  Localization is an essential capability for mobile robots. A rapidly growing
field of research in this area is Visual Place Recognition (VPR), which is the
ability to recognize previously seen places in the world based solely on
images. This present work is the first tutorial paper on visual place
recognition. It unifies the terminology of VPR and complements prior research
in two important directions: 1) It provides a systematic introduction for
newcomers to the field, covering topics such as the formulation of the VPR
problem, a general-purpose algorithmic pipeline, an evaluation methodology for
VPR approaches, and the major challenges for VPR and how they may be addressed.
2) As a contribution for researchers acquainted with the VPR problem, it
examines the intricacies of different VPR problem types regarding input, data
processing, and output. The tutorial also discusses the subtleties behind the
evaluation of VPR algorithms, e.g., the evaluation of a VPR system that has to
find all matching database images per query, as opposed to just a single match.
Practical code examples in Python illustrate to prospective practitioners and
researchers how VPR is implemented and evaluated.
