Visual localization is an important component of many location-based systems such as self-driving cars, autonomous robots, or augmented, mixed, and virtual reality. The goal is to estimate the accurate position and orientation of a camera from images. In more detail, correspondences between a representation of the environment (map) and a query image are utilized to estimate the camera pose in 6 degrees of freedom (DOF).
In this presentation, I will given an overview of popular techniques for visual localization and by providing concrete examples, I will go deeper into approaches that use global representations for image retrieval and local features for accurate pose computation. I will also introduce our open source platform named kapture, that is designed to facilitate future research in this and related domains.