title: How to calculate 3D object points from 2D image points using stereo triangulation?
body: <p>I have a stereo-calibrated camera system calibrated using OpenCV and Python.  I am trying to use it to calculate the 3D position of image points.  I have collected the intrinsic and extrinsic matrices, as well as, the E, F, R, and T matrices.  I am confused on how to triangulate the 2D image points to 3D object points.  I have read the following post but I am confused on the process (<a href="https://stackoverflow.com/questions/10502790/in-a-calibrated-stereo-vision-rig-how-does-one-obtain-the-camera-matrices-nee">In a calibrated stereo-vision rig, how does one obtain the &quot;camera matrices&quot; needed for implementing a 3D triangulation algorithm?</a>).  Can some one explain how to get from 2D to 3D?  From reading around, I feel that the fundamental matrix (F) is important, but I haven't found a clear way to link it to the projection matrix (P).  Can someone please walk me through this process? </p>
  
  <p>I appreciate any help I can get.</p>