title: Generating 3D (x,y,z) Point Clouds from Two 2D Stereo Images
body: <p>I've been trying to read through the Stackoverflow questions for generating point clouds (x,y,z) coordinates from a left and right stereo image pair. </p>
  
  <p>I haven't come to any definite solution, and I'm asking the community here for some help.</p>
  
  <p><strong><em>Problem statement:</em></strong> <strong><em>Given two stereo images, generate 3D (x,y,z) cartesian coordinate point clouds from those and do so in a way that lends itself to completing this point-cloud generation in a way that could work over a large set (thousands) of pairs of stereo images</em></strong></p>
  
  <p>My programming language experience lends itself to MATLAB, but I've dabbled in Python, and C++ is limited, but I may be able to work in that as well.</p>
  
  <p><strong>Speed is a factor here, so the the idea is to find a quick method of successively going through these pairs and generating the point cloud.</strong></p>
  
  <p>NOTE: I am not asking for the BEST as to avoid comparative solutions, I'm just asking for solutions. </p>
  
  <p>Thank you very much!</p>
  
  <p>Edit: After being recommended to utilize the Stereo Block Matching implementation in OpenCV, I may steer away from this method, as there is a wide variation in regards to texture of the topographical pictures that I'm dealing with.</p>