--- /dev/null
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+// By downloading, copying, installing or using the software you agree to this license.
+// If you do not agree to this license, do not download, install,
+// copy or use the software.
+//
+//
+// License Agreement
+// For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+// * Redistribution's of source code must retain the above copyright notice,
+// this list of conditions and the following disclaimer.
+//
+// * Redistribution's in binary form must reproduce the above copyright notice,
+// this list of conditions and the following disclaimer in the documentation
+// and/or other materials provided with the distribution.
+//
+// * The name of the copyright holders may not be used to endorse or promote products
+// derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#include "_cvaux.h"
+#include <algorithm>
+#include <cmath>
+#include <limits>
+#include <set>
+#include <fstream>
+
+using namespace cv;
+using namespace std;
+
+/********************************* local utility *********************************/
+
+namespace cv
+{
+ using std::log;
+ using std::max;
+ using std::min;
+ using std::sqrt;
+}
+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> void iota(FwIt first, FwIt last, T value) { while(first != last) *first++ = value++; }
+
+void computeNormals( const Octree& Octree, const vector<Point3f>& centers, vector<Point3f>& normals,
+ 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;
+ }
+
+ 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 vector<Point3f>& points, const vector<Point3f>& normals,
+ 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;
+
+ vector< vector<Point3f> > pointsInSpherePool(nthreads);
+ for(i = 0; i < nthreads; i++)
+ pointsInSpherePool[i].reserve(2048);
+
+ float halfSuppport = support / 2;
+ float searchRad = support * sqrt(5.f) / 2; // 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();
+ 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);
+#if CV_SSE2
+ __m128 rotmatSSE[3];
+ convertTransformMatrix(rotmat, (float*)rotmatSSE);
+#endif
+ 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)
+ {
+ __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 = 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 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)
+{
+ const size_t neighbors = 3;
+ const size_t minReasonable = 10;
+
+ size_t tryNum = static_cast<size_t>(tryRatio * vtx.size());
+ tryNum = min(max(tryNum, minReasonable), vtx.size());
+
+ CvMat desc = cvMat(vtx.size(), 3, CV_32F, &vtx[0]);
+ CvFeatureTree* tr = cvCreateKDTree(&desc);
+
+ vector<double> dist(tryNum * neighbors);
+ vector<int> inds(tryNum * neighbors);
+ vector<Point3f> query;
+
+ RNG& rng = theRNG();
+ for(size_t i = 0; i < tryNum; ++i)
+ query.push_back(vtx[rng.next() % vtx.size()]);
+
+ CvMat cvinds = cvMat( tryNum, neighbors, CV_32S, &inds[0] );
+ CvMat cvdist = cvMat( tryNum, neighbors, CV_64F, &dist[0] );
+ CvMat cvquery = cvMat( tryNum, 3, CV_32F, &query[0] );
+ cvFindFeatures(tr, &cvquery, &cvinds, &cvdist, neighbors, 50);
+ cvReleaseFeatureTree(tr);
+
+ const int invalid_dist = -2;
+ for(size_t 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, less<double>());
+
+ return resolution = (float)dist[ dist.size() / 2 ];
+}
+
+void cv::Mesh3D::computeNormals(float normalRadius, int minNeighbors)
+{
+ buildOctree();
+ vector<uchar> mask;
+ ::computeNormals(octree, vtx, normals, mask, normalRadius, minNeighbors);
+}
+
+void cv::Mesh3D::computeNormals(const vector<int>& subset, float normalRadius, int minNeighbors)
+{
+ buildOctree();
+ 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 String& file, const vector<Scalar>& colors) const
+{
+ ofstream ofs(file.c_str());
+
+ ofs << "#VRML V2.0 utf8" << endl;
+ ofs << "Shape" << std::endl << "{" << endl;
+ ofs << "geometry PointSet" << endl << "{" << endl;
+ ofs << "coord Coordinate" << endl << "{" << endl;
+ ofs << "point[" << endl;
+
+ for(size_t i = 0; i < vtx.size(); ++i)
+ ofs << vtx[i].x << " " << vtx[i].y << " " << vtx[i].z << endl;
+
+ ofs << "]" << endl; //point[
+ ofs << "}" << endl; //Coordinate{
+
+ if (vtx.size() == colors.size())
+ {
+ ofs << "color Color" << endl << "{" << endl;
+ ofs << "color[" << endl;
+
+ for(size_t i = 0; i < colors.size(); ++i)
+ ofs << (float)colors[i][2] << " " << (float)colors[i][1] << " " << (float)colors[i][0] << endl;
+
+ ofs << "]" << endl; //color[
+ ofs << "}" << endl; //color Color{
+ }
+
+ ofs << "}" << endl; //PointSet{
+ ofs << "}" << 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) / 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 = 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) / sqrt(n.x * n.x + n.y * n.y + n.z * n.z);
+ float alpha = 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)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 - 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 - exp( -(n_Sm1_to_m2 + n_Ss1_to_s2) * gamma05_inv ) );
+
+ return (float)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(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
+{
+ size_t spinNum = getSpinCount();
+ size_t num = min(spinNum, xCount * yCount);
+
+ if (num == 0)
+ return Mat();
+
+ RNG& rng = theRNG();
+
+ vector<Mat> spins;
+ for(size_t i = 0; i < num; ++i)
+ spins.push_back(getSpinImage( rng.next() % spinNum ).reshape(1, imageWidth));
+
+ if (separateScale)
+ for(size_t 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(size_t i = 0; i < num; ++i)
+ {
+ double m;
+ minMaxLoc(spins[i], 0, &m);
+ totalMax = max(m, totalMax);
+ }
+
+ for(size_t 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(yCount * sz + (yCount - 1), xCount * sz + (xCount - 1), CV_8UC3);
+ result = colors[(static_cast<int64>(cvGetTickCount()/cvGetTickFrequency())/1000) % colors_mum];
+
+ size_t pos = 0;
+ for(size_t y = 0; y < yCount; ++y)
+ for(size_t x = 0; x < 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 = min(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();
+
+ 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() % left.size();
+ subset[i] = left[pos];
+
+ left[pos] = left.back();
+ left.resize(left.size() - 1);
+ }
+ sort(subset, less<int>());
+ }
+}
+
+void cv::SpinImageModel::setSubset(const vector<int>& ss)
+{
+ subset = ss;
+}
+
+void cv::SpinImageModel::repackSpinImages(const vector<uchar>& mask, Mat& spinImages, bool reAlloc) const
+{
+ if (reAlloc)
+ {
+ size_t spinCount = mask.size() - count(mask.begin(), mask.end(), (uchar)0);
+ Mat newImgs(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(t).copyTo(row);
+ }
+ spinImages = newImgs;
+ }
+ else
+ {
+ int last = (int)mask.size();
+
+ int dest = 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);
+
+ 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( remove(subset.begin(), subset.end(), -1) - subset.begin() );
+
+ vector<Point3f> vtx;
+ 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]);
+ }
+
+ 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( remove(subset.begin(), subset.end(), (int)i) - subset.begin() );
+}
+
+void cv::SpinImageModel::matchSpinToModel(const Mat& spin, vector<int>& indeces, vector<float>& corrCoeffs, bool useExtremeOutliers) const
+{
+ const SpinImageModel& model = *this;
+
+ indeces.clear();
+ corrCoeffs.clear();
+
+ vector<float> corrs(model.spinImages.rows);
+ vector<uchar> masks(model.spinImages.rows);
+ 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, 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(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 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>(corespInd);
+ float maximum = numeric_limits<float>::min();
+
+ for(citer pos = group.begin(); pos != group.end(); ++pos)
+ maximum = max(wgcLine[*pos], maximum);
+
+ return maximum;
+ }
+private:
+ WgcHelper& operator=(const WgcHelper& helper);
+};
+
+}
+
+ void cv::SpinImageModel::match(const SpinImageModel& scene, vector< vector<Vec2i> >& result)
+{
+ if (mesh.vtx.empty())
+ throw Mesh3D::EmptyMeshException();
+
+ result.clear();
+
+ SpinImageModel& model = *this;
+ const float infinity = numeric_limits<float>::infinity();
+ const float float_max = 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)
+ {
+ vector<int> nonzero(model.spinImages.rows);
+ for(int i = 0; i < model.spinImages.rows; ++i)
+ nonzero[i] = countNonZero(model.spinImages.row(i));
+ sort(nonzero, less<int>());
+ model.lambda = static_cast<float>( nonzero[ nonzero.size()/2 ] ) / 2;
+ }
+
+ TickMeter corr_timer;
+ corr_timer.start();
+ vector<Match> allMatches;
+ for(int i = 0; i < scene.spinImages.rows; ++i)
+ {
+ vector<int> indeces;
+ 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 << endl;
+ }
+ corr_timer.stop();
+ if (out) *out << "Spin correlation time = " << corr_timer << endl;
+ if (out) *out << "Matches number = " << allMatches.size() << endl;
+
+ if(allMatches.empty())
+ return;
+
+ /* filtering by similarity measure */
+ const float fraction = 0.5f;
+ float maxMeasure = max_element(allMatches.begin(), allMatches.end(), less<float>())->measure;
+ allMatches.erase(
+ remove_if(allMatches.begin(), allMatches.end(), bind2nd(less<float>(), maxMeasure * fraction)),
+ allMatches.end());
+ if (out) *out << "Matches number [filtered by similarity measure] = " << allMatches.size() << endl;
+
+ size_t matchesSize = allMatches.size();
+ if(matchesSize == 0)
+ return;
+
+ /* filtering by geometric consistency */
+ for(size_t i = 0; i < matchesSize; ++i)
+ {
+ size_t consistNum = 1;
+ float gc = float_max;
+
+ for(size_t 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(
+ remove_if(allMatches.begin(), allMatches.end(), bind2nd(equal_to<float>(), infinity)),
+ allMatches.end());
+ if (out) *out << "Matches number [filtered by geometric consistency] = " << allMatches.size() << endl;
+
+
+ matchesSize = allMatches.size();
+ if(matchesSize == 0)
+ return;
+
+ if (out) *out << "grouping ..." << endl;
+
+ Mat groupingMat(matchesSize, matchesSize, CV_32F);
+ groupingMat = Scalar(0);
+
+ /* grouping */
+ for(size_t j = 0; j < matchesSize; ++j)
+ for(size_t 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(size_t i = 0; i < matchesSize; ++i)
+ allMatchesInds.insert(i);
+
+ vector<float> buf(matchesSize);
+ float *buf_beg = &buf[0];
+ vector<group_t> groups;
+
+ for(size_t g = 0; g < matchesSize; ++g)
+ {
+ if (out) if (g % 100 == 0) *out << "G = " << g << 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 = 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];
+
+ 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"; }
projects / opencv / blobdiff