PTAM algorithm analysis and tutorial - Omer Segal Msc project

In this work, we have provided a set of tools for adopting a known implementation of a computer vision based simultaneous localization and mapping (SLAM) algorithm for pose estimation. These tools are meant to enable to fully understand the given implementation, its assumptions and abilities, and to understand how to modify it for a future use.

First, we created a detailed documentation of the algorithms implementation along with flow charts to clarify the high level of the code. Second, we gave a theoretical review that links the implementation to relevant computer vision terms for a better understanding of each step in the algorithm. Third, we gathered a guide for installing and debugging the code environment for creating the ideal workspace.

Alongside these tools, we added relevant recommendations and insights that can be useful for modifying the implementation, as well as figures from our experiments that are given as visualization aids.