Estimating Image-Matching Uncertainty for Robust Visual Place Recognition

Reliable uncertainty estimation is key to avoid catastrophic failures in visual place recognition pipelines due to perceptual aliasing. This work compares three main categories of uncertainty estimation methods and proposes a simple baseline that considers the spatial locations of the reference images.