Blaser, Stefan

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Stefan
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Blaser, Stefan

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2021 - 20222
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Autor:in: Meyer, Jonas × Typ: 04B - Beitrag Konferenzschrift ×

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  • Vorschaubild
    Publikation
    AI-based 3D detection of parked vehicles on a mobile mapping platform using edge computing
    (2022) Meyer, Jonas; Blaser, Stefan; Nebiker, Stephan [in: The international archives of the photogrammetry, remote sensing and spatial information sciences]
    In this paper we present an edge-based hardware and software framework for the 3D detection and mapping of parked vehicles on a mobile mapping platform for the use case of on-street parking statistics. First, we investigate different point cloud-based 3D object detection methods on our extremely dense and noisy depth maps obtained from low-cost RGB-D sensors to find a suitable object detector and determine the optimal preparation of our data. We then retrain the chosen object detector to detect all types of vehicles, rather than standard cars only. Finally, we design and develop a software framework integrating the newly trained object detector. By repeating the parking statistics of our previous work (Nebiker et al., 2021), our software is tested regarding the detection accuracy. With our edge-based framework, we achieve a precision and recall of 100% and 98% respectively on any parking configuration and vehicle type, outperforming all other known work on on-street parking statistics. Furthermore, our software is evaluated in terms of processing speed and volume of generated data. While the processing speed reaches only 1.9 frames per second due to limited computing resources, the amount of data generated is just 0.25 KB per frame.
    04B - Beitrag Konferenzschrift
  • Vorschaubild
    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, Stephan [in: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences]
    With 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-datasets
    04B - Beitrag Konferenzschrift