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#include "precomp.hpp"
#include <algorithm>
#include <cmath>
#include <functional>
#include <fstream>
#include <limits>
#include <set>
using namespace cv;
/********************************* local utility *********************************/
namespace
{
const static Scalar colors[] =
{
CV_RGB(255, 0, 0),
CV_RGB( 0, 255, 0),
CV_RGB( 0, 0, 255),
CV_RGB(255, 255, 0),
CV_RGB(255, 0, 255),
CV_RGB( 0, 255, 255),
CV_RGB(255, 127, 127),
CV_RGB(127, 127, 255),
CV_RGB(127, 255, 127),
CV_RGB(255, 255, 127),
CV_RGB(127, 255, 255),
CV_RGB(255, 127, 255),
CV_RGB(127, 0, 0),
CV_RGB( 0, 127, 0),
CV_RGB( 0, 0, 127),
CV_RGB(127, 127, 0),
CV_RGB(127, 0, 127),
CV_RGB( 0, 127, 127)
};
size_t colors_mum = sizeof(colors)/sizeof(colors[0]);
template<class FwIt, class T> inline void _iota(FwIt first, FwIt last, T value)
{
while(first != last) *first++ = value++;
}
void computeNormals( const Octree& Octree, const std::vector<Point3f>& centers, std::vector<Point3f>& normals,
std::vector<uchar>& mask, float normalRadius, int minNeighbors = 20)
{
size_t normals_size = centers.size();
normals.resize(normals_size);
if (mask.size() != normals_size)
{
size_t m = mask.size();
mask.resize(normals_size);
if (normals_size > m)
for(; m < normals_size; ++m)
mask[m] = 1;
}
std::vector<Point3f> buffer;
buffer.reserve(128);
SVD svd;
const static Point3f zero(0.f, 0.f, 0.f);
for(size_t n = 0; n < normals_size; ++n)
{
if (mask[n] == 0)
continue;
const Point3f& center = centers[n];
Octree.getPointsWithinSphere(center, normalRadius, buffer);
int buf_size = (int)buffer.size();
if (buf_size < minNeighbors)
{
normals[n] = Mesh3D::allzero;
mask[n] = 0;
continue;
}
//find the mean point for normalization
Point3f mean(Mesh3D::allzero);
for(int i = 0; i < buf_size; ++i)
mean += buffer[i];
mean.x /= buf_size;
mean.y /= buf_size;
mean.z /= buf_size;
double pxpx = 0;
double pypy = 0;
double pzpz = 0;
double pxpy = 0;
double pxpz = 0;
double pypz = 0;
for(int i = 0; i < buf_size; ++i)
{
const Point3f& p = buffer[i];
pxpx += (p.x - mean.x) * (p.x - mean.x);
pypy += (p.y - mean.y) * (p.y - mean.y);
pzpz += (p.z - mean.z) * (p.z - mean.z);
pxpy += (p.x - mean.x) * (p.y - mean.y);
pxpz += (p.x - mean.x) * (p.z - mean.z);
pypz += (p.y - mean.y) * (p.z - mean.z);
}
//create and populate matrix with normalized nbrs
double M_data[] = { pxpx, pxpy, pxpz, /**/ pxpy, pypy, pypz, /**/ pxpz, pypz, pzpz };
Mat M(3, 3, CV_64F, M_data);
svd(M, SVD::MODIFY_A);
/*normals[n] = Point3f( (float)((double*)svd.vt.data)[6],
(float)((double*)svd.vt.data)[7],
(float)((double*)svd.vt.data)[8] );*/
normals[n] = reinterpret_cast<Point3d*>(svd.vt.data)[2];
mask[n] = 1;
}
}
void initRotationMat(const Point3f& n, float out[9])
{
double pitch = atan2(n.x, n.z);
double pmat[] = { cos(pitch), 0, -sin(pitch) ,
0 , 1, 0 ,
sin(pitch), 0, cos(pitch) };
double roll = atan2((double)n.y, n.x * pmat[3*2+0] + n.z * pmat[3*2+2]);
double rmat[] = { 1, 0, 0,
0, cos(roll), -sin(roll) ,
0, sin(roll), cos(roll) };
for(int i = 0; i < 3; ++i)
for(int j = 0; j < 3; ++j)
out[3*i+j] = (float)(rmat[3*i+0]*pmat[3*0+j] +
rmat[3*i+1]*pmat[3*1+j] + rmat[3*i+2]*pmat[3*2+j]);
}
void transform(const Point3f& in, float matrix[9], Point3f& out)
{
out.x = in.x * matrix[3*0+0] + in.y * matrix[3*0+1] + in.z * matrix[3*0+2];
out.y = in.x * matrix[3*1+0] + in.y * matrix[3*1+1] + in.z * matrix[3*1+2];
out.z = in.x * matrix[3*2+0] + in.y * matrix[3*2+1] + in.z * matrix[3*2+2];
}
#if CV_SSE2
void convertTransformMatrix(const float* matrix, float* sseMatrix)
{
sseMatrix[0] = matrix[0]; sseMatrix[1] = matrix[3]; sseMatrix[2] = matrix[6]; sseMatrix[3] = 0;
sseMatrix[4] = matrix[1]; sseMatrix[5] = matrix[4]; sseMatrix[6] = matrix[7]; sseMatrix[7] = 0;
sseMatrix[8] = matrix[2]; sseMatrix[9] = matrix[5]; sseMatrix[10] = matrix[8]; sseMatrix[11] = 0;
}
inline __m128 transformSSE(const __m128* matrix, const __m128& in)
{
assert(((size_t)matrix & 15) == 0);
__m128 a0 = _mm_mul_ps(_mm_load_ps((float*)(matrix+0)), _mm_shuffle_ps(in,in,_MM_SHUFFLE(0,0,0,0)));
__m128 a1 = _mm_mul_ps(_mm_load_ps((float*)(matrix+1)), _mm_shuffle_ps(in,in,_MM_SHUFFLE(1,1,1,1)));
__m128 a2 = _mm_mul_ps(_mm_load_ps((float*)(matrix+2)), _mm_shuffle_ps(in,in,_MM_SHUFFLE(2,2,2,2)));
return _mm_add_ps(_mm_add_ps(a0,a1),a2);
}
inline __m128i _mm_mullo_epi32_emul(const __m128i& a, __m128i& b)
{
__m128i pack = _mm_packs_epi32(a, a);
return _mm_unpacklo_epi16(_mm_mullo_epi16(pack, b), _mm_mulhi_epi16(pack, b));
}
#endif
void computeSpinImages( const Octree& Octree, const std::vector<Point3f>& points, const std::vector<Point3f>& normals,
std::vector<uchar>& mask, Mat& spinImages, int imageWidth, float binSize)
{
float pixelsPerMeter = 1.f / binSize;
float support = imageWidth * binSize;
assert(normals.size() == points.size());
assert(mask.size() == points.size());
size_t points_size = points.size();
mask.resize(points_size);
int height = imageWidth;
int width = imageWidth;
spinImages.create( (int)points_size, width*height, CV_32F );
int nthreads = getNumThreads();
int i;
std::vector< std::vector<Point3f> > pointsInSpherePool(nthreads);
for(i = 0; i < nthreads; i++)
pointsInSpherePool[i].reserve(2048);
float halfSuppport = support / 2;
float searchRad = support * std::sqrt(5.f) / 2; // std::sqrt(sup*sup + (sup/2) * (sup/2) )
#ifdef _OPENMP
#pragma omp parallel for num_threads(nthreads)
#endif
for(i = 0; i < (int)points_size; ++i)
{
if (mask[i] == 0)
continue;
int t = cvGetThreadNum();
std::vector<Point3f>& pointsInSphere = pointsInSpherePool[t];
const Point3f& center = points[i];
Octree.getPointsWithinSphere(center, searchRad, pointsInSphere);
size_t inSphere_size = pointsInSphere.size();
if (inSphere_size == 0)
{
mask[i] = 0;
continue;
}
const Point3f& normal = normals[i];
float rotmat[9];
initRotationMat(normal, rotmat);
Point3f new_center;
transform(center, rotmat, new_center);
Mat spinImage = spinImages.row(i).reshape(1, height);
float* spinImageData = (float*)spinImage.data;
int step = width;
spinImage = Scalar(0.);
float alpha, beta;
size_t j = 0;
#if CV_SSE2
if (inSphere_size > 4 && checkHardwareSupport(CV_CPU_SSE2))
{
__m128 rotmatSSE[3];
convertTransformMatrix(rotmat, (float*)rotmatSSE);
__m128 center_x4 = _mm_set1_ps(new_center.x);
__m128 center_y4 = _mm_set1_ps(new_center.y);
__m128 center_z4 = _mm_set1_ps(new_center.z + halfSuppport);
__m128 ppm4 = _mm_set1_ps(pixelsPerMeter);
__m128i height4m1 = _mm_set1_epi32(spinImage.rows-1);
__m128i width4m1 = _mm_set1_epi32(spinImage.cols-1);
assert( spinImage.step <= 0xffff );
__m128i step4 = _mm_set1_epi16((short)step);
__m128i zero4 = _mm_setzero_si128();
__m128i one4i = _mm_set1_epi32(1);
__m128 zero4f = _mm_setzero_ps();
__m128 one4f = _mm_set1_ps(1.f);
//__m128 two4f = _mm_set1_ps(2.f);
int CV_DECL_ALIGNED(16) o[4];
for (; j <= inSphere_size - 5; j += 4)
{
__m128 pt0 = transformSSE(rotmatSSE, _mm_loadu_ps((float*)&pointsInSphere[j+0])); // x0 y0 z0 .
__m128 pt1 = transformSSE(rotmatSSE, _mm_loadu_ps((float*)&pointsInSphere[j+1])); // x1 y1 z1 .
__m128 pt2 = transformSSE(rotmatSSE, _mm_loadu_ps((float*)&pointsInSphere[j+2])); // x2 y2 z2 .
__m128 pt3 = transformSSE(rotmatSSE, _mm_loadu_ps((float*)&pointsInSphere[j+3])); // x3 y3 z3 .
__m128 z0 = _mm_unpackhi_ps(pt0, pt1); // z0 z1 . .
__m128 z1 = _mm_unpackhi_ps(pt2, pt3); // z2 z3 . .
__m128 beta4 = _mm_sub_ps(center_z4, _mm_movelh_ps(z0, z1)); // b0 b1 b2 b3
__m128 xy0 = _mm_unpacklo_ps(pt0, pt1); // x0 x1 y0 y1
__m128 xy1 = _mm_unpacklo_ps(pt2, pt3); // x2 x3 y2 y3
__m128 x4 = _mm_movelh_ps(xy0, xy1); // x0 x1 x2 x3
__m128 y4 = _mm_movehl_ps(xy1, xy0); // y0 y1 y2 y3
x4 = _mm_sub_ps(x4, center_x4);
y4 = _mm_sub_ps(y4, center_y4);
__m128 alpha4 = _mm_sqrt_ps(_mm_add_ps(_mm_mul_ps(x4,x4),_mm_mul_ps(y4,y4)));
__m128 n1f4 = _mm_mul_ps( beta4, ppm4); /* beta4 float */
__m128 n2f4 = _mm_mul_ps(alpha4, ppm4); /* alpha4 float */
/* floor */
__m128i n1 = _mm_sub_epi32(_mm_cvttps_epi32( _mm_add_ps( n1f4, one4f ) ), one4i);
__m128i n2 = _mm_sub_epi32(_mm_cvttps_epi32( _mm_add_ps( n2f4, one4f ) ), one4i);
__m128 f1 = _mm_sub_ps( n1f4, _mm_cvtepi32_ps(n1) ); /* { beta4 } */
__m128 f2 = _mm_sub_ps( n2f4, _mm_cvtepi32_ps(n2) ); /* { alpha4 } */
__m128 f1f2 = _mm_mul_ps(f1, f2); // f1 * f2
__m128 omf1omf2 = _mm_add_ps(_mm_sub_ps(_mm_sub_ps(one4f, f2), f1), f1f2); // (1-f1) * (1-f2)
__m128i _mask = _mm_and_si128(
_mm_andnot_si128(_mm_cmpgt_epi32(zero4, n1), _mm_cmpgt_epi32(height4m1, n1)),
_mm_andnot_si128(_mm_cmpgt_epi32(zero4, n2), _mm_cmpgt_epi32(width4m1, n2)));
__m128 maskf = _mm_cmpneq_ps(_mm_cvtepi32_ps(_mask), zero4f);
__m128 v00 = _mm_and_ps( omf1omf2 , maskf); // a00 b00 c00 d00
__m128 v01 = _mm_and_ps( _mm_sub_ps( f2, f1f2 ), maskf); // a01 b01 c01 d01
__m128 v10 = _mm_and_ps( _mm_sub_ps( f1, f1f2 ), maskf); // a10 b10 c10 d10
__m128 v11 = _mm_and_ps( f1f2 , maskf); // a11 b11 c11 d11
__m128i ofs4 = _mm_and_si128(_mm_add_epi32(_mm_mullo_epi32_emul(n1, step4), n2), _mask);
_mm_store_si128((__m128i*)o, ofs4);
__m128 t0 = _mm_unpacklo_ps(v00, v01); // a00 a01 b00 b01
__m128 t1 = _mm_unpacklo_ps(v10, v11); // a10 a11 b10 b11
__m128 u0 = _mm_movelh_ps(t0, t1); // a00 a01 a10 a11
__m128 u1 = _mm_movehl_ps(t1, t0); // b00 b01 b10 b11
__m128 x0 = _mm_loadl_pi(u0, (__m64*)(spinImageData+o[0])); // x00 x01
x0 = _mm_loadh_pi(x0, (__m64*)(spinImageData+o[0]+step)); // x00 x01 x10 x11
x0 = _mm_add_ps(x0, u0);
_mm_storel_pi((__m64*)(spinImageData+o[0]), x0);
_mm_storeh_pi((__m64*)(spinImageData+o[0]+step), x0);
x0 = _mm_loadl_pi(x0, (__m64*)(spinImageData+o[1])); // y00 y01
x0 = _mm_loadh_pi(x0, (__m64*)(spinImageData+o[1]+step)); // y00 y01 y10 y11
x0 = _mm_add_ps(x0, u1);
_mm_storel_pi((__m64*)(spinImageData+o[1]), x0);
_mm_storeh_pi((__m64*)(spinImageData+o[1]+step), x0);
t0 = _mm_unpackhi_ps(v00, v01); // c00 c01 d00 d01
t1 = _mm_unpackhi_ps(v10, v11); // c10 c11 d10 d11
u0 = _mm_movelh_ps(t0, t1); // c00 c01 c10 c11
u1 = _mm_movehl_ps(t1, t0); // d00 d01 d10 d11
x0 = _mm_loadl_pi(x0, (__m64*)(spinImageData+o[2])); // z00 z01
x0 = _mm_loadh_pi(x0, (__m64*)(spinImageData+o[2]+step)); // z00 z01 z10 z11
x0 = _mm_add_ps(x0, u0);
_mm_storel_pi((__m64*)(spinImageData+o[2]), x0);
_mm_storeh_pi((__m64*)(spinImageData+o[2]+step), x0);
x0 = _mm_loadl_pi(x0, (__m64*)(spinImageData+o[3])); // w00 w01
x0 = _mm_loadh_pi(x0, (__m64*)(spinImageData+o[3]+step)); // w00 w01 w10 w11
x0 = _mm_add_ps(x0, u1);
_mm_storel_pi((__m64*)(spinImageData+o[3]), x0);
_mm_storeh_pi((__m64*)(spinImageData+o[3]+step), x0);
}
}
#endif
for (; j < inSphere_size; ++j)
{
Point3f pt;
transform(pointsInSphere[j], rotmat, pt);
beta = halfSuppport - (pt.z - new_center.z);
if (beta >= support || beta < 0)
continue;
alpha = std::sqrt( (new_center.x - pt.x) * (new_center.x - pt.x) +
(new_center.y - pt.y) * (new_center.y - pt.y) );
float n1f = beta * pixelsPerMeter;
float n2f = alpha * pixelsPerMeter;
int n1 = cvFloor(n1f);
int n2 = cvFloor(n2f);
float f1 = n1f - n1;
float f2 = n2f - n2;
if ((unsigned)n1 >= (unsigned)(spinImage.rows-1) ||
(unsigned)n2 >= (unsigned)(spinImage.cols-1))
continue;
float *cellptr = spinImageData + step * n1 + n2;
float f1f2 = f1*f2;
cellptr[0] += 1 - f1 - f2 + f1f2;
cellptr[1] += f2 - f1f2;
cellptr[step] += f1 - f1f2;
cellptr[step+1] += f1f2;
}
mask[i] = 1;
}
}
}
/********************************* Mesh3D *********************************/
const Point3f cv::Mesh3D::allzero(0.f, 0.f, 0.f);
cv::Mesh3D::Mesh3D() { resolution = -1; }
cv::Mesh3D::Mesh3D(const std::vector<Point3f>& _vtx)
{
resolution = -1;
vtx.resize(_vtx.size());
std::copy(_vtx.begin(), _vtx.end(), vtx.begin());
}
cv::Mesh3D::~Mesh3D() {}
void cv::Mesh3D::buildOctree() { if (octree.getNodes().empty()) octree.buildTree(vtx); }
void cv::Mesh3D::clearOctree(){ octree = Octree(); }
float cv::Mesh3D::estimateResolution(float /*tryRatio*/)
{
#if 0
const int neighbors = 3;
const int minReasonable = 10;
int tryNum = static_cast<int>(tryRatio * vtx.size());
tryNum = std::min(std::max(tryNum, minReasonable), (int)vtx.size());
CvMat desc = cvMat((int)vtx.size(), 3, CV_32F, &vtx[0]);
CvFeatureTree* tr = cvCreateKDTree(&desc);
std::vector<double> dist(tryNum * neighbors);
std::vector<int> inds(tryNum * neighbors);
std::vector<Point3f> query;
RNG& rng = theRNG();
for(int i = 0; i < tryNum; ++i)
query.push_back(vtx[rng.next() % vtx.size()]);
CvMat cvinds = cvMat( (int)tryNum, neighbors, CV_32S, &inds[0] );
CvMat cvdist = cvMat( (int)tryNum, neighbors, CV_64F, &dist[0] );
CvMat cvquery = cvMat( (int)tryNum, 3, CV_32F, &query[0] );
cvFindFeatures(tr, &cvquery, &cvinds, &cvdist, neighbors, 50);
cvReleaseFeatureTree(tr);
const int invalid_dist = -2;
for(int i = 0; i < tryNum; ++i)
if (inds[i] == -1)
dist[i] = invalid_dist;
dist.resize(remove(dist.begin(), dist.end(), invalid_dist) - dist.begin());
sort(dist, std::less<double>());
return resolution = (float)dist[ dist.size() / 2 ];
#else
CV_Error(CV_StsNotImplemented, "");
return 1.f;
#endif
}
void cv::Mesh3D::computeNormals(float normalRadius, int minNeighbors)
{
buildOctree();
std::vector<uchar> mask;
::computeNormals(octree, vtx, normals, mask, normalRadius, minNeighbors);
}
void cv::Mesh3D::computeNormals(const std::vector<int>& subset, float normalRadius, int minNeighbors)
{
buildOctree();
std::vector<uchar> mask(vtx.size(), 0);
for(size_t i = 0; i < subset.size(); ++i)
mask[subset[i]] = 1;
::computeNormals(octree, vtx, normals, mask, normalRadius, minNeighbors);
}
void cv::Mesh3D::writeAsVrml(const std::string& file, const std::vector<Scalar>& _colors) const
{
std::ofstream ofs(file.c_str());
ofs << "#VRML V2.0 utf8" << std::endl;
ofs << "Shape" << std::endl << "{" << std::endl;
ofs << "geometry PointSet" << std::endl << "{" << std::endl;
ofs << "coord Coordinate" << std::endl << "{" << std::endl;
ofs << "point[" << std::endl;
for(size_t i = 0; i < vtx.size(); ++i)
ofs << vtx[i].x << " " << vtx[i].y << " " << vtx[i].z << std::endl;
ofs << "]" << std::endl; //point[
ofs << "}" << std::endl; //Coordinate{
if (vtx.size() == _colors.size())
{
ofs << "color Color" << std::endl << "{" << std::endl;
ofs << "color[" << std::endl;
for(size_t i = 0; i < _colors.size(); ++i)
ofs << (float)_colors[i][2] << " " << (float)_colors[i][1] << " " << (float)_colors[i][0] << std::endl;
ofs << "]" << std::endl; //color[
ofs << "}" << std::endl; //color Color{
}
ofs << "}" << std::endl; //PointSet{
ofs << "}" << std::endl; //Shape{
}
/********************************* SpinImageModel *********************************/
bool cv::SpinImageModel::spinCorrelation(const Mat& spin1, const Mat& spin2, float lambda, float& result)
{
struct Math { static double atanh(double x) { return 0.5 * std::log( (1 + x) / (1 - x) ); } };
const float* s1 = spin1.ptr<float>();
const float* s2 = spin2.ptr<float>();
int spin_sz = spin1.cols * spin1.rows;
double sum1 = 0.0, sum2 = 0.0, sum12 = 0.0, sum11 = 0.0, sum22 = 0.0;
int N = 0;
int i = 0;
#if CV_SSE2//____________TEMPORARY_DISABLED_____________
float CV_DECL_ALIGNED(16) su1[4], su2[4], su11[4], su22[4], su12[4], n[4];
__m128 zerof4 = _mm_setzero_ps();
__m128 onef4 = _mm_set1_ps(1.f);
__m128 Nf4 = zerof4;
__m128 sum1f4 = zerof4;
__m128 sum2f4 = zerof4;
__m128 sum11f4 = zerof4;
__m128 sum22f4 = zerof4;
__m128 sum12f4 = zerof4;
for(; i < spin_sz - 5; i += 4)
{
__m128 v1f4 = _mm_loadu_ps(s1 + i);
__m128 v2f4 = _mm_loadu_ps(s2 + i);
__m128 mskf4 = _mm_and_ps(_mm_cmpneq_ps(v1f4, zerof4), _mm_cmpneq_ps(v2f4, zerof4));
if( !_mm_movemask_ps(mskf4) )
continue;
Nf4 = _mm_add_ps(Nf4, _mm_and_ps(onef4, mskf4));
v1f4 = _mm_and_ps(v1f4, mskf4);
v2f4 = _mm_and_ps(v2f4, mskf4);
sum1f4 = _mm_add_ps(sum1f4, v1f4);
sum2f4 = _mm_add_ps(sum2f4, v2f4);
sum11f4 = _mm_add_ps(sum11f4, _mm_mul_ps(v1f4, v1f4));
sum22f4 = _mm_add_ps(sum22f4, _mm_mul_ps(v2f4, v2f4));
sum12f4 = _mm_add_ps(sum12f4, _mm_mul_ps(v1f4, v2f4));
}
_mm_store_ps( su1, sum1f4 );
_mm_store_ps( su2, sum2f4 );
_mm_store_ps(su11, sum11f4 );
_mm_store_ps(su22, sum22f4 );
_mm_store_ps(su12, sum12f4 );
_mm_store_ps(n, Nf4 );
N = static_cast<int>(n[0] + n[1] + n[2] + n[3]);
sum1 = su1[0] + su1[1] + su1[2] + su1[3];
sum2 = su2[0] + su2[1] + su2[2] + su2[3];
sum11 = su11[0] + su11[1] + su11[2] + su11[3];
sum22 = su22[0] + su22[1] + su22[2] + su22[3];
sum12 = su12[0] + su12[1] + su12[2] + su12[3];
#endif
for(; i < spin_sz; ++i)
{
float v1 = s1[i];
float v2 = s2[i];
if( !v1 || !v2 )
continue;
N++;
sum1 += v1;
sum2 += v2;
sum11 += v1 * v1;
sum22 += v2 * v2;
sum12 += v1 * v2;
}
if( N < 4 )
return false;
double sum1sum1 = sum1 * sum1;
double sum2sum2 = sum2 * sum2;
double Nsum12 = N * sum12;
double Nsum11 = N * sum11;
double Nsum22 = N * sum22;
if (Nsum11 == sum1sum1 || Nsum22 == sum2sum2)
return false;
double corr = (Nsum12 - sum1 * sum2) / std::sqrt( (Nsum11 - sum1sum1) * (Nsum22 - sum2sum2) );
double atanh = Math::atanh(corr);
result = (float)( atanh * atanh - lambda * ( 1.0 / (N - 3) ) );
return true;
}
inline Point2f cv::SpinImageModel::calcSpinMapCoo(const Point3f& p, const Point3f& v, const Point3f& n)
{
/*Point3f PmV(p.x - v.x, p.y - v.y, p.z - v.z);
float normalNorm = (float)norm(n);
float beta = PmV.dot(n) / normalNorm;
float pmcNorm = (float)norm(PmV);
float alpha = std::sqrt( pmcNorm * pmcNorm - beta * beta);
return Point2f(alpha, beta);*/
float pmv_x = p.x - v.x, pmv_y = p.y - v.y, pmv_z = p.z - v.z;
float beta = (pmv_x * n.x + pmv_y + n.y + pmv_z * n.z) / std::sqrt(n.x * n.x + n.y * n.y + n.z * n.z);
float alpha = std::sqrt( pmv_x * pmv_x + pmv_y * pmv_y + pmv_z * pmv_z - beta * beta);
return Point2f(alpha, beta);
}
inline float cv::SpinImageModel::geometricConsistency(const Point3f& pointScene1, const Point3f& normalScene1,
const Point3f& pointModel1, const Point3f& normalModel1,
const Point3f& pointScene2, const Point3f& normalScene2,
const Point3f& pointModel2, const Point3f& normalModel2)
{
Point2f Sm2_to_m1, Ss2_to_s1;
Point2f Sm1_to_m2, Ss1_to_s2;
double n_Sm2_to_m1 = norm(Sm2_to_m1 = calcSpinMapCoo(pointModel2, pointModel1, normalModel1));
double n_Ss2_to_s1 = norm(Ss2_to_s1 = calcSpinMapCoo(pointScene2, pointScene1, normalScene1));
double gc21 = 2 * norm(Sm2_to_m1 - Ss2_to_s1) / (n_Sm2_to_m1 + n_Ss2_to_s1 ) ;
double n_Sm1_to_m2 = norm(Sm1_to_m2 = calcSpinMapCoo(pointModel1, pointModel2, normalModel2));
double n_Ss1_to_s2 = norm(Ss1_to_s2 = calcSpinMapCoo(pointScene1, pointScene2, normalScene2));
double gc12 = 2 * norm(Sm1_to_m2 - Ss1_to_s2) / (n_Sm1_to_m2 + n_Ss1_to_s2 ) ;
return (float)std::max(gc12, gc21);
}
inline float cv::SpinImageModel::groupingCreteria(const Point3f& pointScene1, const Point3f& normalScene1,
const Point3f& pointModel1, const Point3f& normalModel1,
const Point3f& pointScene2, const Point3f& normalScene2,
const Point3f& pointModel2, const Point3f& normalModel2,
float gamma)
{
Point2f Sm2_to_m1, Ss2_to_s1;
Point2f Sm1_to_m2, Ss1_to_s2;
float gamma05_inv = 0.5f/gamma;
double n_Sm2_to_m1 = norm(Sm2_to_m1 = calcSpinMapCoo(pointModel2, pointModel1, normalModel1));
double n_Ss2_to_s1 = norm(Ss2_to_s1 = calcSpinMapCoo(pointScene2, pointScene1, normalScene1));
double gc21 = 2 * norm(Sm2_to_m1 - Ss2_to_s1) / (n_Sm2_to_m1 + n_Ss2_to_s1 );
double wgc21 = gc21 / (1 - std::exp( -(n_Sm2_to_m1 + n_Ss2_to_s1) * gamma05_inv ) );
double n_Sm1_to_m2 = norm(Sm1_to_m2 = calcSpinMapCoo(pointModel1, pointModel2, normalModel2));
double n_Ss1_to_s2 = norm(Ss1_to_s2 = calcSpinMapCoo(pointScene1, pointScene2, normalScene2));
double gc12 = 2 * norm(Sm1_to_m2 - Ss1_to_s2) / (n_Sm1_to_m2 + n_Ss1_to_s2 );
double wgc12 = gc12 / (1 - std::exp( -(n_Sm1_to_m2 + n_Ss1_to_s2) * gamma05_inv ) );
return (float)std::max(wgc12, wgc21);
}
cv::SpinImageModel::SpinImageModel(const Mesh3D& _mesh) : mesh(_mesh) , out(0)
{
if (mesh.vtx.empty())
throw Mesh3D::EmptyMeshException();
defaultParams();
}
cv::SpinImageModel::SpinImageModel() : out(0) { defaultParams(); }
cv::SpinImageModel::~SpinImageModel() {}
void cv::SpinImageModel::setLogger(std::ostream* log) { out = log; }
void cv::SpinImageModel::defaultParams()
{
normalRadius = 0.f;
minNeighbors = 20;
binSize = 0.f; /* autodetect according to mesh resolution */
imageWidth = 32;
lambda = 0.f; /* autodetect according to medan non zero images bin */
gamma = 0.f; /* autodetect according to mesh resolution */
T_GeometriccConsistency = 0.25f;
T_GroupingCorespondances = 0.25f;
};
Mat cv::SpinImageModel::packRandomScaledSpins(bool separateScale, size_t xCount, size_t yCount) const
{
int spinNum = (int)getSpinCount();
int num = std::min(spinNum, (int)(xCount * yCount));
if (num == 0)
return Mat();
RNG& rng = theRNG();
std::vector<Mat> spins;
for(int i = 0; i < num; ++i)
spins.push_back(getSpinImage( rng.next() % spinNum ).reshape(1, imageWidth));
if (separateScale)
for(int i = 0; i < num; ++i)
{
double max;
Mat spin8u;
minMaxLoc(spins[i], 0, &max);
spins[i].convertTo(spin8u, CV_8U, -255.0/max, 255.0);
spins[i] = spin8u;
}
else
{
double totalMax = 0;
for(int i = 0; i < num; ++i)
{
double m;
minMaxLoc(spins[i], 0, &m);
totalMax = std::max(m, totalMax);
}
for(int i = 0; i < num; ++i)
{
Mat spin8u;
spins[i].convertTo(spin8u, CV_8U, -255.0/totalMax, 255.0);
spins[i] = spin8u;
}
}
int sz = spins.front().cols;
Mat result((int)(yCount * sz + (yCount - 1)), (int)(xCount * sz + (xCount - 1)), CV_8UC3);
result = colors[(static_cast<int64>(cvGetTickCount()/cvGetTickFrequency())/1000) % colors_mum];
int pos = 0;
for(int y = 0; y < (int)yCount; ++y)
for(int x = 0; x < (int)xCount; ++x)
if (pos < num)
{
int starty = (y + 0) * sz + y;
int endy = (y + 1) * sz + y;
int startx = (x + 0) * sz + x;
int endx = (x + 1) * sz + x;
Mat color;
cvtColor(spins[pos++], color, CV_GRAY2BGR);
Mat roi = result(Range(starty, endy), Range(startx, endx));
color.copyTo(roi);
}
return result;
}
void cv::SpinImageModel::selectRandomSubset(float ratio)
{
ratio = std::min(std::max(ratio, 0.f), 1.f);
size_t vtxSize = mesh.vtx.size();
size_t setSize = static_cast<size_t>(vtxSize * ratio);
if (setSize == 0)
{
subset.clear();
}
else if (setSize == vtxSize)
{
subset.resize(vtxSize);
_iota(subset.begin(), subset.end(), 0);
}
else
{
RNG& rnd = theRNG();
std::vector<size_t> left(vtxSize);
_iota(left.begin(), left.end(), (size_t)0);
subset.resize(setSize);
for(size_t i = 0; i < setSize; ++i)
{
int pos = rnd.next() % (int)left.size();
subset[i] = (int)left[pos];
left[pos] = left.back();
left.resize(left.size() - 1);
}
sort(subset, std::less<int>());
}
}
void cv::SpinImageModel::setSubset(const std::vector<int>& ss)
{
subset = ss;
}
void cv::SpinImageModel::repackSpinImages(const std::vector<uchar>& mask, Mat& _spinImages, bool reAlloc) const
{
if (reAlloc)
{
size_t spinCount = mask.size() - std::count(mask.begin(), mask.end(), (uchar)0);
Mat newImgs((int)spinCount, _spinImages.cols, _spinImages.type());
int pos = 0;
for(size_t t = 0; t < mask.size(); ++t)
if (mask[t])
{
Mat row = newImgs.row(pos++);
_spinImages.row((int)t).copyTo(row);
}
_spinImages = newImgs;
}
else
{
int last = (int)mask.size();
int dest = (int)(std::find(mask.begin(), mask.end(), (uchar)0) - mask.begin());
if (dest == last)
return;
int first = dest + 1;
for (; first != last; ++first)
if (mask[first] != 0)
{
Mat row = _spinImages.row(dest);
_spinImages.row(first).copyTo(row);
++dest;
}
_spinImages = _spinImages.rowRange(0, dest);
}
}
void cv::SpinImageModel::compute()
{
/* estimate binSize */
if (binSize == 0.f)
{
if (mesh.resolution == -1.f)
mesh.estimateResolution();
binSize = mesh.resolution;
}
/* estimate normalRadius */
normalRadius = normalRadius != 0.f ? normalRadius : binSize * imageWidth / 2;
mesh.buildOctree();
if (subset.empty())
{
mesh.computeNormals(normalRadius, minNeighbors);
subset.resize(mesh.vtx.size());
_iota(subset.begin(), subset.end(), 0);
}
else
mesh.computeNormals(subset, normalRadius, minNeighbors);
std::vector<uchar> mask(mesh.vtx.size(), 0);
for(size_t i = 0; i < subset.size(); ++i)
if (mesh.normals[subset[i]] == Mesh3D::allzero)
subset[i] = -1;
else
mask[subset[i]] = 1;
subset.resize( std::remove(subset.begin(), subset.end(), -1) - subset.begin() );
std::vector<Point3f> vtx;
std::vector<Point3f> normals;
for(size_t i = 0; i < mask.size(); ++i)
if(mask[i])
{
vtx.push_back(mesh.vtx[i]);
normals.push_back(mesh.normals[i]);
}
std::vector<uchar> spinMask(vtx.size(), 1);
computeSpinImages( mesh.octree, vtx, normals, spinMask, spinImages, imageWidth, binSize);
repackSpinImages(spinMask, spinImages);
size_t mask_pos = 0;
for(size_t i = 0; i < mask.size(); ++i)
if(mask[i])
if (spinMask[mask_pos++] == 0)
subset.resize( std::remove(subset.begin(), subset.end(), (int)i) - subset.begin() );
}
void cv::SpinImageModel::matchSpinToModel(const Mat& spin, std::vector<int>& indeces, std::vector<float>& corrCoeffs, bool useExtremeOutliers) const
{
const SpinImageModel& model = *this;
indeces.clear();
corrCoeffs.clear();
std::vector<float> corrs(model.spinImages.rows);
std::vector<uchar> masks(model.spinImages.rows);
std::vector<float> cleanCorrs;
cleanCorrs.reserve(model.spinImages.rows);
for(int i = 0; i < model.spinImages.rows; ++i)
{
masks[i] = spinCorrelation(spin, model.spinImages.row(i), model.lambda, corrs[i]);
if (masks[i])
cleanCorrs.push_back(corrs[i]);
}
/* Filtering by measure histogram */
size_t total = cleanCorrs.size();
if(total < 5)
return;
sort(cleanCorrs, std::less<float>());
float lower_fourth = cleanCorrs[(1 * total) / 4 - 1];
float upper_fourth = cleanCorrs[(3 * total) / 4 - 0];
float fourth_spread = upper_fourth - lower_fourth;
//extreme or moderate?
float coef = useExtremeOutliers ? 3.0f : 1.5f;
float histThresHi = upper_fourth + coef * fourth_spread;
//float histThresLo = lower_fourth - coef * fourth_spread;
for(size_t i = 0; i < corrs.size(); ++i)
if (masks[i])
if (/* corrs[i] < histThresLo || */ corrs[i] > histThresHi)
{
indeces.push_back((int)i);
corrCoeffs.push_back(corrs[i]);
}
}
namespace
{
struct Match
{
int sceneInd;
int modelInd;
float measure;
Match(){}
Match(int sceneIndex, int modelIndex, float coeff) : sceneInd(sceneIndex), modelInd(modelIndex), measure(coeff) {}
operator float() const { return measure; }
};
typedef std::set<size_t> group_t;
typedef group_t::iterator iter;
typedef group_t::const_iterator citer;
struct WgcHelper
{
const group_t& grp;
const Mat& mat;
WgcHelper(const group_t& group, const Mat& groupingMat) : grp(group), mat(groupingMat){}
float operator()(size_t leftInd) const { return Wgc(leftInd, grp); }
/* Wgc( correspondence_C, group_{C1..Cn} ) = max_i=1..n_( Wgc(C, Ci) ) */
float Wgc(const size_t corespInd, const group_t& group) const
{
const float* wgcLine = mat.ptr<float>((int)corespInd);
float maximum = std::numeric_limits<float>::min();
for(citer pos = group.begin(); pos != group.end(); ++pos)
maximum = std::max(wgcLine[*pos], maximum);
return maximum;
}
private:
WgcHelper& operator=(const WgcHelper& helper);
};
}
void cv::SpinImageModel::match(const SpinImageModel& scene, std::vector< std::vector<Vec2i> >& result)
{
if (mesh.vtx.empty())
throw Mesh3D::EmptyMeshException();
result.clear();
SpinImageModel& model = *this;
const float infinity = std::numeric_limits<float>::infinity();
const float float_max = std::numeric_limits<float>::max();
/* estimate gamma */
if (model.gamma == 0.f)
{
if (model.mesh.resolution == -1.f)
model.mesh.estimateResolution();
model.gamma = 4 * model.mesh.resolution;
}
/* estimate lambda */
if (model.lambda == 0.f)
{
std::vector<int> nonzero(model.spinImages.rows);
for(int i = 0; i < model.spinImages.rows; ++i)
nonzero[i] = countNonZero(model.spinImages.row(i));
sort(nonzero, std::less<int>());
model.lambda = static_cast<float>( nonzero[ nonzero.size()/2 ] ) / 2;
}
TickMeter corr_timer;
corr_timer.start();
std::vector<Match> allMatches;
for(int i = 0; i < scene.spinImages.rows; ++i)
{
std::vector<int> indeces;
std::vector<float> coeffs;
matchSpinToModel(scene.spinImages.row(i), indeces, coeffs);
for(size_t t = 0; t < indeces.size(); ++t)
allMatches.push_back(Match(i, indeces[t], coeffs[t]));
if (out) if (i % 100 == 0) *out << "Comparing scene spinimage " << i << " of " << scene.spinImages.rows << std::endl;
}
corr_timer.stop();
if (out) *out << "Spin correlation time = " << corr_timer << std::endl;
if (out) *out << "Matches number = " << allMatches.size() << std::endl;
if(allMatches.empty())
return;
/* filtering by similarity measure */
const float fraction = 0.5f;
float maxMeasure = max_element(allMatches.begin(), allMatches.end(), std::less<float>())->measure;
allMatches.erase(
remove_if(allMatches.begin(), allMatches.end(), bind2nd(std::less<float>(), maxMeasure * fraction)),
allMatches.end());
if (out) *out << "Matches number [filtered by similarity measure] = " << allMatches.size() << std::endl;
int matchesSize = (int)allMatches.size();
if(matchesSize == 0)
return;
/* filtering by geometric consistency */
for(int i = 0; i < matchesSize; ++i)
{
int consistNum = 1;
float gc = float_max;
for(int j = 0; j < matchesSize; ++j)
if (i != j)
{
const Match& mi = allMatches[i];
const Match& mj = allMatches[j];
if (mi.sceneInd == mj.sceneInd || mi.modelInd == mj.modelInd)
gc = float_max;
else
{
const Point3f& pointSceneI = scene.getSpinVertex(mi.sceneInd);
const Point3f& normalSceneI = scene.getSpinNormal(mi.sceneInd);
const Point3f& pointModelI = model.getSpinVertex(mi.modelInd);
const Point3f& normalModelI = model.getSpinNormal(mi.modelInd);
const Point3f& pointSceneJ = scene.getSpinVertex(mj.sceneInd);
const Point3f& normalSceneJ = scene.getSpinNormal(mj.sceneInd);
const Point3f& pointModelJ = model.getSpinVertex(mj.modelInd);
const Point3f& normalModelJ = model.getSpinNormal(mj.modelInd);
gc = geometricConsistency(pointSceneI, normalSceneI, pointModelI, normalModelI,
pointSceneJ, normalSceneJ, pointModelJ, normalModelJ);
}
if (gc < model.T_GeometriccConsistency)
++consistNum;
}
if (consistNum < matchesSize / 4) /* failed consistensy test */
allMatches[i].measure = infinity;
}
allMatches.erase(
std::remove_if(allMatches.begin(), allMatches.end(), std::bind2nd(std::equal_to<float>(), infinity)),
allMatches.end());
if (out) *out << "Matches number [filtered by geometric consistency] = " << allMatches.size() << std::endl;
matchesSize = (int)allMatches.size();
if(matchesSize == 0)
return;
if (out) *out << "grouping ..." << std::endl;
Mat groupingMat((int)matchesSize, (int)matchesSize, CV_32F);
groupingMat = Scalar(0);
/* grouping */
for(int j = 0; j < matchesSize; ++j)
for(int i = j + 1; i < matchesSize; ++i)
{
const Match& mi = allMatches[i];
const Match& mj = allMatches[j];
if (mi.sceneInd == mj.sceneInd || mi.modelInd == mj.modelInd)
{
groupingMat.ptr<float>(i)[j] = float_max;
groupingMat.ptr<float>(j)[i] = float_max;
continue;
}
const Point3f& pointSceneI = scene.getSpinVertex(mi.sceneInd);
const Point3f& normalSceneI = scene.getSpinNormal(mi.sceneInd);
const Point3f& pointModelI = model.getSpinVertex(mi.modelInd);
const Point3f& normalModelI = model.getSpinNormal(mi.modelInd);
const Point3f& pointSceneJ = scene.getSpinVertex(mj.sceneInd);
const Point3f& normalSceneJ = scene.getSpinNormal(mj.sceneInd);
const Point3f& pointModelJ = model.getSpinVertex(mj.modelInd);
const Point3f& normalModelJ = model.getSpinNormal(mj.modelInd);
float wgc = groupingCreteria(pointSceneI, normalSceneI, pointModelI, normalModelI,
pointSceneJ, normalSceneJ, pointModelJ, normalModelJ,
model.gamma);
groupingMat.ptr<float>(i)[j] = wgc;
groupingMat.ptr<float>(j)[i] = wgc;
}
group_t allMatchesInds;
for(int i = 0; i < matchesSize; ++i)
allMatchesInds.insert(i);
std::vector<float> buf(matchesSize);
float *buf_beg = &buf[0];
std::vector<group_t> groups;
for(int g = 0; g < matchesSize; ++g)
{
if (out) if (g % 100 == 0) *out << "G = " << g << std::endl;
group_t left = allMatchesInds;
group_t group;
left.erase(g);
group.insert(g);
for(;;)
{
size_t left_size = left.size();
if (left_size == 0)
break;
std::transform(left.begin(), left.end(), buf_beg, WgcHelper(group, groupingMat));
size_t minInd = std::min_element(buf_beg, buf_beg + left_size) - buf_beg;
if (buf[minInd] < model.T_GroupingCorespondances) /* can add corespondance to group */
{
iter pos = left.begin();
advance(pos, minInd);
group.insert(*pos);
left.erase(pos);
}
else
break;
}
if (group.size() >= 4)
groups.push_back(group);
}
/* converting the data to final result */
for(size_t i = 0; i < groups.size(); ++i)
{
const group_t& group = groups[i];
std::vector< Vec2i > outgrp;
for(citer pos = group.begin(); pos != group.end(); ++pos)
{
const Match& m = allMatches[*pos];
outgrp.push_back(Vec2i(subset[m.modelInd], scene.subset[m.sceneInd]));
}
result.push_back(outgrp);
}
}
cv::TickMeter::TickMeter() { reset(); }
int64 cv::TickMeter::getTimeTicks() const { return sumTime; }
double cv::TickMeter::getTimeMicro() const { return (double)getTimeTicks()/cvGetTickFrequency(); }
double cv::TickMeter::getTimeMilli() const { return getTimeMicro()*1e-3; }
double cv::TickMeter::getTimeSec() const { return getTimeMilli()*1e-3; }
int64 cv::TickMeter::getCounter() const { return counter; }
void cv::TickMeter::reset() {startTime = 0; sumTime = 0; counter = 0; }
void cv::TickMeter::start(){ startTime = cvGetTickCount(); }
void cv::TickMeter::stop()
{
int64 time = cvGetTickCount();
if ( startTime == 0 )
return;
++counter;
sumTime += ( time - startTime );
startTime = 0;
}
std::ostream& cv::operator<<(std::ostream& out, const TickMeter& tm){ return out << tm.getTimeSec() << "sec"; }