来源OpenCV 3.2.0-dev
http://docs.opencv.org/master/de/dfd/tutorial_sfm_import_reconstruction.html
输入重建
在本教程中,您将学习如何从一个给定的文件导入重建获得与打包机[1]:
下图显示了一个从洛杉矶重建 圣家堂 (BCN)使用数据集[2]。
#include
#include
#include
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
<< " 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
importReconstruction(argv[1], Rs, Ts, Ks, points3d,SFM_IO_BUNDLER);
viz::Viz3d window("Coordinate Frame");
window.setWindowSize(Size(500,500));
window.setWindowPosition(Point(150,150));
window.setBackgroundColor(); // black by default
vector
for (int i = 0; i < points3d.size(); ++i){
point_cloud.push_back(Vec3f(points3d[i]));
}
vector
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;
}
The following picture shows a reconstruction from la Sagrada Familia (BCN) using dataset [2].
[1] http://www.cs.cornell.edu/~snavely/bundler
[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