Auflistung nach Schlagwort "Object detection"

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  • Context-based urban terrain reconstruction from images and videos 
    Bulatov, Dimitri; Rottensteiner, Franz; Schulz, Karsten (Göttingen : Copernicus GmbH, 2012)
    Detection of buildings and vegetation, and even more reconstruction of urban terrain from sequences of aerial images and videos is known to be a challenging task. It has been established that those methods that have as ...
  • Detection and 3D modelling of vehicles from terrestrial stereo image pairs 
    Coenen, Max; Rottensteiner, Franz; Heipke, Christian (Göttingen : Copernicus GmbH, 2017)
    The detection and pose estimation of vehicles plays an important role for automated and autonomous moving objects e.g. in autonomous driving environments. We tackle that problem on the basis of street level stereo images, ...
  • The ISPRS benchmark on urban object classification and 3d building reconstruction 
    Rottensteiner, Franz; Sohn, Gunho; Jung, Jaewook; Gerke, Markus; Baillard, Caroline; Benitez, Sebastien; Breitkopf, Uwe (Göttingen : Copernicus GmbH, 2012)
    For more than two decades, many efforts have been made to develop methods for extracting urban objects from data acquired by airborne sensors. In order to make the results of such algorithms more comparable, benchmarking ...
  • Optimisation of the calibration process of a k-tls based multi-sensor-system by genetic algorithms 
    Hartmann, J.; Von Gösseln, I.; Schild, N.; Dorndorf, A.; Paffenholz, J.-A.; Neumann, I. (Göttingen : Copernicus GmbH, 2019)
    In recent years, the requirements in the industrial production of elongated objects, e.g., aircraft, have been increased. An essential aspect of the production process is the 3D object detection as well as the qualitative ...
  • Precise Vehicle reconstruction for autonomous driving applications 
    Coenen, M.; Rottensteiner, F.; Heipke, C. (Göttingen : Copernicus GmbH, 2019)
    Interactive motion planing and collaborative positioning will play a key role in future autonomous driving applications. For this purpose, the precise reconstruction and pose estimation of other traffic participants, ...
  • Qtrajectories: improving the quality of object tracking using self-organizing camera networks 
    Jaenen, Uwe; Feuerhake, Udo; Klinger, Tobias; Muhle, Daniel; Haehner, Joerg; Sester, Monika; Heipke, Christian (Göttingen : Copernicus GmbH, 2012)
    Previous work in the research field of video surveillance intensively focused on separated aspects of object detection, data association, pattern recognition and system design. In contrast, we propose a holistic approach ...
  • Supervised detection of bomb craters in historical aerial images using convolutional neural networks 
    Clermont, D.; Kruse, C.; Rottensteiner, F.; Heipke, C. (Göttingen : Copernicus, 2019)
    The aftermath of the air strikes during World War II is still present today. Numerous bombs dropped by planes did not explode, still exist in the ground and pose a considerable explosion hazard. Tracking down these duds ...
  • Using Object Detection on Social Media Images for Urban Bicycle Infrastructure Planning: A Case Study of Dresden 
    Knura, Martin; Kluger, Florian; Zahtila, Moris; Schiewe, Jochen; Rosenhahn, Bodo; Burghardt, Dirk (Basel : MDPI, 2021)
    With cities reinforcing greener ways of urban mobility, encouraging urban cycling helps to reduce the number of motorized vehicles on the streets. However, that also leads to a significant increase in the number of bicycles ...
  • Vehicle Pose and Shape Estimation in UAV Imagery Using a CNN 
    El Amrani Abouelassad, S.; Mehltretter, M.; Rottensteiner, F. (Katlenburg-Lindau : Copernicus Publications, 2023)
    Vehicle reconstruction from single aerial images is an important but challenging task. In this work, we introduce a new framework based on convolutional neural networks (CNN) that performs monocular detection, pose, shape ...