void displayProj2d( Viewer3D<space, kspace> & viewer,
const KSpace & ks, const StandardDSS6Computer & dss3d,
const DGtal::Color & color2d )
{
typedef typename StandardDSS6Computer::ArithmeticalDSSComputer2d ArithmeticalDSSComputer2d;
typedef typename ArithmeticalDSSComputer2d::ConstIterator ConstIterator2d;
typedef typename ArithmeticalDSSComputer2d::Point Point2d;
typedef typename KSpace::Cell Cell;
typedef typename KSpace::Point Point3d;
Point3d b = ks.lowerBound();
for ( DGtal::Dimension i = 0; i < 3; ++i )
{
const ArithmeticalDSSComputer2d & dss2d = dss3d.arithmeticalDSS2d( i );
for ( ConstIterator2d itP = dss2d.begin(), itPEnd = dss2d.end(); itP != itPEnd; ++itP )
{
Point2d p = *itP;
Point3d q;
switch (i) {
case 0: q = Point3d( 2*b[ i ] , 2*p[ 0 ]+1, 2*p[ 1 ]+1 ); break;
case 1: q = Point3d( 2*p[ 0 ]+1, 2*b[ i ] , 2*p[ 1 ]+1 ); break;
case 2: q = Point3d( 2*p[ 0 ]+1, 2*p[ 1 ]+1, 2*b[ i ] ); break;
}
Cell c = ks.uCell( q );
viewer << CustomColors3D( color2d, color2d ) << c;
}
}
}
void displayDSS2d( Viewer3D<space, kspace> & viewer,
const KSpace & ks, const StandardDSS6Computer & dss3d,
const DGtal::Color & color2d )
{
typedef typename StandardDSS6Computer::ConstIterator ConstIterator3d;
typedef typename StandardDSS6Computer::ArithmeticalDSSComputer2d ArithmeticalDSSComputer2d;
typedef typename ArithmeticalDSSComputer2d::ConstIterator ConstIterator2d;
typedef typename ArithmeticalDSSComputer2d::Point Point2d;
typedef typename KSpace::Cell Cell;
typedef typename KSpace::Point Point3d;
typedef DGtal::PointVector<2,double> PointD2d;
typedef typename Display3D<>::BallD3D PointD3D;
Point3d b = ks.lowerBound();
for ( DGtal::Dimension i = 0; i < 3; ++i )
{
const typename ArithmeticalDSSComputer2d::Primitive & dss2d
= dss3d.arithmeticalDSS2d( i ).primitive();
// draw 2D bounding boxes for each arithmetical dss 2D.
std::vector<PointD2d> pts2d;
pts2d.push_back( dss2d.project(dss2d.back(), dss2d.Uf()) );
pts2d.push_back( dss2d.project(dss2d.back(), dss2d.Lf()) );
pts2d.push_back( dss2d.project(dss2d.front(), dss2d.Lf()) );
pts2d.push_back( dss2d.project(dss2d.front(), dss2d.Uf()) );
std::vector<PointD3D> bb;
PointD3D p3;
for ( unsigned int j = 0; j < pts2d.size(); ++j )
{
switch (i) {
case 0: p3.center[0] = (double) b[ i ]-0.5; p3.center[1] = pts2d[ j ][ 0 ]; p3.center[2] = pts2d[ j ][ 1 ]; break;
case 1: p3.center[0] = pts2d[ j ][ 0 ]; p3.center[1] = (double) b[ i ]-0.5; p3.center[2] = pts2d[ j ][ 1 ]; break;
case 2: p3.center[0] = pts2d[ j ][ 0 ]; p3.center[1] = pts2d[ j ][ 1 ]; p3.center[2] = (double) b[ i ]-0.5; break;
}
bb.push_back( p3 );
}
for ( unsigned int j = 0; j < pts2d.size(); ++j ){
viewer.setLineColor(color2d);
viewer.addLine( DGtal::Z3i::RealPoint(bb[ j ].center[0], bb[ j ].center[1], bb[ j ].center[2]),
DGtal::Z3i::RealPoint(bb[ (j+1)%4 ].center[0], bb[ (j+1)%4 ].center[1], bb[ (j+1)%4 ].center[2]),
MS3D_LINESIZE );
}
} // for ( DGtal::Dimension i = 0; i < 3; ++i )
}
void chooseEstimator
( const po::variables_map& vm, //< command-line parameters
const KSpace& K, //< cellular grid space
const ImplicitShape& shape, //< implicit shape "ground truth"
const Surface& surface, //< digital surface approximating shape
const KernelFunction& chi, //< the kernel function
const PointPredicate& ptPred ) //< analysed implicit digital shape as a PointPredicate
{
using namespace DGtal::functors;
string nameEstimator = vm[ "estimator" ].as<string>();
double h = vm["gridstep"].as<double>();
typedef ShapeGeometricFunctors::ShapeNormalVectorFunctor<ImplicitShape> NormalFunctor;
typedef TrueDigitalSurfaceLocalEstimator<KSpace, ImplicitShape, NormalFunctor> TrueEstimator;
TrueEstimator true_estimator;
true_estimator.attach( shape );
true_estimator.setParams( K, NormalFunctor(), 20, 0.1, 0.01 );
true_estimator.init( h, surface.begin(), surface.end() );
if ( nameEstimator == "True" )
{
trace.beginBlock( "Chosen estimator is: True." );
typedef TrueDigitalSurfaceLocalEstimator<KSpace, ImplicitShape, NormalFunctor> Estimator;
int maxIter = vm["maxiter"].as<int>();
double accuracy = vm["accuracy"].as<double>();
double gamma = vm["gamma"].as<double>();
Estimator estimator;
estimator.attach( shape );
estimator.setParams( K, NormalFunctor(), maxIter, accuracy, gamma );
estimator.init( h, surface.begin(), surface.end() );
trace.endBlock();
computeEstimation( vm, K, shape, surface, estimator );
}
else if ( nameEstimator == "VCM" )
{
trace.beginBlock( "Chosen estimator is: VCM." );
typedef typename KSpace::Space Space;
typedef typename Surface::DigitalSurfaceContainer SurfaceContainer;
typedef ExactPredicateLpSeparableMetric<Space,2> Metric;
typedef VoronoiCovarianceMeasureOnDigitalSurface<SurfaceContainer,Metric,
KernelFunction> VCMOnSurface;
typedef VCMNormalVectorFunctor<VCMOnSurface> NormalFunctor;
typedef VCMDigitalSurfaceLocalEstimator<SurfaceContainer,Metric,
KernelFunction, NormalFunctor> VCMNormalEstimator;
int embedding = vm["embedding"].as<int>();
Surfel2PointEmbedding embType = embedding == 0 ? Pointels :
embedding == 1 ? InnerSpel : OuterSpel;
double R = vm["R-radius"].as<double>();
double r = vm["r-radius"].as<double>();
double t = vm["trivial-radius"].as<double>();
double alpha = vm["alpha"].as<double>();
if ( alpha != 0.0 ) R *= pow( h, alpha-1.0 );
if ( alpha != 0.0 ) r *= pow( h, alpha-1.0 );
trace.info() << "- R=" << R << " r=" << r << " t=" << t << std::endl;
VCMNormalEstimator estimator;
estimator.attach( surface );
estimator.setParams( embType, R, r, chi, t, Metric(), true );
estimator.init( h, surface.begin(), surface.end() );
trace.endBlock();
computeEstimation( vm, K, shape, surface, estimator );
}
else if ( nameEstimator == "II" )
{
trace.beginBlock( "Chosen estimator is: II." );
typedef typename KSpace::Space Space;
typedef HyperRectDomain<Space> Domain;
typedef ImageContainerBySTLVector< Domain, bool> Image;
typedef typename Domain::ConstIterator DomainConstIterator;
typedef SimpleThresholdForegroundPredicate<Image> ThresholdedImage;
typedef IINormalDirectionFunctor<Space> IINormalFunctor;
typedef IntegralInvariantCovarianceEstimator<KSpace, ThresholdedImage, IINormalFunctor> IINormalEstimator;
double r = vm["r-radius"].as<double>();
double alpha = vm["alpha"].as<double>();
if ( alpha != 0.0 ) r *= pow( h, alpha-1.0 );
trace.info() << " r=" << r << std::endl;
trace.beginBlock( "Preparing characteristic set." );
Domain domain( K.lowerBound(), K.upperBound() );
Image image( domain );
for ( DomainConstIterator it = domain.begin(), itE = domain.end(); it != itE; ++it )
{
image.setValue( *it, ptPred( *it ) );
}
trace.endBlock();
trace.beginBlock( "Initialize II estimator." );
ThresholdedImage thresholdedImage( image, false );
IINormalEstimator ii_estimator( K, thresholdedImage );
ii_estimator.setParams( r );
ii_estimator.init( h, surface.begin(), surface.end() );
trace.endBlock();
trace.endBlock();
computeEstimation( vm, K, shape, surface, ii_estimator );
}
else if ( nameEstimator == "Trivial" )
{
trace.beginBlock( "Chosen estimator is: Trivial." );
typedef HatFunction<double> Functor;
typedef typename KSpace::Space Space;
typedef typename KSpace::Surfel Surfel;
typedef typename Surface::DigitalSurfaceContainer SurfaceContainer;
typedef ExactPredicateLpSeparableMetric<Space,2> Metric;
typedef ElementaryConvolutionNormalVectorEstimator< Surfel, CanonicSCellEmbedder<KSpace> >
SurfelFunctor;
typedef LocalEstimatorFromSurfelFunctorAdapter< SurfaceContainer, Metric, SurfelFunctor, Functor>
NormalEstimator;
double t = vm["trivial-radius"].as<double>();
Functor fct( 1.0, t );
CanonicSCellEmbedder<KSpace> canonic_embedder( K );
SurfelFunctor surfelFct( canonic_embedder, 1.0 );
NormalEstimator estimator;
estimator.attach( surface );
estimator.setParams( Metric(), surfelFct, fct, t );
estimator.init( 1.0, surface.begin(), surface.end() );
trace.endBlock();
computeEstimation( vm, K, shape, surface, estimator );
}
}
