therefore must be
// tested carefully.
for (int sourceRotated = 0; sourceRotated < 5; sourceRotated++)
{
if (sourceRotated == 0)
{
condition.sourceRotX = 0.0;
condition.sourceRotY = 0.0;
condition.sourceRotZ = 0.0;
}
else if (sourceRotated == 1)
{
condition.sourceRotX = 90.0;
condition.sourceRotY = 0.0;
condition.sourceRotZ = 0.0;
}
else if (sourceRotated == 2)
{
condition.sourceRotX = 0.0;
condition.sourceRotY = 90.0;
condition.sourceRotZ = 0.0;
}
else if (sourceRotated == 3)
{
condition.sourceRotX = 0.0;
condition.sourceRotY = 0.0;
condition.sourceRotZ = 90.0;
}
else if (sourceRotated == 4)
{
condition.sourceRotX = 20.0;
condition.sourceRotY = -11.0;
condition.sourceRotZ = 132.0;
}
// Test with various target rotations
for (int targetRotated = 0; targetRotated < 5; targetRotated++)
{
if (targetRotated == 0)
{
condition.targetRotX = 0.0;
condition.targetRotY = 0.0;
condition.targetRotZ = 0.0;
}
else if (targetRotated == 1)
{
condition.targetRotX = 90.0;
condition.targetRotY = 0.0;
condition.targetRotZ = 0.0;
}
else if (targetRotated == 2)
{
condition.targetRotX = 0.0;
condition.targetRotY = 90.0;
condition.targetRotZ = 0.0;
}
else if (targetRotated == 3)
{
condition.targetRotX = 0.0;
condition.targetRotY = 0.0;
condition.targetRotZ = 90.0;
}
else if (targetRotated == 4)
{
condition.targetRotX = -18.0;
condition.targetRotY = 37.2;
condition.targetRotZ = 23.7;
}
if (condition.sourceDimensionality == 3 && condition.targetDimensionality == 3)
{
// Points are not coplanar, we test forward and inverse transforms
condition.testForwardTransform = true;
condition.testInverseTransform = true;
}
else
{
// Points are coplanar, there are some limitations of what transforms are tested
if (condition.regularizeBulkTransform)
{
// If regularization is enabled then both forward and inverse transforms are
// computed but only if all points are in XY plane.
bool allPointsInXYPlane = condition.sourceDimensionality == 2 &&
condition.targetDimensionality == 2 && sourceRotated == 0 &&
targetRotated == 0 && sourceTranslated == 0 && targetTranslated == 0 &&
noise == 0;
condition.testForwardTransform = allPointsInXYPlane;
condition.testInverseTransform = allPointsInXYPlane;
}
else
{
// If regularization is disabled then all coplanar configuration work but
// only for forward transform.
condition.testForwardTransform = true;
condition.testInverseTransform = false;
}
}
// Test this condition
if (TestTransform(condition))
{
numberOfErrors++;
}
}
}
}
}
}
}
}
}
if (numberOfErrors > 0)
{
std::cerr << std::endl << "Number of errors: " << numberOfErrors << std::endl;
return 1;
}
return 0;
}
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