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.

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

“…On the other hand, post-processing approaches traditionally rely on GCPs, which are introduced into the adjustment (Cavegn et al, 2016;Hofmann and Brenner, 2016;Han and Lo, 2017;Molina et al, 2017). This proved to be accurate but is labour intensive and thus costly.…”

“…In order to correct or compensate for this issue, various techniques have been used. For instance, surveyed ground control points (GCPs) (Cavegn et al, 2016) or digital maps (Levinson et al, 2007) 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.…”

Fully Automatic Feature-Based Registration of Mobile Mapping and Aerial Nadir Images for Enabling the Adjustment of Mobile Platform Locations in GNSS-Denied Urban Environments

“…These approaches are all designed to work in a real-time fashion to reduce GNSS-induced localisation issues in difficult scenarios, but cannot reach decimetre-grade accuracy, since external reference information is missing. To retrieve highly accurate sensor orientations of MM platforms, many authors rely on surveyed Ground Control Points (GCPs) which can be integrated into an adjustment solution (Cavegn et al (2016), Han and Lo (2016), Hofmann and Brenner (2016)). Using GCPs is, however, labour-intensive, difficult to automate, and therefore relatively expensive compared to the approach presented in this paper.…”

Position estimation of mobile mapping imaging sensors using aerial imagery

“…To achieve the highest accuracy possible, ground control points are used. Analogously, this technique can also be employed for mobile mapping data (Cavegn et al, 2016). Depending on the quality, the distribution, and the number of ground control points, sub-decimetre accuracy in GNSS-denied areas can be achieved.…”

“…In order to correct or compensate for this issue, various techniques have been used. For instance, surveyed ground control points (GCPs) (Cavegn et al, 2016) or digital maps (Levinson and Thrun, 2007) 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.…”