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_isTracked(false), m_isVisible(false), m_listOfFaceLines(),
63 m_planeCamera(), m_pclPlaneEstimationMethod(2),
64 m_pclPlaneEstimationRansacMaxIter(200), m_pclPlaneEstimationRansacThreshold(0.001), m_polygonLines()
92 PolygonLine polygon_line;
95 polygon_line.m_poly.setNbPoint(2);
96 polygon_line.m_poly.addPoint(0, P1);
97 polygon_line.m_poly.addPoint(1, P2);
103 polygon_line.m_p1 = &polygon_line.m_poly.p[0];
104 polygon_line.m_p2 = &polygon_line.m_poly.p[1];
109 bool already_here =
false;
150 const unsigned int height,
151 const pcl::PointCloud<pcl::PointXYZ>::ConstPtr &point_cloud,
152 vpColVector &desired_features,
const unsigned int stepX,
153 const unsigned int stepY
154 #
if DEBUG_DISPLAY_DEPTH_NORMAL
157 std::vector<std::vector<vpImagePoint> > &roiPts_vec
163 if (width == 0 || height == 0)
166 std::vector<vpImagePoint> roiPts;
170 #
if DEBUG_DISPLAY_DEPTH_NORMAL
176 if (roiPts.size() <= 2) {
178 std::cerr <<
"Error: roiPts.size() <= 2 in computeDesiredFeatures" << std::endl;
186 unsigned int top = (
unsigned int)std::max(0.0, bb.
getTop());
187 unsigned int bottom = (
unsigned int)std::min((
double)height, std::max(0.0, bb.
getBottom()));
188 unsigned int left = (
unsigned int)std::max(0.0, bb.
getLeft());
189 unsigned int right = (
unsigned int)std::min((
double)width, std::max(0.0, bb.
getRight()));
197 pcl::PointCloud<pcl::PointXYZ>::Ptr point_cloud_face(
new pcl::PointCloud<pcl::PointXYZ>);
198 std::vector<double> point_cloud_face_vec, point_cloud_face_custom;
214 double prev_x, prev_y, prev_z;
217 double x = 0.0, y = 0.0;
218 for (
unsigned int i = top; i < bottom; i += stepY) {
219 for (
unsigned int j = left; j < right; j += stepX) {
220 if (pcl::isFinite((*point_cloud)(j, i)) && (*point_cloud)(j, i).z > 0 &&
221 (
m_useScanLine ? (i < m_hiddenFace->getMbScanLineRenderer().getPrimitiveIDs().getHeight() &&
222 j < m_hiddenFace->getMbScanLineRenderer().getPrimitiveIDs().getWidth() &&
227 point_cloud_face->push_back((*point_cloud)(j, i));
230 point_cloud_face_vec.push_back((*point_cloud)(j, i).x);
231 point_cloud_face_vec.push_back((*point_cloud)(j, i).y);
232 point_cloud_face_vec.push_back((*point_cloud)(j, i).z);
244 prev_z = (*point_cloud)(j, i).z;
247 point_cloud_face_custom.push_back(prev_x);
248 point_cloud_face_custom.push_back(x);
250 point_cloud_face_custom.push_back(prev_y);
251 point_cloud_face_custom.push_back(y);
253 point_cloud_face_custom.push_back(prev_z);
254 point_cloud_face_custom.push_back((*point_cloud)(j, i).z);
258 point_cloud_face_custom.push_back(x);
259 point_cloud_face_custom.push_back(y);
260 point_cloud_face_custom.push_back((*point_cloud)(j, i).z);
265 #if DEBUG_DISPLAY_DEPTH_NORMAL 266 debugImage[i][j] = 255;
273 if (checkSSE2 && push) {
274 point_cloud_face_custom.push_back(prev_x);
275 point_cloud_face_custom.push_back(prev_y);
276 point_cloud_face_custom.push_back(prev_z);
280 if (point_cloud_face->empty() && point_cloud_face_custom.empty() && point_cloud_face_vec.empty()) {
295 desired_normal, centroid_point);
309 const unsigned int height,
310 const std::vector<vpColVector> &point_cloud,
311 vpColVector &desired_features,
const unsigned int stepX,
312 const unsigned int stepY
313 #
if DEBUG_DISPLAY_DEPTH_NORMAL
316 std::vector<std::vector<vpImagePoint> > &roiPts_vec
322 if (width == 0 || height == 0)
325 std::vector<vpImagePoint> roiPts;
329 #
if DEBUG_DISPLAY_DEPTH_NORMAL
335 if (roiPts.size() <= 2) {
337 std::cerr <<
"Error: roiPts.size() <= 2 in computeDesiredFeatures" << std::endl;
345 unsigned int top = (
unsigned int)std::max(0.0, bb.
getTop());
346 unsigned int bottom = (
unsigned int)std::min((
double)height, std::max(0.0, bb.
getBottom()));
347 unsigned int left = (
unsigned int)std::max(0.0, bb.
getLeft());
348 unsigned int right = (
unsigned int)std::min((
double)width, std::max(0.0, bb.
getRight()));
356 std::vector<double> point_cloud_face, point_cloud_face_custom;
368 double prev_x, prev_y, prev_z;
371 double x = 0.0, y = 0.0;
372 for (
unsigned int i = top; i < bottom; i += stepY) {
373 for (
unsigned int j = left; j < right; j += stepX) {
374 if (point_cloud[i * width + j][2] > 0 &&
375 (
m_useScanLine ? (i < m_hiddenFace->getMbScanLineRenderer().getPrimitiveIDs().getHeight() &&
376 j < m_hiddenFace->getMbScanLineRenderer().getPrimitiveIDs().getWidth() &&
380 point_cloud_face.push_back(point_cloud[i * width + j][0]);
381 point_cloud_face.push_back(point_cloud[i * width + j][1]);
382 point_cloud_face.push_back(point_cloud[i * width + j][2]);
394 prev_z = point_cloud[i * width + j][2];
397 point_cloud_face_custom.push_back(prev_x);
398 point_cloud_face_custom.push_back(x);
400 point_cloud_face_custom.push_back(prev_y);
401 point_cloud_face_custom.push_back(y);
403 point_cloud_face_custom.push_back(prev_z);
404 point_cloud_face_custom.push_back(point_cloud[i * width + j][2]);
408 point_cloud_face_custom.push_back(x);
409 point_cloud_face_custom.push_back(y);
410 point_cloud_face_custom.push_back(point_cloud[i * width + j][2]);
414 #if DEBUG_DISPLAY_DEPTH_NORMAL 415 debugImage[i][j] = 255;
422 if (checkSSE2 && push) {
423 point_cloud_face_custom.push_back(prev_x);
424 point_cloud_face_custom.push_back(prev_y);
425 point_cloud_face_custom.push_back(prev_z);
429 if (point_cloud_face.empty() && point_cloud_face_custom.empty()) {
438 pcl::PointCloud<pcl::PointXYZ>::Ptr point_cloud_face_pcl(
new pcl::PointCloud<pcl::PointXYZ>);
439 point_cloud_face_pcl->reserve(point_cloud_face.size() / 3);
441 for (
size_t i = 0; i < point_cloud_face.size() / 3; i++) {
442 point_cloud_face_pcl->push_back(
443 pcl::PointXYZ(point_cloud_face[3 * i], point_cloud_face[3 * i + 1], point_cloud_face[3 * i + 2]));
453 desired_normal, centroid_point);
472 pcl::ModelCoefficients::Ptr coefficients(
new pcl::ModelCoefficients);
473 pcl::PointIndices::Ptr inliers(
new pcl::PointIndices);
475 pcl::SACSegmentation<pcl::PointXYZ> seg;
477 seg.setOptimizeCoefficients(
true);
479 seg.setModelType(pcl::SACMODEL_PLANE);
484 seg.setInputCloud(point_cloud_face);
485 seg.segment(*inliers, *coefficients);
487 pcl::PointCloud<pcl::PointXYZ>::Ptr point_cloud_face_extracted(
new pcl::PointCloud<pcl::PointXYZ>);
489 pcl::ExtractIndices<pcl::PointXYZ> extract;
492 extract.setInputCloud(point_cloud_face);
493 extract.setIndices(inliers);
494 extract.setNegative(
false);
495 extract.filter(*point_cloud_face_extracted);
497 pcl::PointXYZ centroid_point_pcl;
498 if (pcl::computeCentroid(*point_cloud_face_extracted, centroid_point_pcl)) {
499 pcl::PointXYZ face_normal;
501 centroid_point_pcl, face_normal);
503 desired_features.
resize(3,
false);
504 desired_features[0] = -coefficients->values[0] / coefficients->values[3];
505 desired_features[1] = -coefficients->values[1] / coefficients->values[3];
506 desired_features[2] = -coefficients->values[2] / coefficients->values[3];
508 desired_normal[0] = face_normal.x;
509 desired_normal[1] = face_normal.y;
510 desired_normal[2] = face_normal.z;
512 centroid_point[0] = centroid_point_pcl.x;
513 centroid_point[1] = centroid_point_pcl.y;
514 centroid_point[2] = centroid_point_pcl.z;
516 std::cerr <<
"Cannot compute centroid!" << std::endl;
519 }
catch (
const pcl::PCLException &e) {
520 std::cerr <<
"Catch a PCL exception: " << e.what() << std::endl;
529 const std::vector<double> &point_cloud_face,
535 std::vector<double> weights;
540 for (
size_t i = 0; i < point_cloud_face.size() / 3; i++) {
541 centroid_point[0] += weights[i] * point_cloud_face[3 * i];
542 centroid_point[1] += weights[i] * point_cloud_face[3 * i + 1];
543 centroid_point[2] += weights[i] * point_cloud_face[3 * i + 2];
548 centroid_point[0] /= den;
549 centroid_point[1] /= den;
550 centroid_point[2] /= den;
563 desired_features.
resize(3,
false);
564 desired_features[0] = -plane_equation_SVD[0] / plane_equation_SVD[3];
565 desired_features[1] = -plane_equation_SVD[1] / plane_equation_SVD[3];
566 desired_features[2] = -plane_equation_SVD[2] / plane_equation_SVD[3];
578 centroid_cam[0] = centroid_point[0];
579 centroid_cam[1] = centroid_point[1];
580 centroid_cam[2] = centroid_point[2];
588 face_normal_cam[0] = desired_normal[0];
589 face_normal_cam[1] = desired_normal[1];
590 face_normal_cam[2] = desired_normal[2];
591 face_normal_cam[3] = 1;
599 if (points_.empty()) {
603 if (points_.size() < 2) {
604 centroid = points_[0];
608 std::vector<vpPoint> points = points_;
609 points.push_back(points_.front());
611 double A1 = 0.0, A2 = 0.0, c_x1 = 0.0, c_x2 = 0.0, c_y = 0.0, c_z = 0.0;
613 for (
size_t i = 0; i < points.size() - 1; i++) {
615 c_x1 += (points[i].get_X() + points[i + 1].get_X()) *
616 (points[i].get_X() * points[i + 1].get_Y() - points[i + 1].get_X() * points[i].get_Y());
617 c_y += (points[i].get_Y() + points[i + 1].get_Y()) *
618 (points[i].get_X() * points[i + 1].get_Y() - points[i + 1].get_X() * points[i].get_Y());
619 A1 += points[i].
get_X() * points[i + 1].get_Y() - points[i + 1].get_X() * points[i].get_Y();
622 c_x2 += (points[i].get_X() + points[i + 1].get_X()) *
623 (points[i].get_X() * points[i + 1].get_Z() - points[i + 1].get_X() * points[i].get_Z());
624 c_z += (points[i].get_Z() + points[i + 1].get_Z()) *
625 (points[i].get_X() * points[i + 1].get_Z() - points[i + 1].get_X() * points[i].get_Z());
626 A2 += points[i].get_X() * points[i + 1].get_Z() - points[i + 1].get_X() * points[i].get_Z();
635 centroid.
set_X(c_x1);
637 centroid.
set_X(c_x2);
647 const unsigned int height, std::vector<vpImagePoint> &roiPts
648 #
if DEBUG_DISPLAY_DEPTH_NORMAL
650 std::vector<std::vector<vpImagePoint> > &roiPts_vec
659 it->m_p1->changeFrame(cMo);
660 it->m_p2->changeFrame(cMo);
664 it->m_poly.changeFrame(cMo);
665 it->m_poly.computePolygonClipped(
m_cam);
667 if (it->m_poly.polyClipped.size() == 2 &&
675 std::vector<std::pair<vpPoint, vpPoint> > linesLst;
679 for (
unsigned int i = 0; i < linesLst.size(); i++) {
680 linesLst[i].first.project();
681 linesLst[i].second.project();
689 roiPts.push_back(ip1);
690 roiPts.push_back(ip2);
692 #if DEBUG_DISPLAY_DEPTH_NORMAL 693 std::vector<vpImagePoint> roiPts_;
694 roiPts_.push_back(ip1);
695 roiPts_.push_back(ip2);
696 roiPts_vec.push_back(roiPts_);
705 #if DEBUG_DISPLAY_DEPTH_NORMAL 706 roiPts_vec.push_back(roiPts);
720 bool isvisible =
false;
724 int index = *itindex;
757 std::vector<vpImagePoint> roiPts;
760 std::vector<vpPoint> polyPts;
768 e4[0] = -centroid.
get_X();
769 e4[1] = -centroid.
get_Y();
770 e4[2] = -centroid.
get_Z();
773 double centroid_x = 0.0;
774 double centroid_y = 0.0;
775 double centroid_z = 0.0;
777 for (
size_t i = 0; i < polyPts.size(); i++) {
778 centroid_x += polyPts[i].get_X();
779 centroid_y += polyPts[i].get_Y();
780 centroid_z += polyPts[i].get_Z();
783 centroid_x /= polyPts.
size();
784 centroid_y /= polyPts.size();
785 centroid_z /= polyPts.size();
792 centroid.
set_X(centroid_x);
793 centroid.
set_Y(centroid_y);
794 centroid.
set_Z(centroid_z);
797 correct_normal.
resize(3,
false);
799 if (angle < M_PI_2) {
800 correct_normal = faceNormal;
802 correct_normal[0] = -faceNormal[0];
803 correct_normal[1] = -faceNormal[1];
804 correct_normal[2] = -faceNormal[2];
810 const pcl::PointXYZ ¢roid_point, pcl::PointXYZ &face_normal)
819 e4[0] = -centroid_point.x;
820 e4[1] = -centroid_point.y;
821 e4[2] = -centroid_point.z;
825 if (angle < M_PI_2) {
826 face_normal = pcl::PointXYZ(faceNormal[0], faceNormal[1], faceNormal[2]);
828 face_normal = pcl::PointXYZ(-faceNormal[0], -faceNormal[1], -faceNormal[2]);
836 face_normal.
resize(3,
false);
846 if (angle >= M_PI_2) {
847 face_normal[0] = -face_normal[0];
848 face_normal[1] = -face_normal[1];
849 face_normal[2] = -face_normal[2];
855 L.
resize(3, 6,
false,
false);
868 features.
resize(3,
false);
869 features[0] = -ux / D;
870 features[1] = -uy / D;
871 features[2] = -uz / D;
874 L[0][0] = ux * ux / D2;
875 L[0][1] = ux * uy / D2;
876 L[0][2] = ux * uz / D2;
882 L[1][0] = ux * uy / D2;
883 L[1][1] = uy * uy / D2;
884 L[1][2] = uy * uz / D2;
890 L[2][0] = ux * uz / D2;
891 L[2][1] = uy * uz / D2;
892 L[2][2] = uz * uz / D2;
900 const bool displayFullModel)
908 line->
display(I, cMo, cam, col, thickness, displayFullModel);
915 const bool displayFullModel)
923 line->
display(I, cMo, cam, col, thickness, displayFullModel);
930 const unsigned int thickness)
946 pt_extremity.
set_X(pt_centroid.
get_X() + pt_normal.get_X() * scale);
947 pt_extremity.
set_Y(pt_centroid.
get_Y() + pt_normal.get_Y() * scale);
948 pt_extremity.
set_Z(pt_centroid.
get_Z() + pt_normal.get_Z() * scale);
973 pt_extremity.
set_X(pt_centroid.
get_X() + correct_normal[0] * scale);
974 pt_extremity.
set_Y(pt_centroid.
get_Y() + correct_normal[1] * scale);
975 pt_extremity.
set_Z(pt_centroid.
get_Z() + correct_normal[2] * scale);
986 const unsigned int thickness)
1002 pt_extremity.
set_X(pt_centroid.
get_X() + pt_normal.get_X() * scale);
1003 pt_extremity.
set_Y(pt_centroid.
get_Y() + pt_normal.get_Y() * scale);
1004 pt_extremity.
set_Z(pt_centroid.
get_Z() + pt_normal.get_Z() * scale);
1029 pt_extremity.
set_X(pt_centroid.
get_X() + correct_normal[0] * scale);
1030 pt_extremity.
set_Y(pt_centroid.
get_Y() + correct_normal[1] * scale);
1031 pt_extremity.
set_Z(pt_centroid.
get_Z() + correct_normal[2] * scale);
1043 vpMbtTukeyEstimator<double> tukey_robust;
1044 std::vector<double> residues(point_cloud_face.size() / 3);
1046 w.resize(point_cloud_face.size() / 3, 1.0);
1048 unsigned int max_iter = 30, iter = 0;
1049 double error = 0.0, prev_error = -1.0;
1050 double A = 0.0, B = 0.0, C = 0.0;
1052 Mat33<double> ATA_3x3;
1061 while (std::fabs(error - prev_error) > 1e-6 && (iter < max_iter)) {
1078 if (point_cloud_face.size() / 3 >= 2) {
1079 const double *ptr_point_cloud = &point_cloud_face[0];
1080 const __m128d vA = _mm_set1_pd(A);
1081 const __m128d vB = _mm_set1_pd(B);
1082 const __m128d vC = _mm_set1_pd(C);
1083 const __m128d vones = _mm_set1_pd(1.0);
1085 double *ptr_residues = &residues[0];
1087 for (; cpt <= point_cloud_face.size() - 6; cpt += 6, ptr_point_cloud += 6, ptr_residues += 2) {
1088 const __m128d vxi = _mm_loadu_pd(ptr_point_cloud);
1089 const __m128d vyi = _mm_loadu_pd(ptr_point_cloud + 2);
1090 const __m128d vZi = _mm_loadu_pd(ptr_point_cloud + 4);
1091 const __m128d vinvZi = _mm_div_pd(vones, vZi);
1094 _mm_add_pd(_mm_add_pd(_mm_mul_pd(vA, vxi), _mm_mul_pd(vB, vyi)), _mm_sub_pd(vC, vinvZi));
1095 _mm_storeu_pd(ptr_residues, tmp);
1099 for (; cpt < point_cloud_face.size(); cpt += 3) {
1100 double xi = point_cloud_face[cpt];
1101 double yi = point_cloud_face[cpt + 1];
1102 double Zi = point_cloud_face[cpt + 2];
1104 residues[cpt / 3] = (A * xi + B * yi + C - 1 / Zi);
1108 tukey_robust.MEstimator(residues, w, 1e-2);
1110 __m128d vsum_wi2_xi2 = _mm_setzero_pd();
1111 __m128d vsum_wi2_yi2 = _mm_setzero_pd();
1112 __m128d vsum_wi2 = _mm_setzero_pd();
1113 __m128d vsum_wi2_xi_yi = _mm_setzero_pd();
1114 __m128d vsum_wi2_xi = _mm_setzero_pd();
1115 __m128d vsum_wi2_yi = _mm_setzero_pd();
1117 __m128d vsum_wi2_xi_Zi = _mm_setzero_pd();
1118 __m128d vsum_wi2_yi_Zi = _mm_setzero_pd();
1119 __m128d vsum_wi2_Zi = _mm_setzero_pd();
1123 if (point_cloud_face.size() / 3 >= 2) {
1124 const double *ptr_point_cloud = &point_cloud_face[0];
1125 double *ptr_w = &w[0];
1127 const __m128d vones = _mm_set1_pd(1.0);
1129 for (; cpt <= point_cloud_face.size() - 6; cpt += 6, ptr_point_cloud += 6, ptr_w += 2) {
1130 const __m128d vwi2 = _mm_mul_pd(_mm_loadu_pd(ptr_w), _mm_loadu_pd(ptr_w));
1132 const __m128d vxi = _mm_loadu_pd(ptr_point_cloud);
1133 const __m128d vyi = _mm_loadu_pd(ptr_point_cloud + 2);
1134 const __m128d vZi = _mm_loadu_pd(ptr_point_cloud + 4);
1135 const __m128d vinvZi = _mm_div_pd(vones, vZi);
1137 vsum_wi2_xi2 = _mm_add_pd(vsum_wi2_xi2, _mm_mul_pd(vwi2, _mm_mul_pd(vxi, vxi)));
1138 vsum_wi2_yi2 = _mm_add_pd(vsum_wi2_yi2, _mm_mul_pd(vwi2, _mm_mul_pd(vyi, vyi)));
1139 vsum_wi2 = _mm_add_pd(vsum_wi2, vwi2);
1140 vsum_wi2_xi_yi = _mm_add_pd(vsum_wi2_xi_yi, _mm_mul_pd(vwi2, _mm_mul_pd(vxi, vyi)));
1141 vsum_wi2_xi = _mm_add_pd(vsum_wi2_xi, _mm_mul_pd(vwi2, vxi));
1142 vsum_wi2_yi = _mm_add_pd(vsum_wi2_yi, _mm_mul_pd(vwi2, vyi));
1144 const __m128d vwi2_invZi = _mm_mul_pd(vwi2, vinvZi);
1145 vsum_wi2_xi_Zi = _mm_add_pd(vsum_wi2_xi_Zi, _mm_mul_pd(vxi, vwi2_invZi));
1146 vsum_wi2_yi_Zi = _mm_add_pd(vsum_wi2_yi_Zi, _mm_mul_pd(vyi, vwi2_invZi));
1147 vsum_wi2_Zi = _mm_add_pd(vsum_wi2_Zi, vwi2_invZi);
1152 _mm_storeu_pd(vtmp, vsum_wi2_xi2);
1153 double sum_wi2_xi2 = vtmp[0] + vtmp[1];
1155 _mm_storeu_pd(vtmp, vsum_wi2_yi2);
1156 double sum_wi2_yi2 = vtmp[0] + vtmp[1];
1158 _mm_storeu_pd(vtmp, vsum_wi2);
1159 double sum_wi2 = vtmp[0] + vtmp[1];
1161 _mm_storeu_pd(vtmp, vsum_wi2_xi_yi);
1162 double sum_wi2_xi_yi = vtmp[0] + vtmp[1];
1164 _mm_storeu_pd(vtmp, vsum_wi2_xi);
1165 double sum_wi2_xi = vtmp[0] + vtmp[1];
1167 _mm_storeu_pd(vtmp, vsum_wi2_yi);
1168 double sum_wi2_yi = vtmp[0] + vtmp[1];
1170 _mm_storeu_pd(vtmp, vsum_wi2_xi_Zi);
1171 double sum_wi2_xi_Zi = vtmp[0] + vtmp[1];
1173 _mm_storeu_pd(vtmp, vsum_wi2_yi_Zi);
1174 double sum_wi2_yi_Zi = vtmp[0] + vtmp[1];
1176 _mm_storeu_pd(vtmp, vsum_wi2_Zi);
1177 double sum_wi2_Zi = vtmp[0] + vtmp[1];
1179 for (; cpt < point_cloud_face.size(); cpt += 3) {
1180 double wi2 = w[cpt / 3] * w[cpt / 3];
1182 double xi = point_cloud_face[cpt];
1183 double yi = point_cloud_face[cpt + 1];
1184 double Zi = point_cloud_face[cpt + 2];
1185 double invZi = 1.0 / Zi;
1187 sum_wi2_xi2 += wi2 * xi * xi;
1188 sum_wi2_yi2 += wi2 * yi * yi;
1190 sum_wi2_xi_yi += wi2 * xi * yi;
1191 sum_wi2_xi += wi2 * xi;
1192 sum_wi2_yi += wi2 * yi;
1194 sum_wi2_xi_Zi += wi2 * xi * invZi;
1195 sum_wi2_yi_Zi += wi2 * yi * invZi;
1196 sum_wi2_Zi += wi2 * invZi;
1199 ATA_3x3[0] = sum_wi2_xi2;
1200 ATA_3x3[1] = sum_wi2_xi_yi;
1201 ATA_3x3[2] = sum_wi2_xi;
1202 ATA_3x3[3] = sum_wi2_xi_yi;
1203 ATA_3x3[4] = sum_wi2_yi2;
1204 ATA_3x3[5] = sum_wi2_yi;
1205 ATA_3x3[6] = sum_wi2_xi;
1206 ATA_3x3[7] = sum_wi2_yi;
1207 ATA_3x3[8] = sum_wi2;
1209 Mat33<double> minv = ATA_3x3.inverse();
1211 A = minv[0] * sum_wi2_xi_Zi + minv[1] * sum_wi2_yi_Zi + minv[2] * sum_wi2_Zi;
1212 B = minv[3] * sum_wi2_xi_Zi + minv[4] * sum_wi2_yi_Zi + minv[5] * sum_wi2_Zi;
1213 C = minv[6] * sum_wi2_xi_Zi + minv[7] * sum_wi2_yi_Zi + minv[8] * sum_wi2_Zi;
1221 __m128d verror = _mm_set1_pd(0.0);
1222 if (point_cloud_face.size() / 3 >= 2) {
1223 const double *ptr_point_cloud = &point_cloud_face[0];
1224 const __m128d vA = _mm_set1_pd(A);
1225 const __m128d vB = _mm_set1_pd(B);
1226 const __m128d vC = _mm_set1_pd(C);
1227 const __m128d vones = _mm_set1_pd(1.0);
1229 double *ptr_residues = &residues[0];
1231 for (; cpt <= point_cloud_face.size() - 6; cpt += 6, ptr_point_cloud += 6, ptr_residues += 2) {
1232 const __m128d vxi = _mm_loadu_pd(ptr_point_cloud);
1233 const __m128d vyi = _mm_loadu_pd(ptr_point_cloud + 2);
1234 const __m128d vZi = _mm_loadu_pd(ptr_point_cloud + 4);
1235 const __m128d vinvZi = _mm_div_pd(vones, vZi);
1237 const __m128d tmp = _mm_add_pd(_mm_add_pd(_mm_mul_pd(vA, vxi), _mm_mul_pd(vB, vyi)), _mm_sub_pd(vC, vinvZi));
1238 verror = _mm_add_pd(verror, _mm_mul_pd(tmp, tmp));
1240 _mm_storeu_pd(ptr_residues, tmp);
1244 _mm_storeu_pd(vtmp, verror);
1245 error = vtmp[0] + vtmp[1];
1247 for (
size_t idx = cpt; idx < point_cloud_face.size(); idx += 3) {
1248 double xi = point_cloud_face[idx];
1249 double yi = point_cloud_face[idx + 1];
1250 double Zi = point_cloud_face[idx + 2];
1252 error +=
vpMath::sqr(A * xi + B * yi + C - 1 / Zi);
1253 residues[idx / 3] = (A * xi + B * yi + C - 1 / Zi);
1256 error /= point_cloud_face.size() / 3;
1262 while (std::fabs(error - prev_error) > 1e-6 && (iter < max_iter)) {
1278 for (
size_t i = 0; i < point_cloud_face.size() / 3; i++) {
1279 double xi = point_cloud_face[3 * i];
1280 double yi = point_cloud_face[3 * i + 1];
1281 double Zi = point_cloud_face[3 * i + 2];
1283 residues[i] = (A * xi + B * yi + C - 1 / Zi);
1287 tukey_robust.MEstimator(residues, w, 1e-2);
1290 double sum_wi2_xi2 = 0.0, sum_wi2_yi2 = 0.0, sum_wi2 = 0.0;
1291 double sum_wi2_xi_yi = 0.0, sum_wi2_xi = 0.0, sum_wi2_yi = 0.0;
1293 double sum_wi2_xi_Zi = 0.0, sum_wi2_yi_Zi = 0.0, sum_wi2_Zi = 0.0;
1295 for (
size_t i = 0; i < point_cloud_face.size() / 3; i++) {
1296 double wi2 = w[i] * w[i];
1298 double xi = point_cloud_face[3 * i];
1299 double yi = point_cloud_face[3 * i + 1];
1300 double Zi = point_cloud_face[3 * i + 2];
1301 double invZi = 1 / Zi;
1303 sum_wi2_xi2 += wi2 * xi * xi;
1304 sum_wi2_yi2 += wi2 * yi * yi;
1306 sum_wi2_xi_yi += wi2 * xi * yi;
1307 sum_wi2_xi += wi2 * xi;
1308 sum_wi2_yi += wi2 * yi;
1310 sum_wi2_xi_Zi += wi2 * xi * invZi;
1311 sum_wi2_yi_Zi += wi2 * yi * invZi;
1312 sum_wi2_Zi += wi2 * invZi;
1315 ATA_3x3[0] = sum_wi2_xi2;
1316 ATA_3x3[1] = sum_wi2_xi_yi;
1317 ATA_3x3[2] = sum_wi2_xi;
1318 ATA_3x3[3] = sum_wi2_xi_yi;
1319 ATA_3x3[4] = sum_wi2_yi2;
1320 ATA_3x3[5] = sum_wi2_yi;
1321 ATA_3x3[6] = sum_wi2_xi;
1322 ATA_3x3[7] = sum_wi2_yi;
1323 ATA_3x3[8] = sum_wi2;
1325 Mat33<double> minv = ATA_3x3.inverse();
1327 A = minv[0] * sum_wi2_xi_Zi + minv[1] * sum_wi2_yi_Zi + minv[2] * sum_wi2_Zi;
1328 B = minv[3] * sum_wi2_xi_Zi + minv[4] * sum_wi2_yi_Zi + minv[5] * sum_wi2_Zi;
1329 C = minv[6] * sum_wi2_xi_Zi + minv[7] * sum_wi2_yi_Zi + minv[8] * sum_wi2_Zi;
1335 for (
size_t i = 0; i < point_cloud_face.size() / 3; i++) {
1336 double xi = point_cloud_face[3 * i];
1337 double yi = point_cloud_face[3 * i + 1];
1338 double Zi = point_cloud_face[3 * i + 2];
1340 error +=
vpMath::sqr(A * xi + B * yi + C - 1 / Zi);
1341 residues[i] = (A * xi + B * yi + C - 1 / Zi);
1344 error /= point_cloud_face.size() / 3;
1350 x_estimated.
resize(3,
false);
1360 const unsigned int max_iter = 10;
1361 double prev_error = 1e3;
1362 double error = 1e3 - 1;
1364 std::vector<double> weights(point_cloud_face.size() / 3, 1.0);
1365 std::vector<double> residues(point_cloud_face.size() / 3);
1366 vpMatrix M((
unsigned int)(point_cloud_face.size() / 3), 3);
1367 vpMbtTukeyEstimator<double> tukey;
1370 for (
unsigned int iter = 0; iter < max_iter && std::fabs(error - prev_error) > 1e-6; iter++) {
1372 tukey.MEstimator(residues, weights, 1e-4);
1384 for (
size_t i = 0; i < point_cloud_face.size() / 3; i++) {
1385 residues[i] = std::fabs(A * point_cloud_face[3 * i] + B * point_cloud_face[3 * i + 1] +
1386 C * point_cloud_face[3 * i + 2] + D) /
1387 sqrt(A * A + B * B + C * C);
1390 tukey.MEstimator(residues, weights, 1e-4);
1391 plane_equation_estimated.
resize(4,
false);
1395 double centroid_x = 0.0, centroid_y = 0.0, centroid_z = 0.0;
1396 double total_w = 0.0;
1398 for (
size_t i = 0; i < point_cloud_face.size() / 3; i++) {
1399 centroid_x += weights[i] * point_cloud_face[3 * i];
1400 centroid_y += weights[i] * point_cloud_face[3 * i + 1];
1401 centroid_z += weights[i] * point_cloud_face[3 * i + 2];
1402 total_w += weights[i];
1405 centroid_x /= total_w;
1406 centroid_y /= total_w;
1407 centroid_z /= total_w;
1410 for (
size_t i = 0; i < point_cloud_face.size() / 3; i++) {
1411 M[(
unsigned int)i][0] = weights[i] * (point_cloud_face[3 * i] - centroid_x);
1412 M[(
unsigned int)i][1] = weights[i] * (point_cloud_face[3 * i + 1] - centroid_y);
1413 M[(
unsigned int)i][2] = weights[i] * (point_cloud_face[3 * i + 2] - centroid_z);
1422 double smallestSv = W[0];
1423 unsigned int indexSmallestSv = 0;
1424 for (
unsigned int i = 1; i < W.
size(); i++) {
1425 if (W[i] < smallestSv) {
1427 indexSmallestSv = i;
1431 normal = V.
getCol(indexSmallestSv);
1434 double A = normal[0], B = normal[1], C = normal[2];
1435 double D = -(A * centroid_x + B * centroid_y + C * centroid_z);
1438 plane_equation_estimated[0] = A;
1439 plane_equation_estimated[1] = B;
1440 plane_equation_estimated[2] = C;
1441 plane_equation_estimated[3] = D;
1446 for (
size_t i = 0; i < point_cloud_face.size() / 3; i++) {
1447 residues[i] = std::fabs(A * point_cloud_face[3 * i] + B * point_cloud_face[3 * i + 1] +
1448 C * point_cloud_face[3 * i + 2] + D) /
1449 sqrt(A * A + B * B + C * C);
1450 error += residues[i] * residues[i];
1452 error /= sqrt(error / total_w);
1456 tukey.MEstimator(residues, weights, 1e-4);
1459 centroid.
resize(3,
false);
1460 double total_w = 0.0;
1462 for (
size_t i = 0; i < point_cloud_face.size() / 3; i++) {
1463 centroid[0] += weights[i] * point_cloud_face[3 * i];
1464 centroid[1] += weights[i] * point_cloud_face[3 * i + 1];
1465 centroid[2] += weights[i] * point_cloud_face[3 * i + 2];
1466 total_w += weights[i];
1469 centroid[0] /= total_w;
1470 centroid[1] /= total_w;
1471 centroid[2] /= total_w;
1474 double A = normal[0], B = normal[1], C = normal[2];
1475 double D = -(A * centroid[0] + B * centroid[1] + C * centroid[2]);
1478 plane_equation_estimated[0] = A;
1479 plane_equation_estimated[1] = B;
1480 plane_equation_estimated[2] = C;
1481 plane_equation_estimated[3] = D;
1499 if (dx <= std::numeric_limits<double>::epsilon() && dy <= std::numeric_limits<double>::epsilon() &&
1500 dz <= std::numeric_limits<double>::epsilon())
1512 (*it)->setCameraParameters(camera);
1522 (*it)->useScanLine = v;
vpFeatureEstimationType m_featureEstimationMethod
Method to estimate the desired features.
void svd(vpColVector &w, vpMatrix &V)
Implementation of a matrix and operations on matrices.
void getRoiClipped(const vpCameraParameters &cam, std::vector< vpImagePoint > &roi)
bool computeDesiredFeatures(const vpHomogeneousMatrix &cMo, const unsigned int width, const unsigned int height, const pcl::PointCloud< pcl::PointXYZ >::ConstPtr &point_cloud, vpColVector &desired_features, const unsigned int stepX, const unsigned int stepY)
double get_oY() const
Get the point Y coordinate in the object frame.
Implements a 3D polygon with render functionnalities like clipping.
void computeVisibilityDisplay()
void setVisible(bool _isvisible)
void display(const vpImage< unsigned char > &I, const vpHomogeneousMatrix &cMo, const vpCameraParameters &cam, const vpColor &col, const unsigned int thickness=1, const bool displayFullModel=false)
Implementation of an homogeneous matrix and operations on such kind of matrices.
std::list< int > Lindex_polygon
Index of the faces which contain the line.
void setFarClippingDistance(const double &dist)
int m_pclPlaneEstimationMethod
PCL plane estimation method.
static void convertPoint(const vpCameraParameters &cam, const double &x, const double &y, double &u, double &v)
Point coordinates conversion from normalized coordinates in meter to pixel coordinates ...
void resize(const unsigned int nrows, const unsigned int ncols, const bool flagNullify=true, const bool recopy_=true)
unsigned int m_clippingFlag
Flags specifying which clipping to used.
Class to define colors available for display functionnalities.
int m_pclPlaneEstimationRansacMaxIter
PCL pane estimation max number of iterations.
vpPoint * p1
The first extremity.
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)
error that can be emited by ViSP classes.
vpMbScanLine & getMbScanLineRenderer()
vpHomogeneousMatrix inverse() const
Manage the line of a polygon used in the model-based tracker.
static void convertPoint(const vpCameraParameters &cam, const double &u, const double &v, double &x, double &y)
Point coordinates conversion from pixel coordinates to normalized coordinates in meter...
unsigned int size() const
Return the number of elements of the 2D array.
double m_distNearClip
Distance for near clipping.
void addLine(vpPoint &p1, vpPoint &p2, vpMbHiddenFaces< vpMbtPolygon > *const faces, int polygon=-1, std::string name="")
void set_X(const double X)
Set the point X coordinate in the camera frame.
vpMbtPolygon & getPolygon()
bool samePoint(const vpPoint &P1, const vpPoint &P2) const
double get_oX() const
Get the point X coordinate in the object frame.
bool m_useScanLine
Scan line visibility.
vpCameraParameters m_cam
Camera intrinsic parameters.
vpRect getBoundingBox() const
Class that defines what is a point.
void computeROI(const vpHomogeneousMatrix &cMo, const unsigned int width, const unsigned int height, std::vector< vpImagePoint > &roiPts)
void setScanLineVisibilityTest(const bool v)
bool computePolygonCentroid(const std::vector< vpPoint > &points, vpPoint ¢roid)
void setCameraParameters(const vpCameraParameters &camera)
bool m_faceActivated
True if the face should be considered by the tracker.
vpMbtPolygon * m_polygon
Polygon defining the face.
Defines a generic 2D polygon.
vpColVector & normalize()
void set_Z(const double Z)
Set the point Z coordinate in the camera frame.
void computeInteractionMatrix(const vpHomogeneousMatrix &cMo, vpMatrix &L, vpColVector &features)
vpPoint * p2
The second extremity.
void changeFrame(const vpHomogeneousMatrix &cMo)
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)
static double sqr(double x)
bool computeDesiredFeaturesPCL(const pcl::PointCloud< pcl::PointXYZ >::ConstPtr &point_cloud_face, vpColVector &desired_features, vpColVector &desired_normal, vpColVector ¢roid_point)
VISP_EXPORT bool checkSSE2()
bool isInside(const vpImagePoint &iP, const PointInPolygonMethod &method=PnPolyRayCasting) const
void getPolygonClipped(std::vector< std::pair< vpPoint, unsigned int > > &poly)
vpMbHiddenFaces< vpMbtPolygon > * m_hiddenFace
Pointer to the list of faces.
Generic class defining intrinsic camera parameters.
void setIndex(const unsigned int i)
void set_Y(const double Y)
Set the point Y coordinate in the camera frame.
double get_oZ() const
Get the point Z coordinate in the object frame.
vpPoint m_faceDesiredNormal
Face (normalized) normal (computed from the sensor)
virtual bool isVisible(const vpHomogeneousMatrix &cMo, const double alpha, const bool &modulo=false, const vpCameraParameters &cam=vpCameraParameters(), const vpImage< unsigned char > &I=vpImage< unsigned char >())
double m_distFarClip
Distance for near clipping.
std::vector< vpMbtDistanceLine * > m_listOfFaceLines
void displayFeature(const vpImage< unsigned char > &I, const vpHomogeneousMatrix &cMo, const vpCameraParameters &cam, const double scale=0.05, const unsigned int thickness=1)
void setClipping(const unsigned int &flags)
std::vector< PolygonLine > m_polygonLines
vpFaceCentroidType m_faceCentroidMethod
Method to compute the face centroid for the current features.
void setName(const std::string &line_name)
void setCameraParameters(const vpCameraParameters &camera)
double get_X() const
Get the point X coordinate in the camera frame.
void computeScanLineQuery(const vpPoint &a, const vpPoint &b, std::vector< std::pair< vpPoint, vpPoint > > &lines, const bool &displayResults=false)
void setWorldCoordinates(const double oX, const double oY, const double oZ)
void estimatePlaneEquationSVD(const std::vector< double > &point_cloud_face, const vpHomogeneousMatrix &cMo, vpColVector &plane_equation_estimated, vpColVector ¢roid)
unsigned int getHeight() const
void computeDesiredFeaturesSVD(const std::vector< double > &point_cloud_face, const vpHomogeneousMatrix &cMo, vpColVector &desired_features, vpColVector &desired_normal, vpColVector ¢roid_point)
void computeDesiredNormalAndCentroid(const vpHomogeneousMatrix &cMo, const vpColVector &desired_normal, const vpColVector ¢roid_point)
Implementation of column vector and the associated operations.
static double dotProd(const vpColVector &a, const vpColVector &b)
double get_x() const
Get the point x coordinate in the image plane.
void setRight(double pos)
vpMbHiddenFaces< vpMbtPolygon > * hiddenface
Pointer to the list of faces.
double get_y() const
Get the point y coordinate in the image plane.
bool isVisible(const unsigned int i)
void addPolygon(const int &index)
void setNearClippingDistance(const double &dist)
vpPoint m_faceDesiredCentroid
Desired centroid (computed from the sensor)
Defines a rectangle in the plane.
Class that defines a 2D point in an image. This class is useful for image processing and stores only ...
Compute the geometric centroid.
virtual ~vpMbtFaceDepthNormal()
double get_Z() const
Get the point Z coordinate in the camera frame.
vpPlane m_planeObject
Plane equation described in the object frame.
void changeFrame(const vpHomogeneousMatrix &cMo, vpColVector &_cP)
double get_Y() const
Get the point Y coordinate in the camera frame.
vpColVector getCol(const unsigned int j) const
void estimateFeatures(const std::vector< double > &point_cloud_face, const vpHomogeneousMatrix &cMo, vpColVector &x_estimated, std::vector< double > &weights)
unsigned int getWidth() const
void setBottom(double pos)
void display(const vpImage< unsigned char > &I, const vpHomogeneousMatrix &cMo, const vpCameraParameters &cam, const vpColor &col, const unsigned int thickness=1, const bool displayFullModel=false)
bool useScanLine
Use scanline rendering.
void buildFrom(vpPoint &_p1, vpPoint &_p2)
static const vpColor blue
void computeNormalVisibility(const double nx, const double ny, const double nz, const vpColVector ¢roid_point, vpColVector &face_normal)
double m_pclPlaneEstimationRansacThreshold
PCL plane estimation RANSAC threshold.
void resize(const unsigned int i, const bool flagNullify=true)
void computeFov(const unsigned int &w, const unsigned int &h)