Visual Servoing Platform  version 3.0.1
testPoseRansac.cpp

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

/****************************************************************************
*
* This file is part of the ViSP software.
*
* This software is free software; you can redistribute it and/or
* modify it under the terms of the GNU General Public License
* See the file LICENSE.txt at the root directory of this source
*
* For using ViSP with software that can not be combined with the GNU
*
*
* This software was developed at:
* Inria Rennes - Bretagne Atlantique
* Campus Universitaire de Beaulieu
* 35042 Rennes Cedex
* France
*
* Inria at visp@inria.fr
*
* This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE
* 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/vision/vpPose.h>
#include <visp3/core/vpPoint.h>
#include <visp3/core/vpMath.h>
#include <visp3/core/vpHomogeneousMatrix.h>
#include <stdlib.h>
#include <stdio.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++)
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(vpException &e) {
std::cout << "Catch an exception: " << e << std::endl;
return 1;
}
}