We present an improved model for MRF-based depth upsampling, guided by image-as well as 3D surface normal features. By exploiting the underlying camera model we define a novel regularization term that implicitly evaluates the planarity of arbitrary oriented surfaces. Our method improves upsampling quality in scenes composed of predominantly planar surfaces, such as urban areas. We use a synthetic dataset to demonstrate that our approach outperforms recent methods that implement distance-based regularization terms. Finally, we validate our approach for mapping applications on our experimental vehicle.


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    Titel :

    Guided depth upsampling for precise mapping of urban environments


    Beteiligte:
    Wirges, Sascha (Autor:in) / Roxin, Bjorn (Autor:in) / Rehder, Eike (Autor:in) / Kuhner, Tilman (Autor:in) / Lauer, Martin (Autor:in)


    Erscheinungsdatum :

    2017-06-01


    Format / Umfang :

    1684904 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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