Compute the pose of a 3D object using the Ransac method.
#include <iomanip>
#include <sstream>
#include <algorithm>
#include <map>
#include <visp3/vision/vpPose.h>
#include <visp3/core/vpPoint.h>
#include <visp3/core/vpMath.h>
#include <visp3/core/vpGaussRand.h>
#include <visp3/core/vpHomogeneousMatrix.h>
const std::string file_content =
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"0.000547 0.063627 -0.034407 "
"-0.038058 0.154792 -0.009202 "
"-0.057976 0.145744 -0.001916 "
"0.048347 0.058938 -0.004908 "
"0.043359 0.058916 -0.004699 "
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"-0.069152 0.078835 0.040145 "
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"-0.009322 0.175020 -0.028678 "
"-0.060545 0.169731 -0.062221 "
"-0.068381 0.149044 -0.036363 "
"-0.050757 0.137975 0.001565 "
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"-0.027938 0.155215 -0.003967 "
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"-0.028940 0.154865 -0.002858 "
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"-0.008588 0.169530 -0.025410 "
"-0.067979 0.154919 -0.051359 "
"-0.018495 0.165075 -0.017689 "
"-0.013589 0.169514 -0.023467 "
"-0.009085 0.173025 -0.027717 "
"-0.066223 0.155560 -0.052081 "
"-0.029333 0.154386 -0.003606 "
"-0.063933 0.153712 -0.036871 "
"-0.028864 0.154571 -0.003558 "
"-0.064135 0.160881 -0.057617 "
"-0.072553 0.150608 -0.041367 "
"-0.030385 0.154168 -0.002474 "
"-0.009715 0.177216 -0.029461 "
"-0.014691 0.160456 -0.011333 "
"-0.063650 0.159498 -0.051954 "
"-0.072177 0.146332 -0.024671 "
"-0.020377 0.158233 -0.007259 "
"-0.062349 0.141045 -0.006499 "
"-0.064196 0.142314 -0.007840 "
"-0.068829 0.148429 -0.034137 "
"-0.067194 0.151677 -0.045577 "
"-0.071411 0.144356 -0.015185 "
"-0.009825 0.166960 -0.022046 "
"-0.052896 0.143026 -0.000456 "
"-0.032692 0.152804 -0.002950 "
"-0.072038 0.149669 -0.039594 "
"-0.072282 0.143895 -0.012909 ";
}
int checkInlierIndex(const std::vector<unsigned int> &vectorOfFoundInlierIndex, const std::vector<bool> &vectorOfOutlierFlags) {
int nbInlierIndexOk = 0;
for(std::vector<unsigned int>::const_iterator it = vectorOfFoundInlierIndex.begin();
it != vectorOfFoundInlierIndex.end(); ++it) {
if(!vectorOfOutlierFlags[*it]) {
nbInlierIndexOk++;
}
}
return nbInlierIndexOk;
}
bool checkInlierPoints(const std::vector<vpPoint> &vectorOfFoundInlierPoints, const std::vector<unsigned int> &vectorOfFoundInlierIndex,
const std::vector<vpPoint> &bunnyModelPoints_noisy) {
for(size_t i = 0; i < vectorOfFoundInlierPoints.size(); i++) {
if(!samePoints(vectorOfFoundInlierPoints[i], bunnyModelPoints_noisy[vectorOfFoundInlierIndex[i]])) {
std::cerr << "Problem with the inlier index and the corresponding inlier point !" << std::endl;
return false;
}
}
return true;
}
void readBunnyModelPoints(std::vector<vpPoint> &bunnyModelPoints, std::vector<vpPoint> &bunnyModelPoints_noisy) {
std::istringstream iss_file_content(file_content);
while (iss_file_content) {
double oX, oY, oZ;
iss_file_content >> oX >> oY >> oZ;
pt.project(cMo_groundTruth);
bunnyModelPoints.push_back(pt);
pt.set_x(pt.get_x() + gaussian_noise());
pt.set_y(pt.get_y() + gaussian_noise());
bunnyModelPoints_noisy.push_back(pt);
}
std::cout << "The raw model contains " << bunnyModelPoints.size() << " points." << std::endl;
std::cout << "cMo_groundTruth=\n" << cMo_groundTruth << std::endl << std::endl;
}
bool testRansac(const std::vector<vpPoint> &bunnyModelPoints_original, const std::vector<vpPoint> &bunnyModelPoints_noisy_original,
const size_t nb_model_points, const bool test_duplicate, const bool test_degenerate) {
std::vector<vpPoint> bunnyModelPoints = bunnyModelPoints_original;
std::vector<vpPoint> bunnyModelPoints_noisy = bunnyModelPoints_noisy_original;
if (nb_model_points > 0) {
bunnyModelPoints.resize(nb_model_points);
bunnyModelPoints_noisy.resize(nb_model_points);
}
vpPose ground_truth_pose, real_pose;
ground_truth_pose.
addPoints(bunnyModelPoints);
if(r_lagrange < r_dementhon) {
cMo_estimated = cMo_lagrange;
} else {
cMo_estimated = cMo_dementhon;
}
std::cout << "\ncMo estimated using VVS on data with small gaussian noise:\n" << cMo_estimated << std::endl;
std::cout << "Corresponding residual: " << r_vvs << std::endl;
size_t nbOutliers = (size_t) (0.35 * bunnyModelPoints_noisy.size());
std::vector<bool> vectorOfOutlierFlags(bunnyModelPoints_noisy.size(), false);
for(size_t i = 0; i < nbOutliers; i++) {
bunnyModelPoints_noisy[i].set_x(bunnyModelPoints_noisy[i].get_x() + noise());
bunnyModelPoints_noisy[i].set_y(bunnyModelPoints_noisy[i].get_y() + noise());
vectorOfOutlierFlags[i] = true;
}
if (test_duplicate) {
size_t nbDuplicatePoints = 100;
for (size_t i = 0; i < nbDuplicatePoints; i++) {
size_t index = (size_t) rand() % bunnyModelPoints_noisy.size();
vpPoint duplicatePoint = bunnyModelPoints_noisy[index];
bunnyModelPoints_noisy.push_back(duplicatePoint);
vectorOfOutlierFlags.push_back(true);
}
}
if (test_degenerate) {
size_t nbDegeneratePoints = 100;
double degenerate_tolerence = 9.999e-7;
std::vector<vpPoint> listOfDegeneratePoints;
for(size_t i = 0; i < nbDegeneratePoints; i++) {
size_t index = (size_t) rand() % bunnyModelPoints_noisy.size();
vpPoint degeneratePoint = bunnyModelPoints_noisy[index];
degeneratePoint.
set_oX(degeneratePoint.
get_oX() + degenerate_tolerence);
degeneratePoint.
set_oY(degeneratePoint.
get_oY() + degenerate_tolerence);
degeneratePoint.
set_oZ(degeneratePoint.
get_oZ() - degenerate_tolerence);
listOfDegeneratePoints.push_back(degeneratePoint);
index = (size_t) rand() % bunnyModelPoints_noisy.size();
degeneratePoint = bunnyModelPoints_noisy[index];
degeneratePoint.
set_x(degeneratePoint.
get_x() + degenerate_tolerence);
degeneratePoint.
set_y(degeneratePoint.
get_y() - degenerate_tolerence);
listOfDegeneratePoints.push_back(degeneratePoint);
}
for (std::vector<vpPoint>::const_iterator it_degenerate = listOfDegeneratePoints.begin();
it_degenerate != listOfDegeneratePoints.end(); ++it_degenerate) {
bunnyModelPoints_noisy.push_back(*it_degenerate);
vectorOfOutlierFlags.push_back(true);
}
}
std::vector<size_t> vectorOfIndex(bunnyModelPoints_noisy.size());
for(size_t i = 0; i < vectorOfIndex.size(); i++) {
vectorOfIndex[i] = i;
}
std::random_shuffle(vectorOfIndex.begin(), vectorOfIndex.end());
std::vector<vpPoint> bunnyModelPoints_noisy_tmp = bunnyModelPoints_noisy;
bunnyModelPoints_noisy.clear();
std::vector<bool> vectorOfOutlierFlags_tmp = vectorOfOutlierFlags;
vectorOfOutlierFlags.clear();
for(std::vector<size_t>::const_iterator it = vectorOfIndex.begin(); it != vectorOfIndex.end(); ++it) {
bunnyModelPoints_noisy.push_back(bunnyModelPoints_noisy_tmp[*it]);
vectorOfOutlierFlags.push_back(vectorOfOutlierFlags_tmp[*it]);
}
vpPose pose_ransac, pose_ransac2;
#if defined (VISP_HAVE_PTHREAD) || (defined (_WIN32) && !defined(WINRT_8_0)) || defined (VISP_HAVE_OPENMP)
# define TEST_PARALLEL_RANSAC
#endif
#ifdef TEST_PARALLEL_RANSAC
vpPose pose_ransac_parallel, pose_ransac_parallel2;
#if !defined (VISP_HAVE_OPENMP)
#endif
#endif
for(std::vector<vpPoint>::const_iterator it = bunnyModelPoints_noisy.begin();
it != bunnyModelPoints_noisy.end(); ++it) {
}
pose_ransac.
addPoints(bunnyModelPoints_noisy);
pose_ransac2.
addPoints(bunnyModelPoints_noisy);
#ifdef TEST_PARALLEL_RANSAC
pose_ransac_parallel.
addPoints(bunnyModelPoints_noisy);
pose_ransac_parallel2.
addPoints(bunnyModelPoints_noisy);
#endif
std::cout << "\nNumber of model points in the noisy data vector: "
<< bunnyModelPoints_noisy.size() << " points." << std::endl << std::endl;
unsigned int nbInlierToReachConsensus = (unsigned int)(60.0 * (double)(bunnyModelPoints_noisy.size()) / 100.0);
double threshold = 0.001;
#ifdef TEST_PARALLEL_RANSAC
#endif
std::cout << "Number of RANSAC iterations to ensure p=0.99 and epsilon=0.4: " << ransac_iterations << std::endl;
std::cout << "\ncMo estimated with RANSAC (1000 iterations) on noisy data:\n" << cMo_estimated_RANSAC << std::endl;
std::cout << "Computation time: " << t_RANSAC << " ms" << std::endl;
double r_RANSAC_estimated = ground_truth_pose.
computeResidual(cMo_estimated_RANSAC);
std::cout << "Corresponding residual (1000 iterations): " << r_RANSAC_estimated << std::endl;
std::cout << "\ncMo estimated with RANSAC (" << ransac_iterations << " iterations) on noisy data:\n"
<< cMo_estimated_RANSAC_2 << std::endl;
std::cout << "Computation time: " << t_RANSAC << " ms" << std::endl;
double r_RANSAC_estimated_2 = ground_truth_pose.
computeResidual(cMo_estimated_RANSAC_2);
std::cout << "Corresponding residual (" << ransac_iterations << " iterations): " << r_RANSAC_estimated_2 << std::endl;
if(r_lagrange < r_dementhon) {
cMo_estimated = cMo_lagrange;
} else {
cMo_estimated = cMo_dementhon;
}
std::cout << "\ncMo estimated with only VVS on noisy data:\n" << cMo_estimated << std::endl;
std::cout << "Corresponding residual: " << r_estimated << std::endl;
#ifdef TEST_PARALLEL_RANSAC
std::cout << "\ncMo estimated with parallel RANSAC (1000 iterations) on noisy data:\n" << cMo_estimated_RANSAC_parallel << std::endl;
std::cout << "Computation time: " << t_RANSAC_parallel << " ms" << std::endl;
double r_RANSAC_estimated_parallel = ground_truth_pose.
computeResidual(cMo_estimated_RANSAC_parallel);
std::cout << "Corresponding residual (1000 iterations): " << r_RANSAC_estimated_parallel << std::endl;
std::cout << "\ncMo estimated with parallel RANSAC (" << ransac_iterations << " iterations) on noisy data:\n" << cMo_estimated_RANSAC_parallel2 << std::endl;
std::cout << "Computation time: " << t_RANSAC_parallel2 << " ms" << std::endl;
double r_RANSAC_estimated_parallel2 = ground_truth_pose.
computeResidual(cMo_estimated_RANSAC_parallel2);
std::cout << "Corresponding residual (" << ransac_iterations << " iterations): " << r_RANSAC_estimated_parallel2 << std::endl;
#endif
int nbInlierIndexOk = checkInlierIndex(vectorOfFoundInlierIndex, vectorOfOutlierFlags);
int nbTrueInlierIndex = (int) std::count(vectorOfOutlierFlags.begin(), vectorOfOutlierFlags.end(), false);
std::cout << "\nThere are " << nbInlierIndexOk << " true inliers found, " << vectorOfFoundInlierIndex.size()
<< " inliers returned and " << nbTrueInlierIndex << " true inliers." << std::endl;
std::vector<vpPoint> vectorOfFoundInlierPoints = pose_ransac.
getRansacInliers();
if(vectorOfFoundInlierPoints.size() != vectorOfFoundInlierIndex.size()) {
std::cerr << "The number of inlier index is different with the number of inlier points !" << std::endl;
return false;
}
if (!checkInlierPoints(vectorOfFoundInlierPoints, vectorOfFoundInlierIndex, bunnyModelPoints_noisy)) {
return false;
}
std::cout << "\nCheck for RANSAC iterations: " << ransac_iterations << std::endl;
nbInlierIndexOk = checkInlierIndex(vectorOfFoundInlierIndex_2, vectorOfOutlierFlags);
std::cout << "There are " << nbInlierIndexOk << " true inliers found, " << vectorOfFoundInlierIndex_2.size()
<< " inliers returned and " << nbTrueInlierIndex << " true inliers." << std::endl;
std::vector<vpPoint> vectorOfFoundInlierPoints_2 = pose_ransac2.
getRansacInliers();
if(vectorOfFoundInlierPoints_2.size() != vectorOfFoundInlierIndex_2.size()) {
std::cerr << "The number of inlier index is different with the number of inlier points !" << std::endl;
return false;
}
if (!checkInlierPoints(vectorOfFoundInlierPoints_2, vectorOfFoundInlierIndex_2, bunnyModelPoints_noisy)) {
return false;
}
#ifdef TEST_PARALLEL_RANSAC
std::cout << "\nCheck for parallel RANSAC (1000 iterations)" << std::endl;
std::vector<unsigned int> vectorOfFoundInlierIndex_parallel = pose_ransac_parallel.
getRansacInlierIndex();
nbInlierIndexOk = checkInlierIndex(vectorOfFoundInlierIndex_parallel, vectorOfOutlierFlags);
std::cout << "There are " << nbInlierIndexOk << " true inliers found, " << vectorOfFoundInlierIndex_parallel.size()
<< " inliers returned and " << nbTrueInlierIndex << " true inliers." << std::endl;
std::vector<vpPoint> vectorOfFoundInlierPoints_parallel = pose_ransac_parallel.
getRansacInliers();
if(vectorOfFoundInlierPoints_parallel.size() != vectorOfFoundInlierIndex_parallel.size()) {
std::cerr << "The number of inlier index is different with the number of inlier points !" << std::endl;
return false;
}
if (!checkInlierPoints(vectorOfFoundInlierPoints_parallel, vectorOfFoundInlierIndex_parallel, bunnyModelPoints_noisy)) {
return false;
}
std::cout << "\nCheck for parallel RANSAC (" << ransac_iterations << " iterations)" << std::endl;
std::vector<unsigned int> vectorOfFoundInlierIndex_parallel2 = pose_ransac_parallel2.
getRansacInlierIndex();
nbInlierIndexOk = checkInlierIndex(vectorOfFoundInlierIndex_parallel2, vectorOfOutlierFlags);
std::cout << "There are " << nbInlierIndexOk << " true inliers found, " << vectorOfFoundInlierIndex_parallel2.size()
<< " inliers returned and " << nbTrueInlierIndex << " true inliers." << std::endl;
std::vector<vpPoint> vectorOfFoundInlierPoints_parallel2 = pose_ransac_parallel2.
getRansacInliers();
if(vectorOfFoundInlierPoints_parallel2.size() != vectorOfFoundInlierIndex_parallel2.size()) {
std::cerr << "The number of inlier index is different with the number of inlier points !" << std::endl;
return false;
}
if (!checkInlierPoints(vectorOfFoundInlierPoints_parallel2, vectorOfFoundInlierIndex_parallel2, bunnyModelPoints_noisy)) {
return false;
}
#endif
if(r_RANSAC_estimated > threshold ) {
std::cerr << "The pose estimated with the RANSAC method is badly estimated!" << std::endl;
std::cerr << "r_RANSAC_estimated=" << r_RANSAC_estimated << std::endl;
std::cerr << "threshold=" << threshold << std::endl;
return false;
} else {
#ifdef TEST_PARALLEL_RANSAC
if (r_RANSAC_estimated_parallel > threshold) {
std::cerr << "The pose estimated with the parallel RANSAC method is badly estimated!" << std::endl;
std::cerr << "r_RANSAC_estimated_parallel=" << r_RANSAC_estimated_parallel << std::endl;
std::cerr << "threshold=" << threshold << std::endl;
return false;
}
#endif
std::cout << "The pose estimated with the RANSAC method is well estimated!" << std::endl;
}
return true;
}
int main() {
int sample_sizes[] = {2, 3, 4, 5, 6, 7, 8};
double epsilon[] = {0.05, 0.1, 0.2, 0.25, 0.3, 0.4, 0.5};
std::cout << " ";
for (int cpt2 = 0; cpt2 < 7; cpt2++) {
std::cout << std::setfill(' ') << std::setw(5) << epsilon[cpt2] << " ";
}
std::cout << std::endl;
std::cout << std::setfill(' ') << std::setw(7) << "+";
for (int cpt2 = 0; cpt2 < 6; cpt2++) {
std::cout << std::setw(7) << "-------";
}
std::cout << std::endl;
for (int cpt1 = 0; cpt1 < 7; cpt1++) {
std::cout << std::setfill(' ') << std::setw(6) << sample_sizes[cpt1] << "|";
for (int cpt2 = 0; cpt2 < 7; cpt2++) {
std::cout << std::setfill(' ') << std::setw(6) << ransac_iters;
}
std::cout << std::endl;
}
std::cout << std::endl;
try {
size_t model_sizes[] = {10, 20, 50, 100, 200, 500, 1000, 0, 0};
bool duplicates[] = {false, false, false, false, false, false, false, false, true};
bool degenerates[] = {false, false, false, false, false, false, true, true, true};
int nb = 9;
std::vector<vpPoint> bunnyModelPoints, bunnyModelPoints_noisy_original;
readBunnyModelPoints(bunnyModelPoints, bunnyModelPoints_noisy_original);
for (int cpt = 0; cpt < nb; cpt++) {
std::cout << "\n\n====================================================================" << std::endl;
if (model_sizes[cpt] == 0) {
std::cout << "Test on " << bunnyModelPoints_noisy_original.size() << " model points." << std::endl;
} else {
std::cout << "Test on " << model_sizes[cpt] << " model points." << std::endl;
}
std::cout << "Test duplicate: " << duplicates[cpt] << " ; Test degenerate: " << degenerates[cpt] << std::endl;
if ( !testRansac(bunnyModelPoints, bunnyModelPoints_noisy_original, model_sizes[cpt], duplicates[cpt], degenerates[cpt]) ) {
return EXIT_FAILURE;
}
}
std::cout << "\n\ntestPoseRansac2 is ok!" << std::endl;
return EXIT_SUCCESS;
}
std::cout << "Catch an exception: " << e << std::endl;
return EXIT_FAILURE;
}
}
1.8.6 
