title: PointCloud from array of disparity map
body: <p>I have to reconstruction a 3d object from a set of image. Suppose i have already done the camera calibration for all the images (form example 10 images, all of them display the subject in different angles). I create an array of disparity map (for example the first one with image 1 and 2 the second one with image 2 and 3 and so on), after that i have to create a point cloud of all disparities map how can i do that? below is show the code i use to process only 2 image.</p>
  
  <pre><code>
  stereo = cv2.StereoSGBM_create(minDisparity= min_disp,
      numDisparities = num_disp,
      blockSize = 5,
      uniquenessRatio = 5,
      speckleWindowSize = 5,
      speckleRange = 5,
      disp12MaxDiff = 1,
      P1 = 8*3*win_size**2,#8*3*win_size**2,
      P2 =32*3*win_size**2) #32*3*win_size**2)
  #Compute disparity map
  print ("\nComputing the disparity  map...")
  disparity_map = stereo.compute(img_1_downsampled, img_2_downsampled)
  
  Q = np.float32([[1,0,0,-w/2.0],
                  [0,-1,0,h/2.0],
                  [0,0,0,-focal_length],
                  [0,0,1,0]])
  
  points_3D = cv2.reprojectImageTo3D(disparity_map, Q)
  </code></pre>