Code

#include <iostream> using namespace std; using namespace cv; using namespace cv::sfm; static void help() { cout << "\n---------------------------------------------------------------------------\n" << " This program shows how to import a reconstructed scene in the \n" << " OpenCV Structure From Motion (SFM) module.\n" << " Usage:\n" << " example_sfm_import_reconstruction <path_to_file>\n" << " where: file_path is the absolute path file into your system which contains\n" << " the reconstructed scene. \n" << "---------------------------------------------------------------------------\n\n" << endl; } int main(int argc,char* argv[]) { if ( argc != 2 ) { help(); exit(0); } vector<Mat> Rs, Ts, Ks, points3d; viz::Viz3d window("Coordinate Frame"); window.setWindowSize(Size(500,500)); window.setWindowPosition(Point(150,150)); window.setBackgroundColor(); // black by default vector<Vec3d> point_cloud; for (int i = 0; i < points3d.size(); ++i){ point_cloud.push_back(Vec3f(points3d[i])); } vector<Affine3d> path; for (size_t i = 0; i < Rs.size(); ++i) path.push_back(Affine3d(Rs[i], Ts[i])); viz::WCloud cloud_widget(point_cloud, viz::Color::green()); viz::WTrajectory trajectory(path, viz::WTrajectory::FRAMES, 0.5); viz::WTrajectoryFrustums frustums(path,Vec2f(0.889484, 0.523599), 0.5, viz::Color::yellow()); window.showWidget("point_cloud", cloud_widget); window.showWidget("cameras", trajectory); window.showWidget("frustums", frustums); cout << endl << "Press 'q' to close each windows ... " << endl; window.spin(); return 0; }

Results

The following picture shows a reconstruction from la Sagrada Familia (BCN) using dataset [2].

[2] Penate Sanchez, A. and Moreno-Noguer, F. and Andrade Cetto, J. and Fleuret, F. (2014). LETHA: Learning from High Quality Inputs for 3D Pose Estimation in Low Quality Images. Proceedings of the International Conference on 3D vision (3DV). URL