In this video, we discuss the problem of acquiring a 3D model of an object, using only simple cameras. We discuss this in the context of the well known "Simultaneous Localisation and Mapping" (SLAM) problem.
In this video, we discuss how the SLAM algorithm is implemented in a simple form. We present the problem is probabilistic terms, where we aim to find the most likely 3D map and camera poses given our observed data. We then explore how Bayes rules can be applied to form an efficient iterative solution.