Visual Servoing Platform  version 3.3.0 under development (2020-02-17)
testPoseRansac.cpp

Compute the pose of a 3D object using the Ransac method.

/****************************************************************************
*
* ViSP, open source Visual Servoing Platform software.
* Copyright (C) 2005 - 2019 by Inria. All rights reserved.
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* it under the terms of the GNU General Public License as published by
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* See http://visp.inria.fr for more information.
*
* This software was developed at:
* Inria Rennes - Bretagne Atlantique
* Campus Universitaire de Beaulieu
* 35042 Rennes Cedex
* France
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* Inria at visp@inria.fr
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* WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE.
*
* Description:
* Compute the pose of a 3D object using the Dementhon method. Assuming that
* the correspondance between 2D points and 3D points is not done, we use
* the RANSAC algorithm to achieve this task
*
* Authors:
* Aurelien Yol
*
*****************************************************************************/
#include <visp3/core/vpHomogeneousMatrix.h>
#include <visp3/core/vpMath.h>
#include <visp3/core/vpPoint.h>
#include <visp3/vision/vpPose.h>
#include <stdio.h>
#include <stdlib.h>
#define L 0.1
int main()
{
try {
std::cout << "Pose computation with matched points" << std::endl;
std::vector<vpPoint> P; // Point to be tracked
P.push_back(vpPoint(-L, -L, 0));
P.push_back(vpPoint(L, -L, 0));
P.push_back(vpPoint(L, L, 0));
P.push_back(vpPoint(-L, L, 0));
double L2 = L * 3.0;
P.push_back(vpPoint(0, -L2, 0));
P.push_back(vpPoint(L2, 0, 0));
P.push_back(vpPoint(0, L2, 0));
P.push_back(vpPoint(-L2, 0, 0));
vpHomogeneousMatrix cMo_ref(0, 0.2, 1, 0, 0, 0);
for (size_t i = 0; i < P.size(); i++) {
P[i].project(cMo_ref);
P[i].print();
std::cout << std::endl;
}
// Introduce an error
double error = 0.01;
P[3].set_y(P[3].get_y() + 2 * error);
P[6].set_x(P[6].get_x() + error);
vpPose pose;
for (size_t i = 0; i < P.size(); i++)
pose.addPoint(P[i]);
unsigned int nbInlierToReachConsensus = (unsigned int)(75.0 * (double)(P.size()) / 100.0);
double threshold = 0.001;
pose.setRansacNbInliersToReachConsensus(nbInlierToReachConsensus);
pose.setRansacThreshold(threshold);
// vpPose::ransac(lp,lP, 5, 1e-6, ninliers, lPi, cMo) ;
std::vector<vpPoint> inliers = pose.getRansacInliers();
std::cout << "Inliers: " << std::endl;
for (unsigned int i = 0; i < inliers.size(); i++) {
inliers[i].print();
std::cout << std::endl;
}
vpPoseVector pose_ref = vpPoseVector(cMo_ref);
vpPoseVector pose_est = vpPoseVector(cMo);
std::cout << std::endl;
std::cout << "reference cMo :\n" << pose_ref.t() << std::endl << std::endl;
std::cout << "estimated cMo :\n" << pose_est.t() << std::endl << std::endl;
int test_fail = 0;
for (unsigned int i = 0; i < 6; i++) {
if (std::fabs(pose_ref[i] - pose_est[i]) > 0.001)
test_fail = 1;
}
std::cout << "Pose is " << (test_fail ? "badly" : "well") << " estimated" << std::endl;
return test_fail;
} catch (const vpException &e) {
std::cout << "Catch an exception: " << e << std::endl;
return 1;
}
}