In this chapter, we explored a way of reconstructing a scene in 3D—by inferring the geometrical features of 2D images taken by the same camera. We wrote a script to calibrate a camera, and you learned about fundamental and essential matrices. We used this knowledge to perform triangulation. We then went on to visualize the real-world geometry of the scene in a 3D point cloud. Using simple 3D scatterplots in matplotlib, we found a way to convince ourselves that our calculations were accurate and practical.
Going forward from here, it will be possible to store the triangulated 3D points in a file that can be parsed by the Point Cloud Library, or to repeat the procedure for different image pairs so that we can generate a denser and more accurate reconstruction. Although we have covered a lot in this chapter, there is a lot more left to do. Typically, when talking about a structure-from-motion pipeline, we include two additional steps that we have not talked about so far: bundle adjustment...
