匯入重建

目標

在本教程中，您將學習如何從使用 Bundler [1] 獲取的給定檔案中匯入重建。

• 載入包含一組相機和 3D 點的檔案。
• 使用 Viz 顯示獲得的結果。

程式碼

#include <opencv2/sfm.hpp>
#include <opencv2/viz.hpp>
 
#include <iostream>
 
using namespace std;
using namespace cv;
using namespace cv::sfm;
 
static void help() {
cout
<< "\n---------------------------------------------------------------------------\n"
<< " 此程式演示如何在 OpenCV 運動結構 (SFM) 模組中匯入重建場景。\n"
<< " OpenCV 運動結構 (SFM) 模組。\n"
<< " example_sfm_scene_reconstruction <檔案路徑> <f> <cx> <cy>\n"
<< " example_sfm_import_reconstruction <path_to_file>\n"
<< " 其中：file_path 是系統中包含重建場景的絕對路徑檔案。\n"
<< " 重建的場景。\n"
<< "---------------------------------------------------------------------------\n\n"
<< endl;
}
 
 
int main(int argc, char* argv[])
{
 
  if ( argc != 2 ) {
help();
exit(0);
  }
 
 
vector<Mat> Rs, Ts, Ks, points3d;
importReconstruction(argv[1], Rs, Ts, Ks, points3d, SFM_IO_BUNDLER);
 
 
 
  viz::Viz3d window("座標框架");
window.setWindowSize(Size(500,500));
window.setWindowPosition(Point(150,150));
window.setBackgroundColor(); // 預設為黑色
 
 
 
vector<Vec3d> point_cloud;
  for (int i = 0; i < points3d.size(); ++i){
point_cloud.push_back(Vec3f(points3d[i]));
  }
 
 
 
for (size_t i = 0; i < Rs_est.size(); ++i)
  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 << "按 'q' 關閉每個視窗 ... " << endl;
 
cv::Affine3
 
  return 0;
}

結果

下圖顯示了使用資料集 [2] 從聖家族教堂 (BCN) 的重建。

[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