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Publikation Open urban and forest datasets from a high-performance mobile mapping backpack. A contribution for advancing the creation of digital city twins(International Society of Photogrammetry and Remote Sensing, 2021) Blaser, Stefan; Meyer, Jonas; Nebiker, StephanWith this contribution, we describe and publish two high-quality street-level datasets, captured with a portable high-performance Mobile Mapping System (MMS). The datasets will be freely available for scientific use. Both datasets, from a city centre and a forest represent area-wide street-level reality captures which can be used e.g. for establishing cloud-based frameworks for infrastructure management as well as for smart city and forestry applications. The quality of these data sets has been thoroughly evaluated and demonstrated. For example, georeferencing accuracies in the centimetre range using these datasets in combination with image-based georeferencing have been achieved. Both high-quality multi sensor system street-level datasets are suitable for evaluating and improving methods for multiple tasks related to high-precision 3D reality capture and the creation of digital twins. Potential applications range from localization and georeferencing, dense image matching and 3D reconstruction to combined methods such as simultaneous localization and mapping and structure-from-motion as well as classification and scene interpretation. Our dataset is available online at: https://www.fhnw.ch/habg/bimage-datasets04B - Beitrag KonferenzschriftPublikation Development of a portable high performance mobile mapping system using the robot operating system(Copernicus, 2018) Blaser, Stefan; Cavegn, Stefan; Nebiker, StephanThe rapid progression in digitalization in the construction industry and in facility management creates an enormous demand for the efficient and accurate reality capturing of indoor spaces. Cloud-based services based on georeferenced metric 3D imagery are already extensively used for infrastructure management in outdoor environments. The goal of our research is to enable such services for indoor applications as well. For this purpose, we designed a portable mobile mapping research platform with a strong focus on acquiring accurate 3D imagery. Our system consists of a multi-head panorama camera in combination with two multi-profile LiDAR scanners and a MEMS-based industrial grade IMU for LiDAR-based online and offline SLAM. Our modular implementation based on the Robot Operating System enables rapid adaptations of the sensor configuration and the acquisition software. The developed workflow provides for completely GNSS-independent data acquisition and camera pose estimation using LiDAR-based SLAM. Furthermore, we apply a novel image-based georeferencing approach for further improving camera poses. First performance evaluations show an improvement from LiDAR-based SLAM to image-based georeferencing by an order of magnitude: from 10–13 cm to 1.3–1.8 cm in absolute 3D point accuracy and from 8–12 cm to sub-centimeter in relative 3D point accuracy.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Centimetre-accuracy in forests and urban canyons. Combining a high-performance image-based mobile mapping backpack with new georeferencing methods(Copernicus, 2020) Blaser, S.; Meyer, Jonas; Nebiker, Stephan; Fricker, L.; Weber, D.Advances in digitalization technologies lead to rapid and massive changes in infrastructure management. New collaborative processes and workflows require detailed, accurate and up-to-date 3D geodata. Image-based web services with 3D measurement functionality, for example, transfer dangerous and costly inspection and measurement tasks from the field to the office workplace. In this contribution, we introduced an image-based backpack mobile mapping system and new georeferencing methods for capture previously inaccessible outdoor locations. We carried out large-scale performance investigations at two different test sites located in a city centre and in a forest area. We compared the performance of direct, SLAM-based and image-based georeferencing under demanding real-world conditions. Both test sites include areas with restricted GNSS reception, poor illumination, and uniform or ambiguous geometry, which create major challenges for reliable and accurate georeferencing. In our comparison of georeferencing methods, image-based georeferencing improved the median precision of coordinate measurement over direct georeferencing by a factor of 10–15 to 3 mm. Image-based georeferencing also showed a superior performance in terms of absolute accuracies with results in the range from 4.3 cm to 13.2 cm. Our investigations showed a great potential for complementing 3D image-based geospatial web-services of cities as well as for creating such web services for forest applications. In addition, such accurately georeferenced 3D imagery has an enormous potential for future visual localization and augmented reality applications.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Portable image-based high performance mobile mapping system in underground environments. System configuration and performance evalutation.(Copernicus, 2019) Blaser, S.; Nebiker, Stephan; Wisler, D.The progression in urbanization increases the need for different types of underground infrastructure. Consequently, infrastructure and life cycle management are rapidly gaining in importance. Mobile reality capturing systems and cloud-based services exploiting georeferenced metric 3D imagery are already extensively used for infrastructure management in outdoor environments. These services minimise dangerous and expensive field visits or measurement campaigns. In this paper, we introduce the BIMAGE Backpack, a portable image-based mobile mapping system for 3D data acquisition in indoor environments. The system consists of a multi-head panorama camera, two multi-profile laser scanners and an inertial measurement unit. With this system, we carried out underground measurement campaigns in the Hagerbach Test Gallery, located in Flums Hochwiese, Switzerland. For our performance evaluations in two different tunnel sections, we employed LiDAR SLAM as well as advanced image-based georeferencing. The obtained absolute accuracies were in the range from 6.2 to 7.4 cm. The relative accuracy, which for many applications is even more important, was in the range of 2–6 mm. These figures demonstrate an accuracy improvement of the subsequent image-based georeferencing over LiDAR SLAM by about an order of magnitude. The investigations show the application potential of image-based portable mobile mapping systems for infrastructure inventory and management in large underground facilities.01A - Beitrag in wissenschaftlicher Zeitschrift