  Image based localization is a classical computer vision challenge, with
several well-known datasets. Generally, datasets consist of a visual 3D
database that captures the modeled scenery, as well as query images whose 3D
pose is to be discovered. Usually the query images have been acquired with a
camera that differs from the imaging hardware used to collect the 3D database;
consequently, it is hard to acquire accurate ground truth poses between query
images and the 3D database. As the accuracy of visual localization algorithms
constantly improves, precise ground truth becomes increasingly important. This
paper proposes TBPos, a novel large-scale visual dataset for image based
positioning, which provides query images with fully accurate ground truth
poses: both the database images and the query images have been derived from the
same laser scanner data. In the experimental part of the paper, the proposed
dataset is evaluated by means of an image-based localization pipeline.
