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.

翻译：基于图像的定位是一个经典的计算机视觉挑战，已有多个知名数据集。通常，数据集包含捕捉场景模型的视觉三维数据库以及需要确定三维姿态的查询图像。查询图像通常由与采集三维数据库的成像硬件不同的相机获取，因此难以获得查询图像与三维数据库之间的精确真实姿态。随着视觉定位算法精度的不断提升，精确的真实姿态变得愈发重要。本文提出TBPos，一种用于图像定位的新型大规模视觉数据集，该数据集为查询图像提供了完全精确的真实姿态：数据库图像和查询图像均源自同一激光扫描仪数据。在论文的实验部分，通过基于图像的定位流程对所提出的数据集进行了评估。