36 #include <visp3/core/vpCPUFeatures.h>
37 #include <visp3/mbt/vpMbtFaceDepthNormal.h>
38 #include <visp3/mbt/vpMbtTukeyEstimator.h>
41 #include <pcl/common/centroid.h>
42 #include <pcl/filters/extract_indices.h>
43 #include <pcl/segmentation/sac_segmentation.h>
46 #if defined __SSE2__ || defined _M_X64 || (defined _M_IX86_FP && _M_IX86_FP >= 2)
47 #include <emmintrin.h>
48 #define VISP_HAVE_SSE2 1
51 #define USE_SSE_CODE 1
52 #if VISP_HAVE_SSE2 && USE_SSE_CODE
59 : m_cam(), m_clippingFlag(
vpPolygon3D::NO_CLIPPING), m_distFarClip(100), m_distNearClip(0.001), m_hiddenFace(NULL),
60 m_planeObject(), m_polygon(NULL), m_useScanLine(false), m_faceActivated(false),
61 m_faceCentroidMethod(GEOMETRIC_CENTROID), m_faceDesiredCentroid(), m_faceDesiredNormal(),
62 m_featureEstimationMethod(ROBUST_FEATURE_ESTIMATION), m_isTrackedDepthNormalFace(true), m_isVisible(false),
63 m_listOfFaceLines(), m_planeCamera(),
64 m_pclPlaneEstimationMethod(2),
65 m_pclPlaneEstimationRansacMaxIter(200), m_pclPlaneEstimationRansacThreshold(0.001), m_polygonLines()
91 vpUniRand &rand_gen,
int polygon, std::string name)
94 PolygonLine polygon_line;
97 polygon_line.m_poly.setNbPoint(2);
98 polygon_line.m_poly.addPoint(0, P1);
99 polygon_line.m_poly.addPoint(1, P2);
105 polygon_line.m_p1 = &polygon_line.m_poly.p[0];
106 polygon_line.m_p2 = &polygon_line.m_poly.p[1];
111 bool already_here =
false;
153 const pcl::PointCloud<pcl::PointXYZ>::ConstPtr &point_cloud,
154 vpColVector &desired_features,
unsigned int stepX,
unsigned int stepY
155 #
if DEBUG_DISPLAY_DEPTH_NORMAL
158 std::vector<std::vector<vpImagePoint> > &roiPts_vec
165 if (width == 0 || height == 0)
168 std::vector<vpImagePoint> roiPts;
172 #
if DEBUG_DISPLAY_DEPTH_NORMAL
178 if (roiPts.size() <= 2) {
180 std::cerr <<
"Error: roiPts.size() <= 2 in computeDesiredFeatures" << std::endl;
188 unsigned int top = (
unsigned int)std::max(0.0, bb.
getTop());
189 unsigned int bottom = (
unsigned int)std::min((
double)height, std::max(0.0, bb.
getBottom()));
190 unsigned int left = (
unsigned int)std::max(0.0, bb.
getLeft());
191 unsigned int right = (
unsigned int)std::min((
double)width, std::max(0.0, bb.
getRight()));
199 pcl::PointCloud<pcl::PointXYZ>::Ptr point_cloud_face(
new pcl::PointCloud<pcl::PointXYZ>);
200 std::vector<double> point_cloud_face_vec, point_cloud_face_custom;
216 double prev_x, prev_y, prev_z;
219 double x = 0.0, y = 0.0;
220 for (
unsigned int i = top; i < bottom; i += stepY) {
221 for (
unsigned int j = left; j < right; j += stepX) {
222 if (
vpMeTracker::inMask(mask, i, j) && pcl::isFinite((*point_cloud)(j, i)) && (*point_cloud)(j, i).z > 0 &&
223 (
m_useScanLine ? (i < m_hiddenFace->getMbScanLineRenderer().getPrimitiveIDs().getHeight() &&
224 j < m_hiddenFace->getMbScanLineRenderer().getPrimitiveIDs().getWidth() &&
229 point_cloud_face->push_back((*point_cloud)(j, i));
232 point_cloud_face_vec.push_back((*point_cloud)(j, i).x);
233 point_cloud_face_vec.push_back((*point_cloud)(j, i).y);
234 point_cloud_face_vec.push_back((*point_cloud)(j, i).z);
246 prev_z = (*point_cloud)(j, i).z;
249 point_cloud_face_custom.push_back(prev_x);
250 point_cloud_face_custom.push_back(x);
252 point_cloud_face_custom.push_back(prev_y);
253 point_cloud_face_custom.push_back(y);
255 point_cloud_face_custom.push_back(prev_z);
256 point_cloud_face_custom.push_back((*point_cloud)(j, i).z);
260 point_cloud_face_custom.push_back(x);
261 point_cloud_face_custom.push_back(y);
262 point_cloud_face_custom.push_back((*point_cloud)(j, i).z);
267 #if DEBUG_DISPLAY_DEPTH_NORMAL
268 debugImage[i][j] = 255;
275 if (checkSSE2 && push) {
276 point_cloud_face_custom.push_back(prev_x);
277 point_cloud_face_custom.push_back(prev_y);
278 point_cloud_face_custom.push_back(prev_z);
282 if (point_cloud_face->empty() && point_cloud_face_custom.empty() && point_cloud_face_vec.empty()) {
297 desired_normal, centroid_point);
311 unsigned int height,
const std::vector<vpColVector> &point_cloud,
312 vpColVector &desired_features,
unsigned int stepX,
unsigned int stepY
313 #
if DEBUG_DISPLAY_DEPTH_NORMAL
316 std::vector<std::vector<vpImagePoint> > &roiPts_vec
323 if (width == 0 || height == 0)
326 std::vector<vpImagePoint> roiPts;
330 #
if DEBUG_DISPLAY_DEPTH_NORMAL
336 if (roiPts.size() <= 2) {
338 std::cerr <<
"Error: roiPts.size() <= 2 in computeDesiredFeatures" << std::endl;
346 unsigned int top = (
unsigned int)std::max(0.0, bb.
getTop());
347 unsigned int bottom = (
unsigned int)std::min((
double)height, std::max(0.0, bb.
getBottom()));
348 unsigned int left = (
unsigned int)std::max(0.0, bb.
getLeft());
349 unsigned int right = (
unsigned int)std::min((
double)width, std::max(0.0, bb.
getRight()));
357 std::vector<double> point_cloud_face, point_cloud_face_custom;
369 double prev_x, prev_y, prev_z;
372 double x = 0.0, y = 0.0;
373 for (
unsigned int i = top; i < bottom; i += stepY) {
374 for (
unsigned int j = left; j < right; j += stepX) {
376 (
m_useScanLine ? (i < m_hiddenFace->getMbScanLineRenderer().getPrimitiveIDs().getHeight() &&
377 j < m_hiddenFace->getMbScanLineRenderer().getPrimitiveIDs().getWidth() &&
381 point_cloud_face.push_back(point_cloud[i * width + j][0]);
382 point_cloud_face.push_back(point_cloud[i * width + j][1]);
383 point_cloud_face.push_back(point_cloud[i * width + j][2]);
395 prev_z = point_cloud[i * width + j][2];
398 point_cloud_face_custom.push_back(prev_x);
399 point_cloud_face_custom.push_back(x);
401 point_cloud_face_custom.push_back(prev_y);
402 point_cloud_face_custom.push_back(y);
404 point_cloud_face_custom.push_back(prev_z);
405 point_cloud_face_custom.push_back(point_cloud[i * width + j][2]);
409 point_cloud_face_custom.push_back(x);
410 point_cloud_face_custom.push_back(y);
411 point_cloud_face_custom.push_back(point_cloud[i * width + j][2]);
415 #if DEBUG_DISPLAY_DEPTH_NORMAL
416 debugImage[i][j] = 255;
423 if (checkSSE2 && push) {
424 point_cloud_face_custom.push_back(prev_x);
425 point_cloud_face_custom.push_back(prev_y);
426 point_cloud_face_custom.push_back(prev_z);
430 if (point_cloud_face.empty() && point_cloud_face_custom.empty()) {
439 pcl::PointCloud<pcl::PointXYZ>::Ptr point_cloud_face_pcl(
new pcl::PointCloud<pcl::PointXYZ>);
440 point_cloud_face_pcl->reserve(point_cloud_face.size() / 3);
442 for (
size_t i = 0; i < point_cloud_face.size() / 3; i++) {
443 point_cloud_face_pcl->push_back(
444 pcl::PointXYZ(point_cloud_face[3 * i], point_cloud_face[3 * i + 1], point_cloud_face[3 * i + 2]));
454 desired_normal, centroid_point);
473 pcl::ModelCoefficients::Ptr coefficients(
new pcl::ModelCoefficients);
474 pcl::PointIndices::Ptr inliers(
new pcl::PointIndices);
476 pcl::SACSegmentation<pcl::PointXYZ> seg;
478 seg.setOptimizeCoefficients(
true);
480 seg.setModelType(pcl::SACMODEL_PLANE);
485 seg.setInputCloud(point_cloud_face);
486 seg.segment(*inliers, *coefficients);
488 pcl::PointCloud<pcl::PointXYZ>::Ptr point_cloud_face_extracted(
new pcl::PointCloud<pcl::PointXYZ>);
490 pcl::ExtractIndices<pcl::PointXYZ> extract;
493 extract.setInputCloud(point_cloud_face);
494 extract.setIndices(inliers);
495 extract.setNegative(
false);
496 extract.filter(*point_cloud_face_extracted);
498 #if PCL_VERSION_COMPARE(>=, 1, 7, 2)
499 pcl::PointXYZ centroid_point_pcl;
500 if (pcl::computeCentroid(*point_cloud_face_extracted, centroid_point_pcl)) {
501 pcl::PointXYZ face_normal;
503 centroid_point_pcl, face_normal);
505 desired_features.
resize(3,
false);
506 desired_features[0] = -coefficients->values[0] / coefficients->values[3];
507 desired_features[1] = -coefficients->values[1] / coefficients->values[3];
508 desired_features[2] = -coefficients->values[2] / coefficients->values[3];
510 desired_normal[0] = face_normal.x;
511 desired_normal[1] = face_normal.y;
512 desired_normal[2] = face_normal.z;
514 centroid_point[0] = centroid_point_pcl.x;
515 centroid_point[1] = centroid_point_pcl.y;
516 centroid_point[2] = centroid_point_pcl.z;
518 std::cerr <<
"Cannot compute centroid!" << std::endl;
522 std::cerr <<
"Cannot compute centroid using PCL " << PCL_VERSION_PRETTY <<
"!" << std::endl;
525 }
catch (
const pcl::PCLException &e) {
526 std::cerr <<
"Catch a PCL exception: " << e.what() << std::endl;
535 const std::vector<double> &point_cloud_face,
541 std::vector<double> weights;
546 for (
size_t i = 0; i < point_cloud_face.size() / 3; i++) {
547 centroid_point[0] += weights[i] * point_cloud_face[3 * i];
548 centroid_point[1] += weights[i] * point_cloud_face[3 * i + 1];
549 centroid_point[2] += weights[i] * point_cloud_face[3 * i + 2];
554 centroid_point[0] /= den;
555 centroid_point[1] /= den;
556 centroid_point[2] /= den;
569 desired_features.
resize(3,
false);
570 desired_features[0] = -plane_equation_SVD[0] / plane_equation_SVD[3];
571 desired_features[1] = -plane_equation_SVD[1] / plane_equation_SVD[3];
572 desired_features[2] = -plane_equation_SVD[2] / plane_equation_SVD[3];
584 centroid_cam[0] = centroid_point[0];
585 centroid_cam[1] = centroid_point[1];
586 centroid_cam[2] = centroid_point[2];
594 face_normal_cam[0] = desired_normal[0];
595 face_normal_cam[1] = desired_normal[1];
596 face_normal_cam[2] = desired_normal[2];
597 face_normal_cam[3] = 1;
605 if (points_.empty()) {
609 if (points_.size() < 2) {
610 centroid = points_[0];
614 std::vector<vpPoint> points = points_;
615 points.push_back(points_.front());
617 double A1 = 0.0, A2 = 0.0, c_x1 = 0.0, c_x2 = 0.0, c_y = 0.0, c_z = 0.0;
619 for (
size_t i = 0; i < points.size() - 1; i++) {
621 c_x1 += (points[i].get_X() + points[i + 1].get_X()) *
622 (points[i].get_X() * points[i + 1].get_Y() - points[i + 1].get_X() * points[i].get_Y());
623 c_y += (points[i].get_Y() + points[i + 1].get_Y()) *
624 (points[i].get_X() * points[i + 1].get_Y() - points[i + 1].get_X() * points[i].get_Y());
625 A1 += points[i].
get_X() * points[i + 1].get_Y() - points[i + 1].get_X() * points[i].get_Y();
628 c_x2 += (points[i].get_X() + points[i + 1].get_X()) *
629 (points[i].get_X() * points[i + 1].get_Z() - points[i + 1].get_X() * points[i].get_Z());
630 c_z += (points[i].get_Z() + points[i + 1].get_Z()) *
631 (points[i].get_X() * points[i + 1].get_Z() - points[i + 1].get_X() * points[i].get_Z());
632 A2 += points[i].get_X() * points[i + 1].get_Z() - points[i + 1].get_X() * points[i].get_Z();
641 centroid.
set_X(c_x1);
643 centroid.
set_X(c_x2);
653 std::vector<vpImagePoint> &roiPts
654 #
if DEBUG_DISPLAY_DEPTH_NORMAL
656 std::vector<std::vector<vpImagePoint> > &roiPts_vec
665 it->m_p1->changeFrame(cMo);
666 it->m_p2->changeFrame(cMo);
670 it->m_poly.changeFrame(cMo);
671 it->m_poly.computePolygonClipped(
m_cam);
673 if (it->m_poly.polyClipped.size() == 2 &&
681 std::vector<std::pair<vpPoint, vpPoint> > linesLst;
685 for (
unsigned int i = 0; i < linesLst.size(); i++) {
686 linesLst[i].first.project();
687 linesLst[i].second.project();
695 roiPts.push_back(ip1);
696 roiPts.push_back(ip2);
698 #if DEBUG_DISPLAY_DEPTH_NORMAL
699 std::vector<vpImagePoint> roiPts_;
700 roiPts_.push_back(ip1);
701 roiPts_.push_back(ip2);
702 roiPts_vec.push_back(roiPts_);
711 #if DEBUG_DISPLAY_DEPTH_NORMAL
712 roiPts_vec.push_back(roiPts);
726 bool isvisible =
false;
730 int index = *itindex;
763 std::vector<vpImagePoint> roiPts;
766 std::vector<vpPoint> polyPts;
774 e4[0] = -centroid.
get_X();
775 e4[1] = -centroid.
get_Y();
776 e4[2] = -centroid.
get_Z();
779 double centroid_x = 0.0;
780 double centroid_y = 0.0;
781 double centroid_z = 0.0;
783 for (
size_t i = 0; i < polyPts.size(); i++) {
784 centroid_x += polyPts[i].get_X();
785 centroid_y += polyPts[i].get_Y();
786 centroid_z += polyPts[i].get_Z();
789 centroid_x /= polyPts.
size();
790 centroid_y /= polyPts.size();
791 centroid_z /= polyPts.size();
798 centroid.
set_X(centroid_x);
799 centroid.
set_Y(centroid_y);
800 centroid.
set_Z(centroid_z);
803 correct_normal.
resize(3,
false);
805 if (angle < M_PI_2) {
806 correct_normal = faceNormal;
808 correct_normal[0] = -faceNormal[0];
809 correct_normal[1] = -faceNormal[1];
810 correct_normal[2] = -faceNormal[2];
816 pcl::PointXYZ &face_normal)
825 e4[0] = -centroid_point.x;
826 e4[1] = -centroid_point.y;
827 e4[2] = -centroid_point.z;
831 if (angle < M_PI_2) {
832 face_normal = pcl::PointXYZ(faceNormal[0], faceNormal[1], faceNormal[2]);
834 face_normal = pcl::PointXYZ(-faceNormal[0], -faceNormal[1], -faceNormal[2]);
842 face_normal.
resize(3,
false);
852 if (angle >= M_PI_2) {
853 face_normal[0] = -face_normal[0];
854 face_normal[1] = -face_normal[1];
855 face_normal[2] = -face_normal[2];
861 L.resize(3, 6,
false,
false);
874 features.
resize(3,
false);
875 features[0] = -ux / D;
876 features[1] = -uy / D;
877 features[2] = -uz / D;
880 L[0][0] = ux * ux / D2;
881 L[0][1] = ux * uy / D2;
882 L[0][2] = ux * uz / D2;
888 L[1][0] = ux * uy / D2;
889 L[1][1] = uy * uy / D2;
890 L[1][2] = uy * uz / D2;
896 L[2][0] = ux * uz / D2;
897 L[2][1] = uy * uz / D2;
898 L[2][2] = uz * uz / D2;
906 bool displayFullModel)
908 std::vector<std::vector<double> > models =
911 for (
size_t i = 0; i < models.size(); i++) {
920 bool displayFullModel)
922 std::vector<std::vector<double> > models =
925 for (
size_t i = 0; i < models.size(); i++) {
976 pt_extremity.
set_X(pt_centroid.
get_X() + correct_normal[0] * scale);
977 pt_extremity.
set_Y(pt_centroid.
get_Y() + correct_normal[1] * scale);
978 pt_extremity.
set_Z(pt_centroid.
get_Z() + correct_normal[2] * scale);
1031 pt_extremity.
set_X(pt_centroid.
get_X() + correct_normal[0] * scale);
1032 pt_extremity.
set_Y(pt_centroid.
get_Y() + correct_normal[1] * scale);
1033 pt_extremity.
set_Z(pt_centroid.
get_Z() + correct_normal[2] * scale);
1045 vpMbtTukeyEstimator<double> tukey_robust;
1046 std::vector<double> residues(point_cloud_face.size() / 3);
1048 w.resize(point_cloud_face.size() / 3, 1.0);
1050 unsigned int max_iter = 30, iter = 0;
1051 double error = 0.0, prev_error = -1.0;
1052 double A = 0.0, B = 0.0, C = 0.0;
1054 Mat33<double> ATA_3x3;
1063 while (std::fabs(error - prev_error) > 1e-6 && (iter < max_iter)) {
1080 if (point_cloud_face.size() / 3 >= 2) {
1081 const double *ptr_point_cloud = &point_cloud_face[0];
1082 const __m128d vA = _mm_set1_pd(A);
1083 const __m128d vB = _mm_set1_pd(B);
1084 const __m128d vC = _mm_set1_pd(C);
1085 const __m128d vones = _mm_set1_pd(1.0);
1087 double *ptr_residues = &residues[0];
1089 for (; cpt <= point_cloud_face.size() - 6; cpt += 6, ptr_point_cloud += 6, ptr_residues += 2) {
1090 const __m128d vxi = _mm_loadu_pd(ptr_point_cloud);
1091 const __m128d vyi = _mm_loadu_pd(ptr_point_cloud + 2);
1092 const __m128d vZi = _mm_loadu_pd(ptr_point_cloud + 4);
1093 const __m128d vinvZi = _mm_div_pd(vones, vZi);
1096 _mm_add_pd(_mm_add_pd(_mm_mul_pd(vA, vxi), _mm_mul_pd(vB, vyi)), _mm_sub_pd(vC, vinvZi));
1097 _mm_storeu_pd(ptr_residues, tmp);
1101 for (; cpt < point_cloud_face.size(); cpt += 3) {
1102 double xi = point_cloud_face[cpt];
1103 double yi = point_cloud_face[cpt + 1];
1104 double Zi = point_cloud_face[cpt + 2];
1106 residues[cpt / 3] = (A * xi + B * yi + C - 1 / Zi);
1110 tukey_robust.MEstimator(residues, w, 1e-2);
1112 __m128d vsum_wi2_xi2 = _mm_setzero_pd();
1113 __m128d vsum_wi2_yi2 = _mm_setzero_pd();
1114 __m128d vsum_wi2 = _mm_setzero_pd();
1115 __m128d vsum_wi2_xi_yi = _mm_setzero_pd();
1116 __m128d vsum_wi2_xi = _mm_setzero_pd();
1117 __m128d vsum_wi2_yi = _mm_setzero_pd();
1119 __m128d vsum_wi2_xi_Zi = _mm_setzero_pd();
1120 __m128d vsum_wi2_yi_Zi = _mm_setzero_pd();
1121 __m128d vsum_wi2_Zi = _mm_setzero_pd();
1125 if (point_cloud_face.size() / 3 >= 2) {
1126 const double *ptr_point_cloud = &point_cloud_face[0];
1127 double *ptr_w = &w[0];
1129 const __m128d vones = _mm_set1_pd(1.0);
1131 for (; cpt <= point_cloud_face.size() - 6; cpt += 6, ptr_point_cloud += 6, ptr_w += 2) {
1132 const __m128d vwi2 = _mm_mul_pd(_mm_loadu_pd(ptr_w), _mm_loadu_pd(ptr_w));
1134 const __m128d vxi = _mm_loadu_pd(ptr_point_cloud);
1135 const __m128d vyi = _mm_loadu_pd(ptr_point_cloud + 2);
1136 const __m128d vZi = _mm_loadu_pd(ptr_point_cloud + 4);
1137 const __m128d vinvZi = _mm_div_pd(vones, vZi);
1139 vsum_wi2_xi2 = _mm_add_pd(vsum_wi2_xi2, _mm_mul_pd(vwi2, _mm_mul_pd(vxi, vxi)));
1140 vsum_wi2_yi2 = _mm_add_pd(vsum_wi2_yi2, _mm_mul_pd(vwi2, _mm_mul_pd(vyi, vyi)));
1141 vsum_wi2 = _mm_add_pd(vsum_wi2, vwi2);
1142 vsum_wi2_xi_yi = _mm_add_pd(vsum_wi2_xi_yi, _mm_mul_pd(vwi2, _mm_mul_pd(vxi, vyi)));
1143 vsum_wi2_xi = _mm_add_pd(vsum_wi2_xi, _mm_mul_pd(vwi2, vxi));
1144 vsum_wi2_yi = _mm_add_pd(vsum_wi2_yi, _mm_mul_pd(vwi2, vyi));
1146 const __m128d vwi2_invZi = _mm_mul_pd(vwi2, vinvZi);
1147 vsum_wi2_xi_Zi = _mm_add_pd(vsum_wi2_xi_Zi, _mm_mul_pd(vxi, vwi2_invZi));
1148 vsum_wi2_yi_Zi = _mm_add_pd(vsum_wi2_yi_Zi, _mm_mul_pd(vyi, vwi2_invZi));
1149 vsum_wi2_Zi = _mm_add_pd(vsum_wi2_Zi, vwi2_invZi);
1154 _mm_storeu_pd(vtmp, vsum_wi2_xi2);
1155 double sum_wi2_xi2 = vtmp[0] + vtmp[1];
1157 _mm_storeu_pd(vtmp, vsum_wi2_yi2);
1158 double sum_wi2_yi2 = vtmp[0] + vtmp[1];
1160 _mm_storeu_pd(vtmp, vsum_wi2);
1161 double sum_wi2 = vtmp[0] + vtmp[1];
1163 _mm_storeu_pd(vtmp, vsum_wi2_xi_yi);
1164 double sum_wi2_xi_yi = vtmp[0] + vtmp[1];
1166 _mm_storeu_pd(vtmp, vsum_wi2_xi);
1167 double sum_wi2_xi = vtmp[0] + vtmp[1];
1169 _mm_storeu_pd(vtmp, vsum_wi2_yi);
1170 double sum_wi2_yi = vtmp[0] + vtmp[1];
1172 _mm_storeu_pd(vtmp, vsum_wi2_xi_Zi);
1173 double sum_wi2_xi_Zi = vtmp[0] + vtmp[1];
1175 _mm_storeu_pd(vtmp, vsum_wi2_yi_Zi);
1176 double sum_wi2_yi_Zi = vtmp[0] + vtmp[1];
1178 _mm_storeu_pd(vtmp, vsum_wi2_Zi);
1179 double sum_wi2_Zi = vtmp[0] + vtmp[1];
1181 for (; cpt < point_cloud_face.size(); cpt += 3) {
1182 double wi2 = w[cpt / 3] * w[cpt / 3];
1184 double xi = point_cloud_face[cpt];
1185 double yi = point_cloud_face[cpt + 1];
1186 double Zi = point_cloud_face[cpt + 2];
1187 double invZi = 1.0 / Zi;
1189 sum_wi2_xi2 += wi2 * xi * xi;
1190 sum_wi2_yi2 += wi2 * yi * yi;
1192 sum_wi2_xi_yi += wi2 * xi * yi;
1193 sum_wi2_xi += wi2 * xi;
1194 sum_wi2_yi += wi2 * yi;
1196 sum_wi2_xi_Zi += wi2 * xi * invZi;
1197 sum_wi2_yi_Zi += wi2 * yi * invZi;
1198 sum_wi2_Zi += wi2 * invZi;
1201 ATA_3x3[0] = sum_wi2_xi2;
1202 ATA_3x3[1] = sum_wi2_xi_yi;
1203 ATA_3x3[2] = sum_wi2_xi;
1204 ATA_3x3[3] = sum_wi2_xi_yi;
1205 ATA_3x3[4] = sum_wi2_yi2;
1206 ATA_3x3[5] = sum_wi2_yi;
1207 ATA_3x3[6] = sum_wi2_xi;
1208 ATA_3x3[7] = sum_wi2_yi;
1209 ATA_3x3[8] = sum_wi2;
1211 Mat33<double> minv = ATA_3x3.inverse();
1213 A = minv[0] * sum_wi2_xi_Zi + minv[1] * sum_wi2_yi_Zi + minv[2] * sum_wi2_Zi;
1214 B = minv[3] * sum_wi2_xi_Zi + minv[4] * sum_wi2_yi_Zi + minv[5] * sum_wi2_Zi;
1215 C = minv[6] * sum_wi2_xi_Zi + minv[7] * sum_wi2_yi_Zi + minv[8] * sum_wi2_Zi;
1223 __m128d verror = _mm_set1_pd(0.0);
1224 if (point_cloud_face.size() / 3 >= 2) {
1225 const double *ptr_point_cloud = &point_cloud_face[0];
1226 const __m128d vA = _mm_set1_pd(A);
1227 const __m128d vB = _mm_set1_pd(B);
1228 const __m128d vC = _mm_set1_pd(C);
1229 const __m128d vones = _mm_set1_pd(1.0);
1231 double *ptr_residues = &residues[0];
1233 for (; cpt <= point_cloud_face.size() - 6; cpt += 6, ptr_point_cloud += 6, ptr_residues += 2) {
1234 const __m128d vxi = _mm_loadu_pd(ptr_point_cloud);
1235 const __m128d vyi = _mm_loadu_pd(ptr_point_cloud + 2);
1236 const __m128d vZi = _mm_loadu_pd(ptr_point_cloud + 4);
1237 const __m128d vinvZi = _mm_div_pd(vones, vZi);
1239 const __m128d tmp = _mm_add_pd(_mm_add_pd(_mm_mul_pd(vA, vxi), _mm_mul_pd(vB, vyi)), _mm_sub_pd(vC, vinvZi));
1240 verror = _mm_add_pd(verror, _mm_mul_pd(tmp, tmp));
1242 _mm_storeu_pd(ptr_residues, tmp);
1246 _mm_storeu_pd(vtmp, verror);
1247 error = vtmp[0] + vtmp[1];
1249 for (
size_t idx = cpt; idx < point_cloud_face.size(); idx += 3) {
1250 double xi = point_cloud_face[idx];
1251 double yi = point_cloud_face[idx + 1];
1252 double Zi = point_cloud_face[idx + 2];
1254 error +=
vpMath::sqr(A * xi + B * yi + C - 1 / Zi);
1255 residues[idx / 3] = (A * xi + B * yi + C - 1 / Zi);
1258 error /= point_cloud_face.size() / 3;
1264 while (std::fabs(error - prev_error) > 1e-6 && (iter < max_iter)) {
1280 for (
size_t i = 0; i < point_cloud_face.size() / 3; i++) {
1281 double xi = point_cloud_face[3 * i];
1282 double yi = point_cloud_face[3 * i + 1];
1283 double Zi = point_cloud_face[3 * i + 2];
1285 residues[i] = (A * xi + B * yi + C - 1 / Zi);
1289 tukey_robust.MEstimator(residues, w, 1e-2);
1292 double sum_wi2_xi2 = 0.0, sum_wi2_yi2 = 0.0, sum_wi2 = 0.0;
1293 double sum_wi2_xi_yi = 0.0, sum_wi2_xi = 0.0, sum_wi2_yi = 0.0;
1295 double sum_wi2_xi_Zi = 0.0, sum_wi2_yi_Zi = 0.0, sum_wi2_Zi = 0.0;
1297 for (
size_t i = 0; i < point_cloud_face.size() / 3; i++) {
1298 double wi2 = w[i] * w[i];
1300 double xi = point_cloud_face[3 * i];
1301 double yi = point_cloud_face[3 * i + 1];
1302 double Zi = point_cloud_face[3 * i + 2];
1303 double invZi = 1 / Zi;
1305 sum_wi2_xi2 += wi2 * xi * xi;
1306 sum_wi2_yi2 += wi2 * yi * yi;
1308 sum_wi2_xi_yi += wi2 * xi * yi;
1309 sum_wi2_xi += wi2 * xi;
1310 sum_wi2_yi += wi2 * yi;
1312 sum_wi2_xi_Zi += wi2 * xi * invZi;
1313 sum_wi2_yi_Zi += wi2 * yi * invZi;
1314 sum_wi2_Zi += wi2 * invZi;
1317 ATA_3x3[0] = sum_wi2_xi2;
1318 ATA_3x3[1] = sum_wi2_xi_yi;
1319 ATA_3x3[2] = sum_wi2_xi;
1320 ATA_3x3[3] = sum_wi2_xi_yi;
1321 ATA_3x3[4] = sum_wi2_yi2;
1322 ATA_3x3[5] = sum_wi2_yi;
1323 ATA_3x3[6] = sum_wi2_xi;
1324 ATA_3x3[7] = sum_wi2_yi;
1325 ATA_3x3[8] = sum_wi2;
1327 Mat33<double> minv = ATA_3x3.inverse();
1329 A = minv[0] * sum_wi2_xi_Zi + minv[1] * sum_wi2_yi_Zi + minv[2] * sum_wi2_Zi;
1330 B = minv[3] * sum_wi2_xi_Zi + minv[4] * sum_wi2_yi_Zi + minv[5] * sum_wi2_Zi;
1331 C = minv[6] * sum_wi2_xi_Zi + minv[7] * sum_wi2_yi_Zi + minv[8] * sum_wi2_Zi;
1337 for (
size_t i = 0; i < point_cloud_face.size() / 3; i++) {
1338 double xi = point_cloud_face[3 * i];
1339 double yi = point_cloud_face[3 * i + 1];
1340 double Zi = point_cloud_face[3 * i + 2];
1342 error +=
vpMath::sqr(A * xi + B * yi + C - 1 / Zi);
1343 residues[i] = (A * xi + B * yi + C - 1 / Zi);
1346 error /= point_cloud_face.size() / 3;
1352 x_estimated.
resize(3,
false);
1362 unsigned int max_iter = 10;
1363 double prev_error = 1e3;
1364 double error = 1e3 - 1;
1366 std::vector<double> weights(point_cloud_face.size() / 3, 1.0);
1367 std::vector<double> residues(point_cloud_face.size() / 3);
1368 vpMatrix M((
unsigned int)(point_cloud_face.size() / 3), 3);
1369 vpMbtTukeyEstimator<double> tukey;
1372 for (
unsigned int iter = 0; iter < max_iter && std::fabs(error - prev_error) > 1e-6; iter++) {
1374 tukey.MEstimator(residues, weights, 1e-4);
1386 for (
size_t i = 0; i < point_cloud_face.size() / 3; i++) {
1387 residues[i] = std::fabs(A * point_cloud_face[3 * i] + B * point_cloud_face[3 * i + 1] +
1388 C * point_cloud_face[3 * i + 2] + D) /
1389 sqrt(A * A + B * B + C * C);
1392 tukey.MEstimator(residues, weights, 1e-4);
1393 plane_equation_estimated.
resize(4,
false);
1397 double centroid_x = 0.0, centroid_y = 0.0, centroid_z = 0.0;
1398 double total_w = 0.0;
1400 for (
size_t i = 0; i < point_cloud_face.size() / 3; i++) {
1401 centroid_x += weights[i] * point_cloud_face[3 * i];
1402 centroid_y += weights[i] * point_cloud_face[3 * i + 1];
1403 centroid_z += weights[i] * point_cloud_face[3 * i + 2];
1404 total_w += weights[i];
1407 centroid_x /= total_w;
1408 centroid_y /= total_w;
1409 centroid_z /= total_w;
1412 for (
size_t i = 0; i < point_cloud_face.size() / 3; i++) {
1413 M[(
unsigned int)i][0] = weights[i] * (point_cloud_face[3 * i] - centroid_x);
1414 M[(
unsigned int)i][1] = weights[i] * (point_cloud_face[3 * i + 1] - centroid_y);
1415 M[(
unsigned int)i][2] = weights[i] * (point_cloud_face[3 * i + 2] - centroid_z);
1424 double smallestSv = W[0];
1425 unsigned int indexSmallestSv = 0;
1426 for (
unsigned int i = 1; i < W.
size(); i++) {
1427 if (W[i] < smallestSv) {
1429 indexSmallestSv = i;
1433 normal = V.
getCol(indexSmallestSv);
1436 double A = normal[0], B = normal[1], C = normal[2];
1437 double D = -(A * centroid_x + B * centroid_y + C * centroid_z);
1440 plane_equation_estimated[0] = A;
1441 plane_equation_estimated[1] = B;
1442 plane_equation_estimated[2] = C;
1443 plane_equation_estimated[3] = D;
1448 for (
size_t i = 0; i < point_cloud_face.size() / 3; i++) {
1449 residues[i] = std::fabs(A * point_cloud_face[3 * i] + B * point_cloud_face[3 * i + 1] +
1450 C * point_cloud_face[3 * i + 2] + D) /
1451 sqrt(A * A + B * B + C * C);
1452 error += weights[i] * residues[i];
1458 tukey.MEstimator(residues, weights, 1e-4);
1461 centroid.
resize(3,
false);
1462 double total_w = 0.0;
1464 for (
size_t i = 0; i < point_cloud_face.size() / 3; i++) {
1465 centroid[0] += weights[i] * point_cloud_face[3 * i];
1466 centroid[1] += weights[i] * point_cloud_face[3 * i + 1];
1467 centroid[2] += weights[i] * point_cloud_face[3 * i + 2];
1468 total_w += weights[i];
1471 centroid[0] /= total_w;
1472 centroid[1] /= total_w;
1473 centroid[2] /= total_w;
1476 double A = normal[0], B = normal[1], C = normal[2];
1477 double D = -(A * centroid[0] + B * centroid[1] + C * centroid[2]);
1480 plane_equation_estimated[0] = A;
1481 plane_equation_estimated[1] = B;
1482 plane_equation_estimated[2] = C;
1483 plane_equation_estimated[3] = D;
1491 std::vector<std::vector<double> >
1494 std::vector<std::vector<double> > features;
1519 #if (VISP_CXX_STANDARD >= VISP_CXX_STANDARD_11)
1520 std::vector<double> params = {2,
1522 im_extremity.
get_j()};
1524 std::vector<double> params;
1525 params.push_back(2);
1526 params.push_back(im_centroid.
get_i());
1527 params.push_back(im_centroid.
get_j());
1528 params.push_back(im_extremity.
get_i());
1529 params.push_back(im_extremity.
get_j());
1531 features.push_back(params);
1549 pt_extremity.
set_X(pt_centroid.
get_X() + correct_normal[0] * scale);
1550 pt_extremity.
set_Y(pt_centroid.
get_Y() + correct_normal[1] * scale);
1551 pt_extremity.
set_Z(pt_centroid.
get_Z() + correct_normal[2] * scale);
1557 #if (VISP_CXX_STANDARD >= VISP_CXX_STANDARD_11)
1558 std::vector<double> params = {3,
1560 im_extremity.
get_j()};
1562 std::vector<double> params;
1563 params.push_back(3);
1564 params.push_back(im_centroid.
get_i());
1565 params.push_back(im_centroid.
get_j());
1566 params.push_back(im_extremity.
get_i());
1567 params.push_back(im_extremity.
get_j());
1569 features.push_back(params);
1590 bool displayFullModel)
1592 std::vector<std::vector<double> > models;
1600 std::vector<std::vector<double> > lineModels =
1602 models.insert(models.end(), lineModels.begin(), lineModels.end());
1624 if (dx <= std::numeric_limits<double>::epsilon() && dy <= std::numeric_limits<double>::epsilon() &&
1625 dz <= std::numeric_limits<double>::epsilon())
1637 (*it)->setCameraParameters(camera);
1647 (*it)->useScanLine = v;
unsigned int size() const
Return the number of elements of the 2D array.
Generic class defining intrinsic camera parameters.
void computeFov(const unsigned int &w, const unsigned int &h)
Implementation of column vector and the associated operations.
static double dotProd(const vpColVector &a, const vpColVector &b)
vpColVector & normalize()
void resize(unsigned int i, bool flagNullify=true)
Class to define RGB colors available for display functionalities.
static const vpColor blue
static void displayLine(const vpImage< unsigned char > &I, const vpImagePoint &ip1, const vpImagePoint &ip2, const vpColor &color, unsigned int thickness=1, bool segment=true)
static void displayArrow(const vpImage< unsigned char > &I, const vpImagePoint &ip1, const vpImagePoint &ip2, const vpColor &color=vpColor::white, unsigned int w=4, unsigned int h=2, unsigned int thickness=1)
error that can be emitted by ViSP classes.
@ badValue
Used to indicate that a value is not in the allowed range.
Implementation of an homogeneous matrix and operations on such kind of matrices.
vpHomogeneousMatrix inverse() const
Class that defines a 2D point in an image. This class is useful for image processing and stores only ...
unsigned int getWidth() const
unsigned int getHeight() const
static double sqr(double x)
Implementation of a matrix and operations on matrices.
void svd(vpColVector &w, vpMatrix &V)
vpColVector getCol(unsigned int j) const
vpMbScanLine & getMbScanLineRenderer()
bool isVisible(unsigned int i)
void computeScanLineQuery(const vpPoint &a, const vpPoint &b, std::vector< std::pair< vpPoint, vpPoint > > &lines, const bool &displayResults=false)
Manage the line of a polygon used in the model-based tracker.
void setIndex(unsigned int i)
vpPoint * p2
The second extremity.
std::list< int > Lindex_polygon
Index of the faces which contain the line.
void buildFrom(vpPoint &_p1, vpPoint &_p2, vpUniRand &rand_gen)
vpMbHiddenFaces< vpMbtPolygon > * hiddenface
Pointer to the list of faces.
std::vector< std::vector< double > > getModelForDisplay(unsigned int width, unsigned int height, const vpHomogeneousMatrix &cMo, const vpCameraParameters &cam, bool displayFullModel=false)
bool useScanLine
Use scanline rendering.
vpPoint * p1
The first extremity.
void setCameraParameters(const vpCameraParameters &camera)
void setName(const std::string &line_name)
void setVisible(bool _isvisible)
void addPolygon(const int &index)
vpMbtPolygon & getPolygon()
double m_pclPlaneEstimationRansacThreshold
PCL plane estimation RANSAC threshold.
int m_pclPlaneEstimationMethod
PCL plane estimation method.
double m_distNearClip
Distance for near clipping.
void computeInteractionMatrix(const vpHomogeneousMatrix &cMo, vpMatrix &L, vpColVector &features)
std::vector< std::vector< double > > getModelForDisplay(unsigned int width, unsigned int height, const vpHomogeneousMatrix &cMo, const vpCameraParameters &cam, bool displayFullModel=false)
void addLine(vpPoint &p1, vpPoint &p2, vpMbHiddenFaces< vpMbtPolygon > *const faces, vpUniRand &rand_gen, int polygon=-1, std::string name="")
void setCameraParameters(const vpCameraParameters &camera)
void computeDesiredFeaturesSVD(const std::vector< double > &point_cloud_face, const vpHomogeneousMatrix &cMo, vpColVector &desired_features, vpColVector &desired_normal, vpColVector ¢roid_point)
double m_distFarClip
Distance for near clipping.
bool samePoint(const vpPoint &P1, const vpPoint &P2) const
bool computeDesiredFeatures(const vpHomogeneousMatrix &cMo, unsigned int width, unsigned int height, const pcl::PointCloud< pcl::PointXYZ >::ConstPtr &point_cloud, vpColVector &desired_features, unsigned int stepX, unsigned int stepY, const vpImage< bool > *mask=NULL)
void displayFeature(const vpImage< unsigned char > &I, const vpHomogeneousMatrix &cMo, const vpCameraParameters &cam, double scale=0.05, unsigned int thickness=1)
vpMbHiddenFaces< vpMbtPolygon > * m_hiddenFace
Pointer to the list of faces.
std::vector< std::vector< double > > getFeaturesForDisplay(const vpHomogeneousMatrix &cMo, const vpCameraParameters &cam, double scale=0.05)
bool computePolygonCentroid(const std::vector< vpPoint > &points, vpPoint ¢roid)
void computeROI(const vpHomogeneousMatrix &cMo, unsigned int width, unsigned int height, std::vector< vpImagePoint > &roiPts)
void setScanLineVisibilityTest(bool v)
void estimatePlaneEquationSVD(const std::vector< double > &point_cloud_face, const vpHomogeneousMatrix &cMo, vpColVector &plane_equation_estimated, vpColVector ¢roid)
std::vector< vpMbtDistanceLine * > m_listOfFaceLines
void computeDesiredNormalAndCentroid(const vpHomogeneousMatrix &cMo, const vpColVector &desired_normal, const vpColVector ¢roid_point)
bool m_isTrackedDepthNormalFace
vpFeatureEstimationType m_featureEstimationMethod
Method to estimate the desired features.
vpMbtPolygon * m_polygon
Polygon defining the face.
vpPoint m_faceDesiredCentroid
Desired centroid (computed from the sensor)
void display(const vpImage< unsigned char > &I, const vpHomogeneousMatrix &cMo, const vpCameraParameters &cam, const vpColor &col, unsigned int thickness=1, bool displayFullModel=false)
vpCameraParameters m_cam
Camera intrinsic parameters.
@ ROBUST_FEATURE_ESTIMATION
@ ROBUST_SVD_PLANE_ESTIMATION
vpPlane m_planeObject
Plane equation described in the object frame.
void computeVisibilityDisplay()
bool m_faceActivated
True if the face should be considered by the tracker.
@ GEOMETRIC_CENTROID
Compute the geometric centroid.
vpFaceCentroidType m_faceCentroidMethod
Method to compute the face centroid for the current features.
int m_pclPlaneEstimationRansacMaxIter
PCL pane estimation max number of iterations.
unsigned int m_clippingFlag
Flags specifying which clipping to used.
void computeDesiredFeaturesRobustFeatures(const std::vector< double > &point_cloud_face_custom, const std::vector< double > &point_cloud_face, const vpHomogeneousMatrix &cMo, vpColVector &desired_features, vpColVector &desired_normal, vpColVector ¢roid_point)
vpPoint m_faceDesiredNormal
Face (normalized) normal (computed from the sensor)
void estimateFeatures(const std::vector< double > &point_cloud_face, const vpHomogeneousMatrix &cMo, vpColVector &x_estimated, std::vector< double > &weights)
virtual ~vpMbtFaceDepthNormal()
std::vector< PolygonLine > m_polygonLines
bool computeDesiredFeaturesPCL(const pcl::PointCloud< pcl::PointXYZ >::ConstPtr &point_cloud_face, vpColVector &desired_features, vpColVector &desired_normal, vpColVector ¢roid_point)
void computeNormalVisibility(double nx, double ny, double nz, const vpColVector ¢roid_point, vpColVector &face_normal)
bool m_useScanLine
Scan line visibility.
virtual bool isVisible(const vpHomogeneousMatrix &cMo, double alpha, const bool &modulo=false, const vpCameraParameters &cam=vpCameraParameters(), unsigned int width=0, unsigned int height=0)
static bool inMask(const vpImage< bool > *mask, unsigned int i, unsigned int j)
static void convertPoint(const vpCameraParameters &cam, const double &x, const double &y, double &u, double &v)
static void convertPoint(const vpCameraParameters &cam, const double &u, const double &v, double &x, double &y)
void changeFrame(const vpHomogeneousMatrix &cMo)
Class that defines a 3D point in the object frame and allows forward projection of a 3D point in the ...
double get_oX() const
Get the point oX coordinate in the object frame.
double get_y() const
Get the point y coordinate in the image plane.
double get_Y() const
Get the point cY coordinate in the camera frame.
double get_oZ() const
Get the point oZ coordinate in the object frame.
void set_X(double cX)
Set the point cX coordinate in the camera frame.
double get_x() const
Get the point x coordinate in the image plane.
void set_Y(double cY)
Set the point cY coordinate in the camera frame.
double get_Z() const
Get the point cZ coordinate in the camera frame.
void set_Z(double cZ)
Set the point cZ coordinate in the camera frame.
double get_oY() const
Get the point oY coordinate in the object frame.
void changeFrame(const vpHomogeneousMatrix &cMo, vpColVector &cP) const
double get_X() const
Get the point cX coordinate in the camera frame.
void setWorldCoordinates(double oX, double oY, double oZ)
Implements a 3D polygon with render functionalities like clipping.
void setFarClippingDistance(const double &dist)
void setNearClippingDistance(const double &dist)
void setClipping(const unsigned int &flags)
void getRoiClipped(const vpCameraParameters &cam, std::vector< vpImagePoint > &roi)
void getPolygonClipped(std::vector< std::pair< vpPoint, unsigned int > > &poly)
Defines a generic 2D polygon.
vpRect getBoundingBox() const
bool isInside(const vpImagePoint &iP, const PointInPolygonMethod &method=PnPolyRayCasting) const
Defines a rectangle in the plane.
void setRight(double pos)
void setBottom(double pos)
Class for generating random numbers with uniform probability density.
VISP_EXPORT bool checkSSE2()