vcglib/vcg/complex/trimesh/point_sampling.h

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* Visual and Computer Graphics Library                            o     o   *
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* Copyright(C) 2004                                                \/)\/    *
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/****************************************************************************

The sampling Class has a set of static functions, that you can call to sample the surface of a mesh.
Each function is templated on the mesh and on a Sampler object s. 
Each function calls many time the sample object with the sampling point as parameter.
 
Sampler Classes and Sampling algorithms are independent. 
Sampler classes exploits the sample that are generated with various algorithms.
For example, you can compute Hausdorff distance (that is a sampler) using various 
sampling strategies (montecarlo, stratified etc).
 
****************************************************************************/
#ifndef __VCGLIB_POINT_SAMPLING
#define __VCGLIB_POINT_SAMPLING

#include <vcg/math/random_generator.h>
#include <vcg/complex/trimesh/closest.h>
#include <vcg/space/index/spatial_hashing.h>
#include <vcg/complex/trimesh/stat.h>
#include <vcg/complex/trimesh/update/topology.h>
#include <vcg/space/box2.h>
namespace vcg
{
namespace tri
{

/// Trivial Sampler, an example sampler object that show the required interface used by the sampling class. 
/// Most of the sampling classes call the AddFace method with the face containing the sample and its barycentric coord.
template <class MeshType>
class TrivialSampler
{
	public:
		typedef typename MeshType::CoordType			CoordType;
		typedef typename MeshType::VertexType			VertexType;
    typedef typename MeshType::FaceType				FaceType;

	TrivialSampler(){};
	std::vector<CoordType> sampleVec;
	
	void AddVert(const VertexType &p) 
	{
		sampleVec.push_back(p.cP());
	}
	void AddFace(const FaceType &f, const CoordType &p) 
	{
		sampleVec.push_back(f.P(0)*p[0] + f.P(1)*p[1] +f.P(2)*p[2] );
	}
	
	void AddTextureSample(const FaceType &, const CoordType &, const Point2i &)
	{
		// Retrieve the color of the sample from the face f using the barycentric coord p 
		// and write that color in a texture image at position tp[0],tp[1]
	}
}; // end class TrivialSampler

template <class MetroMesh, class VertexSampler>
class SurfaceSampling
{
		typedef typename MetroMesh::CoordType			CoordType;
		typedef typename MetroMesh::ScalarType			ScalarType;
		typedef typename MetroMesh::VertexType			VertexType;
		typedef typename MetroMesh::VertexPointer		VertexPointer;
		typedef typename MetroMesh::VertexIterator		VertexIterator;
		typedef typename MetroMesh::FacePointer			FacePointer;
		typedef typename MetroMesh::FaceIterator		FaceIterator;
		typedef typename MetroMesh::FaceType			FaceType;
		typedef typename MetroMesh::FaceContainer		FaceContainer;

private:

	/// Cell for Poisson Disk sampling.
	class Cell
	{
	public:
		Point3<ScalarType> center;      // center of the cell
		double halfedge;                // size (half) of the cell
		bool isempty;                   // false if contains almost one sample

		// ctor
		Cell() :
			center(0.0,0.0,0.0),
			halfedge(0.0),
			isempty(true)
		{
		}

		vcg::Box3<ScalarType> convertToBBox()
		{
			vcg::Box3<ScalarType> box3(center, halfedge);
			return box3;
		}
	}; // end class Cell
	
public:

static math::MarsenneTwisterRNG &SamplingRandomGenerator() 
{
	static math::MarsenneTwisterRNG rnd;
	return rnd;
}

// Returns an integer random number in the [0,i-1] interval using the improve Marsenne-Twister method.
static unsigned int RandomInt(unsigned int i)
{
	return (SamplingRandomGenerator().generate(0) % i);
}

// Returns a random number in the [0,1) real interval using the improved Marsenne-Twister method.
static double RandomDouble01()
{
	return SamplingRandomGenerator().generate01();
}

// Returns a random number in the [0,1] real interval using the improved Marsenne-Twister.
static double RandomDouble01closed()
{
	return SamplingRandomGenerator().generate01closed();
}

static void AllVertex(MetroMesh & m, VertexSampler &ps)
{
	VertexIterator vi;
	for(vi=m.vert.begin();vi!=m.vert.end();++vi)
	{
		if(!(*vi).IsD())
		{
			ps.AddVert(*vi);
		}
	}
}

/// Sample the vertices in a weighted way. Each vertex has a probability of being chosen
/// that is proportional to its quality. 
/// It assumes that you are asking a number of vertices smaller than nv;
/// Algorithm: 
/// 1) normalize quality so that sum q == 1;
/// 2) shuffle vertices.
/// 3) for each vertices choose it if rand > thr;
 
static void VertexWeighted(MetroMesh & m, VertexSampler &ps, int sampleNum)
{
	ScalarType qSum = 0;
	VertexIterator vi;
	for(vi = m.vert.begin(); vi != m.vert.end(); ++vi)
			if(!(*vi).IsD()) 
						qSum += (*vi).Q();
	  
	ScalarType samplePerUnit = sampleNum/qSum;
	ScalarType floatSampleNum =0;
	std::vector<VertexPointer> vertVec;
	FillAndShuffleVertexPointerVector(m,vertVec);

	std::vector<bool> vertUsed(m.vn,false);
	
	int i=0; int cnt=0;
	while(cnt < sampleNum)
		{
			if(vertUsed[i])
				{
						floatSampleNum += vertVec[i]->Q() * samplePerUnit;
						int vertSampleNum   = (int) floatSampleNum;
						floatSampleNum -= (float) vertSampleNum; 
						
						// for every sample p_i in T...
						if(vertSampleNum > 1)
							{
								ps.AddVert(*vertVec[i]);
								cnt++;
								vertUsed[i]=true;
							}
				}
			i = (i+1)%m.vn;				
		}
}

/// Sample the vertices in a uniform way. Each vertex has a probability of being chosen
/// that is proportional to the area it represent. 
static void VertexAreaUniform(MetroMesh & m, VertexSampler &ps, int sampleNum)
{
	VertexIterator vi;
	for(vi = m.vert.begin(); vi != m.vert.end(); ++vi)
		if(!(*vi).IsD()) 
						(*vi).Q() = 0;

	FaceIterator fi;
	for(fi = m.face.begin(); fi != m.face.end(); ++fi)
		if(!(*fi).IsD()) 
		{
			ScalarType areaThird = DoubleArea(*fi)/6.0;
			(*fi).V(0).Q()+=areaThird;
			(*fi).V(1).Q()+=areaThird;
			(*fi).V(2).Q()+=areaThird;
		}
	
	VertexWeighted(m,ps,sampleNum);
}
	
static void	FillAndShuffleFacePointerVector(MetroMesh & m, std::vector<FacePointer> &faceVec)
{
	FaceIterator fi;
	for(fi=m.face.begin();fi!=m.face.end();++fi) 
		if(!(*fi).IsD())	faceVec.push_back(&*fi);
	
	assert((int)faceVec.size()==m.fn);
	
	unsigned int (*p_myrandom)(unsigned int) = RandomInt;
	std::random_shuffle(faceVec.begin(),faceVec.end(), p_myrandom);
}
static void	FillAndShuffleVertexPointerVector(MetroMesh & m, std::vector<VertexPointer> &vertVec)
{
	VertexIterator vi;
	for(vi=m.vert.begin();vi!=m.vert.end();++vi) 
				if(!(*vi).IsD())	vertVec.push_back(&*vi);

	assert((int)vertVec.size()==m.vn);
	
	unsigned int (*p_myrandom)(unsigned int) = RandomInt;
	std::random_shuffle(vertVec.begin(),vertVec.end(), p_myrandom);
}

/// Sample the vertices in a uniform way. Each vertex has the same probabiltiy of being chosen. 
static void VertexUniform(MetroMesh & m, VertexSampler &ps, int sampleNum)
{
	if(sampleNum>=m.vn) {
	  AllVertex(m,ps);
		return;
	} 
	
	std::vector<VertexPointer> vertVec;
	FillAndShuffleVertexPointerVector(m,vertVec);
	
	for(int i =0; i< sampleNum; ++i)
		ps.AddVert(*vertVec[i]);
}


static void FaceUniform(MetroMesh & m, VertexSampler &ps, int sampleNum)
{
	if(sampleNum>=m.fn) {
	  AllFace(m,ps);
		return;
	} 

	std::vector<FacePointer> faceVec;
	FillAndShuffleFacePointerVector(m,faceVec);

	for(int i =0; i< sampleNum; ++i)
		ps.AddFace(*faceVec[i],Barycenter(*faceVec[i]));
}

static void AllFace(MetroMesh & m, VertexSampler &ps)
{
	FaceIterator fi;
	for(fi=m.face.begin();fi!=m.face.end();++fi) 
				if(!(*fi).IsD())
				{
					ps.AddFace(*fi,Barycenter(*fi));
				}
}


static void AllEdge(MetroMesh & m, VertexSampler &ps)
{
    // Edge sampling.
		typedef typename UpdateTopology<MetroMesh>::PEdge SimpleEdge;
		std::vector< SimpleEdge > Edges;
		typename std::vector< SimpleEdge >::iterator ei;
    UpdateTopology<MetroMesh>::FillUniqueEdgeVector(m,Edges);

		for(ei=Edges.begin(); ei!=Edges.end(); ++ei)
				{
					Point3f interp(0,0,0);
					interp[ (*ei).z     ]=.5; 
					interp[((*ei).z+1)%3]=.5;
					ps.AddFace(*(*ei).f,interp);
				}
}

// Regular Uniform Edge sampling
// Each edge is subdivided in a number of pieces proprtional to its lenght
// Sample are choosen without touching the vertices.

static void EdgeUniform(MetroMesh & m, VertexSampler &ps,int sampleNum)
{
		typedef typename UpdateTopology<MetroMesh>::PEdge SimpleEdge;
		std::vector< SimpleEdge > Edges;
    UpdateTopology<MetroMesh>::FillUniqueEdgeVector(m,Edges);
    // First loop compute total edge lenght;
		float edgeSum=0;
		typename std::vector< SimpleEdge >::iterator ei;
		for(ei=Edges.begin(); ei!=Edges.end(); ++ei)
					edgeSum+=Distance((*ei).v[0]->P(),(*ei).v[1]->P());
					
		qDebug("Edges %i  edge sum %f",Edges.size(),edgeSum);			
		float sampleLen = edgeSum/sampleNum;
		qDebug("EdgesSamples %i  Sampling Len %f",sampleNum,sampleLen);			
		float rest=0;
		for(ei=Edges.begin(); ei!=Edges.end(); ++ei)
				{
					float len = Distance((*ei).v[0]->P(),(*ei).v[1]->P());
					float samplePerEdge = floor((len+rest)/sampleLen);
					rest = (len+rest) - samplePerEdge * sampleLen;
					float step = 1.0/(samplePerEdge+1);
					for(int i=0;i<samplePerEdge;++i)
					{
						Point3f interp(0,0,0);
						interp[ (*ei).z     ]=step*(i+1); 
						interp[((*ei).z+1)%3]=1.0-step*(i+1);
						ps.AddFace(*(*ei).f,interp);
					}
				}
}

// Generate the barycentric coords of a random point over a single face, 
// with a uniform distribution over the triangle. 
// It uses the parallelogram folding trick. 
static CoordType RandomBaricentric()
{
	CoordType interp;
	interp[1] = RandomDouble01();
	interp[2] = RandomDouble01();
	if(interp[1] + interp[2] > 1.0)
	{
		interp[1] = 1.0 - interp[1];
		interp[2] = 1.0 - interp[2];
		}
	
	assert(interp[1] + interp[2] <= 1.0);
	interp[0]=1.0-(interp[1] + interp[2]);
	return interp;
}

static void StratifiedMontecarlo(MetroMesh & m, VertexSampler &ps,int sampleNum)
{
	ScalarType area = Stat<MetroMesh>::ComputeMeshArea(m);
	ScalarType samplePerAreaUnit = sampleNum/area;
	//qDebug("samplePerAreaUnit %f",samplePerAreaUnit);
	// Montecarlo sampling.
	double  floatSampleNum = 0.0;
	
	FaceIterator fi;	
	for(fi=m.face.begin(); fi != m.face.end(); fi++)
		if(!(*fi).IsD())
		{
			// compute # samples in the current face (taking into account of the remainders)
			floatSampleNum += 0.5*DoubleArea(*fi) * samplePerAreaUnit;
			int faceSampleNum   = (int) floatSampleNum;
			
			// for every sample p_i in T...
			for(int i=0; i < faceSampleNum; i++)
					ps.AddFace(*fi,RandomBaricentric());
			floatSampleNum -= (double) faceSampleNum; 
		}
}

static void Montecarlo(MetroMesh & m, VertexSampler &ps,int sampleNum)
{
	typedef  std::pair<ScalarType, FacePointer> IntervalType;
	std::vector< IntervalType > intervals (m.fn+1);
	FaceIterator fi;	
	int i=0;
	intervals[i]=std::make_pair(0,FacePointer(0));
	// First loop: build a sequence of consecutive segments proportional to the triangle areas.
	for(fi=m.face.begin(); fi != m.face.end(); fi++)
		if(!(*fi).IsD())
		{
			intervals[i+1]=std::make_pair(intervals[i].first+0.5*DoubleArea(*fi), &*fi);
			++i;
		}
	ScalarType meshArea = intervals.back().first;
	for(i=0;i<sampleNum;++i)
		{
			ScalarType val = meshArea * RandomDouble01();
			// lower_bound returns the furthermost iterator i in [first, last) such that, for every iterator j in [first, i), *j < value.
			// E.g. An iterator pointing to the first element "not less than" val, or end() if every element is less than val.
			typename std::vector<IntervalType>::iterator it = lower_bound(intervals.begin(),intervals.end(),std::make_pair(val,FacePointer(0)) );
			assert(it != intervals.end());
			assert(it != intervals.begin());
			assert( (*(it-1)).first <val );
			assert( (*(it)).first >= val);
			ps.AddFace( *(*it).second, RandomBaricentric() );
		}
}
	
static ScalarType WeightedArea(FaceType f)
{
	ScalarType averageQ = ( f.V(0)->Q() + f.V(1)->Q() + f.V(2)->Q() ) /3.0;
	return DoubleArea(f)*averageQ/2.0;
}

/// Compute a sampling of the surface that is weighted by the quality
/// the area of each face is multiplied by the average of the quality of the vertices. 
/// So the a face with a zero quality on all its vertices is never sampled and a face with average quality 2 get twice the samples of a face with the same area but with an average quality of 1;
static void WeightedMontecarlo(MetroMesh & m, VertexSampler &ps, int sampleNum)
{
	assert(tri::HasPerVertexQuality(m));
	
	ScalarType weightedArea = 0;
	FaceIterator fi;
	for(fi = m.face.begin(); fi != m.face.end(); ++fi)
			if(!(*fi).IsD()) 
						weightedArea += WeightedArea(*fi);
	
	ScalarType samplePerAreaUnit = sampleNum/weightedArea;
	//qDebug("samplePerAreaUnit %f",samplePerAreaUnit);
	// Montecarlo sampling.
	double  floatSampleNum = 0.0;
	for(fi=m.face.begin(); fi != m.face.end(); fi++)
		if(!(*fi).IsD())
    {
			// compute # samples in the current face (taking into account of the remainders)
			floatSampleNum += WeightedArea(*fi) * samplePerAreaUnit;
			int faceSampleNum   = (int) floatSampleNum;
			
			// for every sample p_i in T...
			for(int i=0; i < faceSampleNum; i++)
					ps.AddFace(*fi,RandomBaricentric());
							
			floatSampleNum -= (double) faceSampleNum; 
    }
}


// Subdivision sampling of a single face. 
// return number of added samples

static int SingleFaceSubdivision(int sampleNum, const CoordType & v0, const CoordType & v1, const CoordType & v2, VertexSampler &ps, FacePointer fp, bool randSample)
{
    // recursive face subdivision.
    if(sampleNum == 1)
    {
        // ground case.
			CoordType SamplePoint;
			if(randSample) 
			{
				CoordType rb=RandomBaricentric();
				SamplePoint=v0*rb[0]+v1*rb[1]+v2*rb[2];
			}
			else SamplePoint=((v0+v1+v2)/3.0f);
			
			CoordType SampleBary;
			InterpolationParameters(*fp,SamplePoint,SampleBary[0],SampleBary[1],SampleBary[2]);
			ps.AddFace(*fp,SampleBary);
			return 1;
    }

		int s0 = sampleNum /2;
		int s1 = sampleNum-s0;
		assert(s0>0);
		assert(s1>0);
	
	  ScalarType w0 = ScalarType(s1)/ScalarType(sampleNum);
		ScalarType w1 = 1.0-w0;
    // compute the longest edge.
    double  maxd01 = SquaredDistance(v0,v1);
    double  maxd12 = SquaredDistance(v1,v2);
    double  maxd20 = SquaredDistance(v2,v0);
    int     res;
    if(maxd01 > maxd12)
        if(maxd01 > maxd20)     res = 0;
        else                    res = 2;
    else
        if(maxd12 > maxd20)     res = 1;
        else                    res = 2;
				
    int faceSampleNum=0;
    // break the input triangle along the midpoint of the longest edge.
    CoordType  pp;
    switch(res)
    {
     case 0 :    pp = v0*w0 + v1*w1;
                 faceSampleNum+=SingleFaceSubdivision(s0,v0,pp,v2,ps,fp,randSample);
                 faceSampleNum+=SingleFaceSubdivision(s1,pp,v1,v2,ps,fp,randSample);
                 break;
     case 1 :    pp =  v1*w0 + v2*w1;
                 faceSampleNum+=SingleFaceSubdivision(s0,v0,v1,pp,ps,fp,randSample);
                 faceSampleNum+=SingleFaceSubdivision(s1,v0,pp,v2,ps,fp,randSample);
                 break;
     case 2 :    pp = v0*w0 + v2*w1;
                 faceSampleNum+=SingleFaceSubdivision(s0,v0,v1,pp,ps,fp,randSample);
                 faceSampleNum+=SingleFaceSubdivision(s1,pp,v1,v2,ps,fp,randSample);
                 break;
    }
		return faceSampleNum;
}


/// Compute a sampling of the surface where the points are regularly scattered over the face surface using a recursive longest-edge subdivision rule.
static void FaceSubdivision(MetroMesh & m, VertexSampler &ps,int sampleNum, bool randSample)
{
	
	ScalarType area = Stat<MetroMesh>::ComputeMeshArea(m);
	ScalarType samplePerAreaUnit = sampleNum/area;
	//qDebug("samplePerAreaUnit %f",samplePerAreaUnit);
	std::vector<FacePointer> faceVec;
	FillAndShuffleFacePointerVector(m,faceVec);

	double  floatSampleNum = 0.0;
	int faceSampleNum;
    // Subdivision sampling.
	typename std::vector<FacePointer>::iterator fi;
    for(fi=faceVec.begin(); fi!=faceVec.end(); fi++)
    {
        // compute # samples in the current face.
        floatSampleNum += 0.5*DoubleArea(**fi) * samplePerAreaUnit;
        faceSampleNum          = (int) floatSampleNum;
        if(faceSampleNum>0)
            faceSampleNum = SingleFaceSubdivision(faceSampleNum,(**fi).V(0)->cP(), (**fi).V(1)->cP(), (**fi).V(2)->cP(),ps,*fi,randSample);
        floatSampleNum -= (double) faceSampleNum;
    }
}


// Similar Triangles sampling.
// Skip vertex and edges
// Sample per edges includes vertexes, so here we should expect  n_samples_per_edge >=4 

static int SingleFaceSimilar(FacePointer fp, VertexSampler &ps, int n_samples_per_edge)
{
		int n_samples=0;
    int         i, j;
    float segmentNum=n_samples_per_edge -1 ;
		float segmentLen = 1.0/segmentNum;
		// face sampling.
    for(i=1; i < n_samples_per_edge-1; i++)
        for(j=1; j < n_samples_per_edge-1-i; j++)
        {
            //AddSample( v0 + (V1*(double)i + V2*(double)j) );
						CoordType sampleBary(i*segmentLen,j*segmentLen, 1.0 - (i*segmentLen+j*segmentLen) ) ;
            n_samples++;
						ps.AddFace(*fp,sampleBary);
        }
	return n_samples;
}

/// Similar sampling. Each triangle is subdivided into similar triangles following a generalization of the classical 1-to-4 splitting rule of triangles. 
/// According to the level of subdivision <k> you get 1, 4 , 9, 16 , <k^2> triangles. 
/// Of these triangles we consider only internal vertices. (to avoid multiple sampling of edges and vertices).
/// Therefore the number of internal points is ((k-3)*(k-2))/2. where k is the number of point on an edge (vertex included)
//  e.g. for a k=4 you get (1*2)/2 == 1 e.g. a single point, etc.
/// So if you want N samples in a triangle i have to solve  k^2 -5k +6 - 2N = 0 

//      5 + sqrt( 1 + 8N ) 
// k = -------------------  
//             2



//template <class MetroMesh>
//void Sampling<MetroMesh>::SimilarFaceSampling()
static void FaceSimilar(MetroMesh & m, VertexSampler &ps,int sampleNum)
{
	
		ScalarType area = Stat<MetroMesh>::ComputeMeshArea(m);
		ScalarType samplePerAreaUnit = sampleNum/area;
		//qDebug("samplePerAreaUnit %f",samplePerAreaUnit);

		// Similar Triangles sampling.
    int n_samples_per_edge;
    double  n_samples_decimal = 0.0;
    FaceIterator fi;

    printf("Similar Triangles face sampling\n");
    for(fi=m.face.begin(); fi != m.face.end(); fi++)
    {
        // compute # samples in the current face.
        n_samples_decimal += 0.5*DoubleArea(*fi) * samplePerAreaUnit;
        int n_samples          = (int) n_samples_decimal;
        if(n_samples)
        {
            // face sampling.
            n_samples_per_edge = (int)((sqrt(1.0+8.0*(double)n_samples) +5.0)/2.0);
            //n_samples = 0;
            //SingleFaceSimilar((*fi).V(0)->cP(), (*fi).V(1)->cP(), (*fi).V(2)->cP(), n_samples_per_edge);
						n_samples = SingleFaceSimilar(&*fi,ps, n_samples_per_edge);
        }
        n_samples_decimal -= (double) n_samples;
    }
}


	// Rasterization fuction
	// Take a triangle 
	// T deve essere una classe funzionale che ha l'operatore ()
	// con due parametri x,y di tipo S esempio:
	// class Foo { public void operator()(int x, int y ) { ??? } };



static void SingleFaceRaster(FaceType &f,  VertexSampler &ps, const Point2<ScalarType> & v0, const Point2<ScalarType> & v1, const Point2<ScalarType> & v2)
{
	typedef ScalarType S;
		// Calcolo bounding box
	Box2i bbox;

	if(v0[0]<v1[0]) { bbox.min[0]=int(v0[0]); bbox.max[0]=int(v1[0]); }
	else            { bbox.min[0]=int(v1[0]); bbox.max[0]=int(v0[0]); }
	if(v0[1]<v1[1]) { bbox.min[1]=int(v0[1]); bbox.max[1]=int(v1[1]); }
	else            { bbox.min[1]=int(v1[1]); bbox.max[1]=int(v0[1]); }
	     if(bbox.min[0]>int(v2[0])) bbox.min[0]=int(v2[0]);
	else if(bbox.max[0]<int(v2[0])) bbox.max[0]=int(v2[0]);
	     if(bbox.min[1]>int(v2[1])) bbox.min[1]=int(v2[1]);
	else if(bbox.max[1]<int(v2[1])) bbox.max[1]=int(v2[1]);

		// Calcolo versori degli spigoli
	Point2<S> d10 = v1 - v0;
	Point2<S> d21 = v2 - v1;
	Point2<S> d02 = v0 - v2;

		// Preparazione prodotti scalari
	S b0  = (bbox.min[0]-v0[0])*d10[1] - (bbox.min[1]-v0[1])*d10[0];
	S b1  = (bbox.min[0]-v1[0])*d21[1] - (bbox.min[1]-v1[1])*d21[0];
	S b2  = (bbox.min[0]-v2[0])*d02[1] - (bbox.min[1]-v2[1])*d02[0];
		// Preparazione degli steps
	S db0 =  d10[1];
	S db1 =  d21[1];
	S db2 =  d02[1];
		// Preparazione segni
	S dn0 = -d10[0];
	S dn1 = -d21[0];
	S dn2 = -d02[0];
		// Rasterizzazione

	double de = v0[0]*v1[1]-v0[0]*v2[1]-v1[0]*v0[1]+v1[0]*v2[1]-v2[0]*v1[1]+v2[0]*v0[1];

	for(int x=bbox.min[0];x<=bbox.max[0];++x)
	{
		bool in = false;
		S n0  = b0;
		S n1  = b1;
		S n2  = b2;
		for(int y=bbox.min[1];y<=bbox.max[1];++y)
		{
			if( (n0>=0 && n1>=0 && n2>=0) || (n0<=0 && n1<=0 && n2<=0) )
			{
				CoordType baryCoord;
				baryCoord[0] =  double(-y*v1[0]+v2[0]*y+v1[1]*x-v2[0]*v1[1]+v1[0]*v2[1]-x*v2[1])/de;
				baryCoord[1] = -double( x*v0[1]-x*v2[1]-v0[0]*y+v0[0]*v2[1]-v2[0]*v0[1]+v2[0]*y)/de;
				baryCoord[2] = 1-baryCoord[0]-baryCoord[1];

				ps.AddTextureSample(f, baryCoord, Point2i(x,y));
				in = true;
			} else if(in) break;
			n0 += dn0;
			n1 += dn1;
			n2 += dn2;
		}
		b0 += db0;
		b1 += db1;
		b2 += db2;
	}
}

// check the radius constrain
static bool checkPoissonDisk(vcg::SpatialHashTable<VertexType> sht, Point3<ScalarType> p, ScalarType radius) 
{
	typename vcg::SpatialHashTable<VertexType, ScalarType>::CellIterator itBegin;
	typename vcg::SpatialHashTable<VertexType, ScalarType>::CellIterator itEnd;
	typename vcg::SpatialHashTable<VertexType, ScalarType>::CellIterator it;

	// get the samples closest to the given one
	sht.Grid(p, itBegin, itEnd);

	VertexType *v;
	VertexType d;

	for (it = itBegin; it != itEnd; it++)
	{
		v = *it;
		if (Distance(v->P(),p) < radius)
			return false;
	}

	return true;
}

/** Compute a Poisson-disk sampling of the surface.
 *  The radius of the disk is computed according to the estimated sampling density.
 *
 * This algorithm is an adaptation of the algorithm of White et al. :
 *
 * "Poisson Disk Point Set by Hierarchical Dart Throwing" 
 * K. B. White, D. Cline, P. K. Egbert,
 * IEEE Symposium on Interactive Ray Tracing, 2007,
 * 10-12 Sept. 2007, pp. 129-132.
 */
static void Poissondisk(MetroMesh &m, VertexSampler &ps, int sampleNum, int version)
{
	const int MAXLEVELS = 10; // maximum level of subdivision

	// spatial index of mesh face - used to search where to place the samples
	vcg::SpatialHashTable<FaceType, ScalarType> searchSHT;
	typename vcg::SpatialHashTable<FaceType, ScalarType>::CellIterator cellIt;

	// spatial hash table of the generated samples - used to check the radius constrain
	vcg::SpatialHashTable<VertexType, ScalarType> checkSHT;

	// initialize spatial hash table for searching
	ScalarType meshArea = Stat<MetroMesh>::ComputeMeshArea(m);
	ScalarType r = sqrt(meshArea / (0.7 * 3.1415 * sampleNum)); // 0.7 is a density factor

	ScalarType cellsize = r / sqrt(2.0);

	int sizeX = m.bbox.DimX() / r;
	int sizeY = m.bbox.DimY() / r;
	int sizeZ = m.bbox.DimZ() / r;

	Point3i gridsize(sizeX, sizeY, sizeZ);
	searchSHT.InitEmpty(m.bbox, gridsize);
	FaceIterator fi;
	for (fi = m.face.begin(); fi != m.face.end(); fi++)
		searchSHT.Add(&(*fi));

	// initialize spatial hash table for checking
	checkSHT.InitEmpty(m.bbox, gridsize);

	// sampling algorithm (version 1 - "Projection-based")
	// ---------------------------------------------------
	//
	// - extract a cell (C) from the active cell list (with probability proportional to cell's volume)
	// - with a probability proportional to the intersection between the surface and the cell
	//   generate a sample inside C and project it on the mesh 
	//   - if the sample violates the radius constrain discard it, and add the cell to the cells-to-subdivide list
	// - iterate until the active cell list is empty or a pre-defined number of subdivisions is reached
	//

	// sampling algorithm (version 2 - "Surface-based")
	// ------------------------------------------------
	//
	// - extract a cell (C) from the active cell list (with probability proportional to the cell's volume)
	// - with a probability proportional to the intersection between the surface and the cell 
	//   generate a sample on the triangles inside C
	//   - if the sample violated the radius constrain discard it, and add the cell to the cells-to-subdivide list
	// - iterate until the active cell list is empty or a pre-defined number of subdivisions is reached
	//

	std::vector<Point3i *> activeCells;
	std::vector<Point3i *> cellsToSubdivide;
	std::vector<FaceType *> faceToSubdivide;
	typename std::vector<FaceType *>::iterator faceToSubdivideIterator;
	typename std::vector<Point3i>::iterator it;
	int level = 0;

	do
	{
		// extract a cell (C) from the active cell list (with probability proportional to cell's volume)
		///////////////////////////////////////////////////////////////////////////////////////////////////

		// create active cell list
		for (it = searchSHT.AllocatedCells.begin(); it != searchSHT.AllocatedCells.end(); it++)
		{
			activeCells.push_back(&(*it));
		}

		cellsToSubdivide.clear();
		faceToSubdivide.clear();

		// shuffle active cells
		int ncell = static_cast<int>(activeCells.size());
		int index,index2;
		Point3i *temp;
		for (int i = 0; i < 100000; i++)
		{
			index = RandomInt(ncell);
			index2 =  RandomInt(ncell);
			temp = activeCells[index];
			activeCells[index] = temp;
			activeCells[index2] = temp;
		}

		// with a probability proportional to the intersection between the surface and the cell 
		// generate a sample inside C and project it on the mesh
		//////////////////////////////////////////////////////////////////////////////////////////

		for (int i = 0; i < ncell; i++)
		{
			//...TODO...
		}

		
		activeCells.clear();

		// proceed to the next level of subdivision
		searchSHT.Clear();
		gridsize[0] *= 2;
		gridsize[1] *= 2;
		gridsize[2] *= 2;
		searchSHT.InitEmpty(m.bbox, gridsize);
//		for (fi = faceToSubdivide.begin(); fi != faceToSubdivide.end(); fi++)
//			searchSHT.Add(*fi);

		level++;

	} while(level < 10);


}

//template <class MetroMesh>
//void Sampling<MetroMesh>::SimilarFaceSampling()
static void Texture(MetroMesh & m, VertexSampler &ps, int textureWidth, int textureHeight)
{
		FaceIterator fi;

		printf("Similar Triangles face sampling\n");
		for(fi=m.face.begin(); fi != m.face.end(); fi++)
				{
					Point2f ti[3];
					for(int i=0;i<3;++i)
							ti[i]=Point2f((*fi).WT(i).U() * textureWidth, (*fi).WT(i).V() * textureHeight);
					
					SingleFaceRaster(*fi,  ps, ti[0],ti[1],ti[2]);
				}
}



}; // end class


} // end namespace tri
} // end namespace vcg

#endif