Nebiker, Stephan

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Stephan
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Nebiker, Stephan

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2010 - 2019302020 - 20216
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Autor:in: Nebiker, Stephan × Anfangsdatum: 2010 × Hochschule: Hochschule für Architektur, Bau und Geomatik ×

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  • Vorschaubild
    Publikation
    Outdoor mobile mapping and AI-based 3D object detection with low-cost RGB-D cameras. The use case of on-street parking statistics
    (MDPI, 05.08.2021) Nebiker, Stephan; Meyer, Jonas; Blaser, Stefan; Ammann, Manuela; Rhyner, Severin [in: Remote Sensing]
    A successful application of low-cost 3D cameras in combination with artificial intelligence (AI)-based 3D object detection algorithms to outdoor mobile mapping would offer great potential for numerous mapping, asset inventory, and change detection tasks in the context of smart cities. This paper presents a mobile mapping system mounted on an electric tricycle and a procedure for creating on-street parking statistics, which allow government agencies and policy makers to verify and adjust parking policies in different city districts. Our method combines georeferenced red-green-blue-depth (RGB-D) imagery from two low-cost 3D cameras with state-of-the-art 3D object detection algorithms for extracting and mapping parked vehicles. Our investigations demonstrate the suitability of the latest generation of low-cost 3D cameras for real-world outdoor applications with respect to supported ranges, depth measurement accuracy, and robustness under varying lighting conditions. In an evaluation of suitable algorithms for detecting vehicles in the noisy and often incomplete 3D point clouds from RGB-D cameras, the 3D object detection network PointRCNN, which extends region-based convolutional neural networks (R-CNNs) to 3D point clouds, clearly outperformed all other candidates. The results of a mapping mission with 313 parking spaces show that our method is capable of reliably detecting parked cars with a precision of 100% and a recall of 97%. It can be applied to unslotted and slotted parking and different parking types including parallel, perpendicular, and angle parking.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild
    Publikation
    Image-based reality-capturing and 3D modelling for the creation of VR cycling simulations
    (Copernicus, 17.06.2021) Wahbeh, Wissam; Ammann, Manuela; Nebiker, Stephan; van Eggermond, Michael; Erath, Alexander; Wahbeh, Wissam [in: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences]
    With this paper, we present a novel approach for efficiently creating reality-based, high-fidelity urban 3D models for interactive VR cycling simulations. The foundation of these 3D models is accurately georeferenced street-level imagery, which can be captured using vehicle-based or portable mapping platforms. Depending on the desired type of urban model, the street-level imagery is either used for semi-automatically texturing an existing city model or for automatically creating textured 3D meshes from multi-view reconstructions using commercial off-the-shelf software. The resulting textured urban 3D model is then integrated with a real-time traffic simulation solution to create a VR framework based on the Unity game engine. Subsequently, the resulting urban scenes and different planning scenarios can be explored on a physical cycling simulator using a VR helmet or viewed as a 360-degree or conventional video. In addition, the VR environment can be used for augmented reality applications, e.g., mobile augmented reality maps. We apply this framework to a case study in the city of Berne to illustrate design variants of new cycling infrastructure at a major traffic junction to collect feedback from practitioners about the potential for practical applications in planning processes.
    04B - Beitrag Konferenzschrift
  • Vorschaubild
    Publikation
    Image-based reality-capturing and 3D modelling for the creation of VR cycling simulations
    (Copernicus, 2021) Wahbeh, Wissam; Ammann, Manuela; Nebiker, Stephan; van Eggermond, Michael; Erath, Alexander [in: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences]
    With this paper, we present a novel approach for efficiently creating reality-based, high-fidelity urban 3D models for interactive VR cycling simulations. The foundation of these 3D models is accurately georeferenced street-level imagery, which can be captured using vehicle-based or portable mapping platforms. Depending on the desired type of urban model, the street-level imagery is either used for semi-automatically texturing an existing city model or for automatically creating textured 3D meshes from multi-view reconstructions using commercial off-the-shelf software. The resulting textured urban 3D model is then integrated with a real-time traffic simulation solution to create a VR framework based on the Unity game engine. Subsequently, the resulting urban scenes and different planning scenarios can be explored on a physical cycling simulator using a VR helmet or viewed as a 360-degree or conventional video. In addition, the VR environment can be used for augmented reality applications, e.g., mobile augmented reality maps. We apply this framework to a case study in the city of Berne to illustrate design variants of new cycling infrastructure at a major traffic junction to collect feedback from practitioners about the potential for practical applications in planning processes.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild
    Publikation
    Outdoor mobile mapping and AI-based 3D object detection with low-cost RGB-D cameras. The use case of on-street parking statistics
    (MDPI, 2021) Nebiker, Stephan; Meyer, Jonas; Blaser, Stefan; Ammann, Manuela; Rhyner, Severin Eric [in: Remote sensing]
    A successful application of low-cost 3D cameras in combination with artificial intelligence (AI)-based 3D object detection algorithms to outdoor mobile mapping would offer great potential for numerous mapping, asset inventory, and change detection tasks in the context of smart cities. This paper presents a mobile mapping system mounted on an electric tricycle and a procedure for creating on-street parking statistics, which allow government agencies and policy makers to verify and adjust parking policies in different city districts. Our method combines georeferenced red-green-blue-depth (RGB-D) imagery from two low-cost 3D cameras with state-of-the-art 3D object detection algorithms for extracting and mapping parked vehicles. Our investigations demonstrate the suitability of the latest generation of low-cost 3D cameras for real-world outdoor applications with respect to supported ranges, depth measurement accuracy, and robustness under varying lighting conditions. In an evaluation of suitable algorithms for detecting vehicles in the noisy and often incomplete 3D point clouds from RGB-D cameras, the 3D object detection network PointRCNN, which extends region-based convolutional neural networks (R-CNNs) to 3D point clouds, clearly outperformed all other candidates. The results of a mapping mission with 313 parking spaces show that our method is capable of reliably detecting parked cars with a precision of 100% and a recall of 97%. It can be applied to unslotted and slotted parking and different parking types including parallel, perpendicular, and angle parking.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild
    Publikation
    Long-term visual localization in large scale urban environments exploiting street level imagery
    (Copernicus, 2020) Meyer, Jonas; Rettenmund, Daniel; Nebiker, Stephan [in: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences]
    In this paper, we present our approach for robust long-term visual localization in large scale urban environments exploiting street level imagery. Our approach consists of a 2D-image based localization using image retrieval (NetVLAD) to select reference images. This is followed by a 3D-structure based localization with a robust image matcher (DenseSfM) for accurate pose estimation. This visual localization approach is evaluated by means of the ‘Sun’ subset of the RobotCar seasons dataset, which is part of the Visual Localization benchmark. As the results on the RobotCar benchmark dataset are nearly on par with the top ranked approaches, we focused our investigations on reproducibility and performance with own data. For this purpose, we created a dataset with street-level imagery. In order to have independent reference and query images, we used a road-based and a tram-based mapping campaign with a time difference of four years. The approximately 90% successfully oriented images of both datasets are a good indicator for the robustness of our approach. With about 50% success rate, every second image could be localized with a position accuracy better than 0.25 m and a rotation accuracy better than 2°.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild
    Publikation
    Performance evaluation of a mobile mapping application using smartphones and augmented reality frameworks
    (2020) Hasler, Oliver; Blaser, Simon; Nebiker, Stephan [in: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences]
    In this paper, we present a performance evaluation of our smartphone-based mobile mapping application based on an augmented reality (AR) framework in demanding outdoor environments. The implementation runs on Android and iOS devices and demonstrates the great potential of smartphone-based 3D mobile mapping. The application includes several functionalities such as device tracking, coordinate, and distance measuring as well as capturing georeferenced imagery. We evaluated our prototype system by comparing measured points from the tracked device with ground control points in an outdoor environment with four different campaigns. The campaigns consisted of open and closed-loop trajectories and different ground surfaces such as grass, concrete and gravel. Two campaigns passed a stairway in either direction. Our results show that the absolute 3D accuracy of device tracking with state-of-the-art AR framework on a standard smartphone is around 1% of the travelled distance and that the local 3D accuracy reaches sub-decimetre level.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild
    Publikation
    Development of a portable high performance mobile mapping system using the robot operating system
    (Copernicus, 2018) Blaser, Stefan; Cavegn, Stefan; Nebiker, Stephan [in: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences]
    The 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 Zeitschrift
  • Vorschaubild
    Publikation
    Robust and accurate image-based georeferencing exploiting relative orientation constraints
    (Copernicus, 2018) Cavegn, Stefan; Blaser, S.; Nebiker, Stephan; Haala, N. [in: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences]
    Urban environments with extended areas of poor GNSS coverage as well as indoor spaces that often rely on real-time SLAM algorithms for camera pose estimation require sophisticated georeferencing in order to fulfill our high requirements of a few centimeters for absolute 3D point measurement accuracies. Since we focus on image-based mobile mapping, we extended the structure-from-motion pipeline COLMAP with georeferencing capabilities by integrating exterior orientation parameters from direct sensor orientation or SLAM as well as ground control points into bundle adjustment. Furthermore, we exploit constraints for relative orientation parameters among all cameras in bundle adjustment, which leads to a significant robustness and accuracy increase especially by incorporating highly redundant multi-view image sequences. We evaluated our integrated georeferencing approach on two data sets, one captured outdoors by a vehicle-based multi-stereo mobile mapping system and the other captured indoors by a portable panoramic mobile mapping system. We obtained mean RMSE values for check point residuals between image-based georeferencing and tachymetry of 2 cm in an indoor area, and 3 cm in an urban environment where the measurement distances are a multiple compared to indoors. Moreover, in comparison to a solely image-based procedure, our integrated georeferencing approach showed a consistent accuracy increase by a factor of 2–3 at our outdoor test site. Due to pre-calibrated relative orientation parameters, images of all camera heads were oriented correctly in our challenging indoor environment. By performing self-calibration of relative orientation parameters among respective cameras of our vehicle-based mobile mapping system, remaining inaccuracies from suboptimal test field calibration were successfully compensated.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild
    Publikation
    Accurate visual localization in outdoor and indoor environments exploiting 3D image spaces as spatial reference
    (International Society for Photogrammetry and Remote Sensing, 2018) Rettenmund, Daniel; Fehr, Markus; Cavegn, Stefan; Nebiker, Stephan [in: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences]
    In this paper, we present a method for visual localization and pose estimation based on 3D image spaces. The method works in indoor and outdoor environments and does not require the presence of control points or markers. The method is evaluated with different sensors in an outdoor and an indoor test field. The results of our research show the viability of single image localization with absolute position accuracies at the decimetre level for outdoor environments and 5 cm or better for indoor environments. However, the evaluation also revealed a number of limitations of single image visual localization in real-world environments. Some of them could be addressed by an alternative AR-based localization approach, which we also present and compare in this paper. We then discuss the strengths and weaknesses of the two approaches and show possibilities for combining them to obtain accurate and robust visual localization in an absolute coordinate frame.
    04B - Beitrag Konferenzschrift
  • Vorschaubild
    Publikation
    Amtliches 3D-Bild - ein neuer Geodatentyp? - Studienauftrag
    (Hochschule für Architektur, Bau und Geomatik FHNW, 12/2017) Nebiker, Stephan
    Diese Studie im Auftrag der Strategiegruppe Amtliche Vermessung der Swisstopo und der CadastreSuisse soll das Potential eines neuen Datentyps «3D-Bild» und von darauf aufbauenden Geodiensten für die Amtliche Vermessung im Speziellen sowie die Geoinformationsbranche und die Gesellschaft im Allgemeinen aufzeigen. Die Studie bietet eine umfassende Auslegeordnung und eine fundierte Übersicht zur Thematik mit strategischen Anwendungspotentialen, Handlungsoptionen und Empfehlungen. Die Studie zeigt auf, dass die Hauptherausforderungen vor allem strategischer, wirtschaftlicher und politischer Art sind und dass die technische Machbarkeit bereits heute gegeben ist. Entsprechend liegt der Fokus auf der Beantwortung strategischer Fragen und auf dem Aufzeigen von Umsetzungsoptionen. Mit einem Normierungsvorschlag auf der Basis einer REST Schnittstelle wird ein möglicher Weg aufgezeigt. Das «Reality Capturing», d.h. die detaillierte, genaue und realitätsgetreue Erfassung der urbanen und ländlichen Umgebung, und die Schaffung cloudbasierter «Digitaler Realitäten» sind seit Kurzem im grossen Stil technologisch möglich. Die Entwicklung von Technologien und Services zum Aufbau und zur Nutzung digitaler Realitäten wird von Herstellern und Dienstleistern aktiv forciert und in zahlreichen Anwendungsbereichen rasch adaptiert. Zu den Schlüsselmärkten für digitale Realitäten gehören die Fahrzeugnavigation und das zukünftige autonome Fahren. Grosse Automobilkonzerne und Internetgiganten arbeiten mit einem gewaltigen Effort an der Realisierung globaler, detailreicher 3D-Karten auf der Basis mobil erfasster Geodaten – allerdings mit einem Fokus auf «3D-Karten für Maschinen». Die weiteren und für diese Studie besonders relevanten Schlüsselmärkte für digitale Realitäten sind das Ma-nagement und der Werterhalt in den Bereichen öffentliche Infrastruktur und Gebäude. Im Zentrum dieser Studie steht das «3D-Bild» als besonders vielversprechende Realisierungs-möglichkeit für digitalen Realitäten. In einem ersten Teil wird die Grundidee eines georeferen-zierten 3D-Bilds vorgestellt (Kap. 3) und ein Überblick über den aktuellen Stand der Forschung und der Technik gegeben (Kap. 5). Im zweiten Teil werden wichtige konzeptionelle und technische Aspekte zur Erfassung, Georeferenzierung, Speicherung und Nutzung von 3D-Bilddaten behandelt (Kap. 6) sowie konkrete Normierungsvorschläge für deren Nutzung präsentiert (Kap. 7). Im dritten Teil werden die wirtschaftlichen Aspekte: Märkte, Anwendungen, Nutzen und Wirtschaftlichkeit (Kap. 8) sowie organisatorische Aspekte wie mögliche Prozesse, Rollen und Betriebsmodelle sowie rechtliche Fragen erörtert (Kap. 9). In einem abschliessenden Kapitel werden die Relevanz der Thematik sowie die Chancen und Risiken für die Geomatikbranche insgesamt und die Amtliche Vermessung im Speziellen diskutiert. Die Studie zeigt, dass ein Datentyp «3D-Bild» und darauf aufbauende 3D-Bilddienste gut geeig-net sind, um eine einfach und sehr breit nutzbare digitale Realität für zahlreiche Anwendungs-bereiche aufzubauen und zu betreiben. 3D-Bilddienste sind technisch machbar, führen zu einer deutlichen Steigerung in der Produktivität und zu einem eigentlichen Paradigmenwechsel – be-dingt durch die Verlagerung von Feldarbeiten durch Vermessungsfachleute an den PC-Arbeits-platz der unterschiedlichen Fachspezialistinnen und –spezialisten. Erfahrungen mit bereits reali-sierten 3D-Bilddiensten zeigen Kosteneinsparungen in der Grössenordnung von 30-60% und Zeiteinsparungen von bis zu 70%. Hinzu kommt eine deutliche Verbesserung der Arbeitssicherheit durch das Wegfallen von Vermessungsarbeiten im Fahrbahnbereich. Wie die Studie aufzeigt, sind bereits heute zahlreiche konkrete Anwendungen von 3D-Bilddiens-ten im Aussenraum realisiert. Ein besonderes Potential dürften zukünftige Anwendungen im In-nenbereich haben, wie etwa die Baufortschrittsdokumentation, das Facility Management oder die Dokumentation von 3D-Grundeigentum. Die Zukunftsfähigkeit von 3D-Bilddiensten wird durch aktuelle Entwicklungen und Trends in der Forschung unterstrichen: so ist etwa zu erwarten, dass diese eine rein bildbasierte exakte Lokalisierung und vor allem auch Orientierung von Smartphones etc. ermöglichen werden. Damit dürften georeferenzierte 3D-Bilder die Geodatenbasis für völlig neue Anwendungen etwa im Bereich Augmented Reality schaffen. Zusammenfassend kann festgehalten werden, dass die Entwicklung cloud-basierter Geoinformationslösungen und georeferenzierter 3D-Bilddienste in vollem Gang ist und mit oder ohne Akteure aus der Geomatik oder der Amtlichen Vermessung stattfinden wird. Aufgrund ihrer Al-leinstellungsmerkmale wie Qualitätsverständnis, Erfahrung im Betrieb interoperabler und nach-haltiger Geodateninfrastrukturen und des Potentials zur Realisierung eigener neue Anwendungen überwiegen die Chancen für ein aktives Engagement der Geomatikbranche die Risiken des Abwartens oder Abseitsstehens bei weitem.
    05 - Forschungs- oder Arbeitsbericht