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  • Probabilistic Models for 3D Urban Scene Understanding from Movable Platforms

    Andreas Geiger

    Band 025 von Schriftenreihe / Institut für Mess- und Regelungstechnik, Karlsruher Institut für Technologie
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    This work is a contribution to understanding multi-object traffic scenes from video sequences. All data is provided by a camera system which is mounted on top of the autonomous driving platform AnnieWAY. The proposed probabilistic generative model reasons jointly about the 3D scene layout as well as the 3D location and orientation of objects in the scene. In particular, the scene topology, geometry as well as traffic activities are inferred from short video sequences.

    Umfang: V, 162 S.

    Preis: €42.00 | £39.00 | $74.00

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    Empfohlene Zitierweise
    Geiger, A. 2013. Probabilistic Models for 3D Urban Scene Understanding from Movable Platforms. Karlsruhe: KIT Scientific Publishing. DOI: https://doi.org/10.5445/KSP/1000036064
    Geiger, A., 2013. Probabilistic Models for 3D Urban Scene Understanding from Movable Platforms. Karlsruhe: KIT Scientific Publishing. DOI: https://doi.org/10.5445/KSP/1000036064
    Geiger, A. Probabilistic Models for 3D Urban Scene Understanding from Movable Platforms. KIT Scientific Publishing, 2013. DOI: https://doi.org/10.5445/KSP/1000036064
    Geiger, A. (2013). Probabilistic Models for 3D Urban Scene Understanding from Movable Platforms. Karlsruhe: KIT Scientific Publishing. DOI: https://doi.org/10.5445/KSP/1000036064
    Geiger, Andreas. 2013. Probabilistic Models for 3D Urban Scene Understanding from Movable Platforms. Karlsruhe: KIT Scientific Publishing. DOI: https://doi.org/10.5445/KSP/1000036064




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    Weitere Informationen

    Veröffentlicht am 30. August 2013

    Sprache

    Englisch

    Seitenanzahl:

    192

    ISBN
    Paperback 978-3-7315-0081-0

    DOI
    https://doi.org/10.5445/KSP/1000036064