  In this report we present the work performed in order to build a dataset for
benchmarking vision-based localization at intersections, i.e., a set of stereo
video sequences taken from a road vehicle that is approaching an intersection,
altogether with a reliable measure of the observer position. This report is
meant to complement our paper "Vision-Based Localization at Intersections using
Digital Maps" submitted to ICRA2019. It complements the paper because the paper
uses the dataset, but it had no space for describing the work done to obtain
it. Moreover, the dataset is of interest for all those tackling the task of
online localization at intersections for road vehicles, e.g., for a
quantitative comparison with the proposal in our submitted paper, and it is
therefore appropriate to put the dataset description in a separate report. We
considered all datasets from road vehicles that we could find as for the end of
August 2018. After our evaluation, we kept only sub-sequences from the KITTI
dataset. In the future we will increase the collection of sequences with data
from our vehicle.
