/****************************************************************************** * Author: Laurent Kneip * * Contact: kneip.laurent@gmail.com * * License: Copyright (c) 2013 Laurent Kneip, ANU. All rights reserved. * * * * Redistribution and use in source and binary forms, with or without * * modification, are permitted provided that the following conditions * * are met: * * * Redistributions of source code must retain the above copyright * * notice, this list of conditions and the following disclaimer. * * * Redistributions in binary form must reproduce the above copyright * * notice, this list of conditions and the following disclaimer in the * * documentation and/or other materials provided with the distribution. * * * Neither the name of ANU nor the names of its contributors may be * * used to endorse or promote products derived from this software without * * specific prior written permission. * * * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"* * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE * * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE * * ARE DISCLAIMED. IN NO EVENT SHALL ANU OR THE CONTRIBUTORS BE LIABLE * * FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL * * DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR * * SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER * * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT * * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY * * OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF * * SUCH DAMAGE. * ******************************************************************************/ #include #include #include #include #include #include #include #include #include #include #include #include "random_generators.hpp" #include "experiment_helpers.hpp" #include "time_measurement.hpp" using namespace std; using namespace Eigen; using namespace opengv; int main( int argc, char** argv ) { // initialize random seed initializeRandomSeed(); //set experiment parameters double noise = 0.5; double outlierFraction = 0.1; size_t numberPoints = 100; //generate a random pose for viewpoint 1 translation_t position1 = Eigen::Vector3d::Zero(); rotation_t rotation1 = Eigen::Matrix3d::Identity(); //generate a random pose for viewpoint 2 translation_t position2 = generateRandomDirectionTranslation(0.1); rotation_t rotation2 = generateRandomRotation(0.5); //create a fake central camera translations_t camOffsets; rotations_t camRotations; generateCentralCameraSystem( camOffsets, camRotations ); //derive correspondences based on random point-cloud bearingVectors_t bearingVectors1; bearingVectors_t bearingVectors2; std::vector camCorrespondences1; //unused in the central case std::vector camCorrespondences2; //unused in the central case Eigen::MatrixXd gt(3,numberPoints); generateRandom2D2DCorrespondences( position1, rotation1, position2, rotation2, camOffsets, camRotations, numberPoints, noise, outlierFraction, bearingVectors1, bearingVectors2, camCorrespondences1, camCorrespondences2, gt ); //Extract the relative pose translation_t position; rotation_t rotation; extractRelativePose( position1, position2, rotation1, rotation2, position, rotation ); //print experiment characteristics printExperimentCharacteristics( position, rotation, noise, outlierFraction ); //create a central relative adapter relative_pose::CentralRelativeAdapter adapter( bearingVectors1, bearingVectors2, rotation); //Create an EigensolverSacProblem and Ransac //The number of samples can be configured sac::Ransac< sac_problems::relative_pose::EigensolverSacProblem> ransac; std::shared_ptr< sac_problems::relative_pose::EigensolverSacProblem> eigenproblem_ptr( new sac_problems::relative_pose::EigensolverSacProblem(adapter,10)); ransac.sac_model_ = eigenproblem_ptr; ransac.threshold_ = 1.0; ransac.max_iterations_ = 100; //Run the experiment struct timeval tic; struct timeval toc; gettimeofday( &tic, 0 ); ransac.computeModel(); gettimeofday( &toc, 0 ); double ransac_time = TIMETODOUBLE(timeval_minus(toc,tic)); //do final polishing of the model over all inliers sac_problems::relative_pose::EigensolverSacProblem::model_t optimizedModel; eigenproblem_ptr->optimizeModelCoefficients( ransac.inliers_, ransac.model_coefficients_, optimizedModel); //print the results std::cout << "the ransac results is: " << std::endl; std::cout << ransac.model_coefficients_.rotation << std::endl << std::endl; std::cout << "Ransac needed " << ransac.iterations_ << " iterations and "; std::cout << ransac_time << " seconds" << std::endl << std::endl; std::cout << "the number of inliers is: " << ransac.inliers_.size(); std::cout << std::endl << std::endl; std::cout << "the found inliers are: " << std::endl; for(size_t i = 0; i < ransac.inliers_.size(); i++) std::cout << ransac.inliers_[i] << " "; std::cout << std::endl << std::endl; std::cout << "the optimized result is: " << std::endl; std::cout << optimizedModel.rotation << std::endl; // Create Lmeds sac::Lmeds lmeds; lmeds.sac_model_ = eigenproblem_ptr; lmeds.threshold_ = 1.0; lmeds.max_iterations_ = 50; //Run the experiment gettimeofday( &tic, 0 ); lmeds.computeModel(); gettimeofday( &toc, 0 ); double lmeds_time = TIMETODOUBLE(timeval_minus(toc,tic)); //print the results std::cout << "the lmeds results is: " << std::endl; std::cout << lmeds.model_coefficients_.rotation << std::endl << std::endl; std::cout << "lmeds needed " << lmeds.iterations_ << " iterations and "; std::cout << lmeds_time << " seconds" << std::endl << std::endl; std::cout << "the number of inliers is: " << lmeds.inliers_.size(); std::cout << std::endl << std::endl; std::cout << "the found inliers are: " << std::endl; for(size_t i = 0; i < lmeds.inliers_.size(); i++) std::cout << lmeds.inliers_[i] << " "; std::cout << std::endl << std::endl; }