Question

我有一些代码可以解决所有部分，直到使用cv :: stereoRectifyUncalibrated计算值。但是，我不知道从那里可以从那里获得3D点云。

我的代码适用于校准版本，它为我提供了Q矩阵，然后我使用reprojectImageTo3D和StereoBM来给我一个点云。

我想比较两种不同方法的结果，因为有时我无法校准相机。

Answer 1

http://blog.martinperis.com/2012/01/3d-reconstruction-with-opencv-and-point.html我认为这会有所帮助。它有一个代码，可以使用PCL将Disparity Image转换为Point cloud，并在3D查看器中显示。

由于您有Q，两个图像和其他相机参数（来自校准），您应该使用ReprojectTo3D来获取深度图。

使用StereoBM或stereoSGBM获取视差贴图，并使用该Disparit Map和Q获取深度图像。

StereoBM sbm;
sbm.state->SADWindowSize = 9;
sbm.state->numberOfDisparities = 112;
sbm.state->preFilterSize = 5;
sbm.state->preFilterCap = 61;
sbm.state->minDisparity = -39;
sbm.state->textureThreshold = 507;
sbm.state->uniquenessRatio = 0;
sbm.state->speckleWindowSize = 0;
sbm.state->speckleRange = 8;
sbm.state->disp12MaxDiff = 1;

sbm(g1, g2, disp); // g1 and g2 are two gray images
reprojectImageTo3D(disp, Image3D, Q, true, CV_32F);

该代码基本上将深度图转换为点云。

 pcl::PointCloud<pcl::PointXYZRGB>::Ptr point_cloud_ptr (new pcl::PointCloud<pcl::PointXYZRGB>);
 double px, py, pz;
 uchar pr, pg, pb;

 for (int i = 0; i < img_rgb.rows; i++)
 {
     uchar* rgb_ptr = img_rgb.ptr<uchar>(i);
     uchar* disp_ptr = img_disparity.ptr<uchar>(i);
     double* recons_ptr = recons3D.ptr<double>(i);
     for (int j = 0; j < img_rgb.cols; j++)
     {
         //Get 3D coordinates

          uchar d = disp_ptr[j];
          if ( d == 0 ) continue; //Discard bad pixels
          double pw = -1.0 * static_cast<double>(d) * Q32 + Q33; 
          px = static_cast<double>(j) + Q03;
          py = static_cast<double>(i) + Q13;
          pz = Q23;

          // Normalize the points
          px = px/pw;
          py = py/pw;
          pz = pz/pw;

          //Get RGB info
          pb = rgb_ptr[3*j];
          pg = rgb_ptr[3*j+1];
          pr = rgb_ptr[3*j+2];

          //Insert info into point cloud structure
          pcl::PointXYZRGB point;
          point.x = px;
          point.y = py;
          point.z = pz;
          uint32_t rgb = (static_cast<uint32_t>(pr) << 16 |
          static_cast<uint32_t>(pg) << 8 | static_cast<uint32_t>(pb));
          point.rgb = *reinterpret_cast<float*>(&rgb);
          point_cloud_ptr->points.push_back (point);
    }
}

point_cloud_ptr->width = (int) point_cloud_ptr->points.size();
point_cloud_ptr->height = 1;

//Create visualizer
boost::shared_ptr<pcl::visualization::PCLVisualizer> viewer;
viewer = createVisualizer( point_cloud_ptr );

OpenCV StereoRectify未校准到3D Point Cloud

1 个答案: