A Systematic Comparison of Direct and Image-Based Georeferencing in Challenging Urban Areas

Abstract

ABSTRACT:Image-based mobile mapping systems enable an efficient acquisition of georeferenced image sequences, which can be used for geodata capture in subsequent steps. In order to provide accurate measurements in a given reference frame while e.g. aiming at high fidelity 3D urban models, high quality georeferencing of the captured multi-view image sequences is required. Moreover, sub-pixel accurate orientations of these highly redundant image sequences are needed in order to optimally perform steps like dense multiimage matching as a prerequisite for 3D point cloud and mesh generation. While direct georeferencing of image-based mobile mapping data performs well in open areas, poor GNSS coverage in urban canyons aggravates fulfilling these high accuracy requirements, even with high-grade inertial navigation equipment. Hence, we conducted comprehensive investigations aiming at assessing the quality of directly georeferenced sensor orientations as well as the expected improvement by image-based georeferencing in a challenging urban environment. Our study repeatedly delivered mean trajectory deviations of up to 80 cm. By performing image-based georeferencing using bundle adjustment for a limited set of cameras and a limited number of ground control points, mean check point residuals could be lowered from approx. 40 cm to 4 cm. Furthermore, we showed that largely automated image-based georeferencing is capable of detecting and compensating discontinuities in directly georeferenced trajectories.

Precision of Visual Localization Using Dynamic Ground Control Points

“…Visual localization is a broad topic with many applications and lots of ongoing research. Three examples are (Wolcott, Eustice, 2014), (Cavegn et al, 2016) and (Cavegn et al, 2018). The authors investigate the use of information derived from images for georeferencing in environments, which are challenging for GNSS.…”

“…Although the camera is significantly cheaper than the LIDAR the obtained errors are in a similar order of magnitude. (Cavegn et al, 2016) deal with the challenge of georeferencing image sequences. As in urban canyons direct georeferencing is not suitable due to poor GNSS coverage, the authors add image-based georeferencing by using bundle adjustment.…”

“…Due to these reasons, researchers increasingly combine GNSS and INS sensors with image-based localization techniques. As an example, (Cavegn et al, 2016) shows the improvement of image-based georeferencing compared to direct georeferencing. The authors also demonstrate, that in challenging urban areas the uncertainty derived from only GNSS/INS can be too optimistic.…”

Accurate Visual Localization in Outdoor and Indoor Environments Exploiting 3d Image Spaces as Spatial Reference

“…This leads to a dataset of 307 images, whose poses we calculated in a bundle adjustment using some control points with Agisoft PhotoScan. These image sequences are described in detail by Cavegn et al (2016). As approximate pose, we used the values from the direct sensor orientations.…”

Co‐registration of panoramic mobile mapping images and oblique aerial images

“…In order to correct or compensate for this issue, various techniques have been used. For instance, surveyed ground control points (GCPs) (Cavegn et al., ) or digital maps (Levinson et al., ) have been introduced into the adjustment of MM data products. In any case, external references are required to either verify, or increase the accuracy of, the dataset.…”