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  • Dense 3D Mapping using Volume Registration

    Author(s)
    Lincoln, Luke
    Gonzalez, Ruben
    Griffith University Author(s)
    Gonzalez, Ruben
    Lincoln, Luke
    Year published
    2016
    Metadata
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    Abstract
    In this paper, a novel closed form solution is presented for solving the simultaneous localization and mapping (SLAM) problem. Unlike existing methods which rely on iterative feature matching, the proposed method utilises 3D phase correlation. This method provides high noise robustness, even in the presence of moving objects within the scene which are problematic for SLAM systems. Quantitative and qualitative experimental results are presented, evaluating the noise sensitivity, reconstruction quality and robustness in the context of moving objects.In this paper, a novel closed form solution is presented for solving the simultaneous localization and mapping (SLAM) problem. Unlike existing methods which rely on iterative feature matching, the proposed method utilises 3D phase correlation. This method provides high noise robustness, even in the presence of moving objects within the scene which are problematic for SLAM systems. Quantitative and qualitative experimental results are presented, evaluating the noise sensitivity, reconstruction quality and robustness in the context of moving objects.
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    Conference Title
    NATURE OF COMPUTATION AND COMMUNICATION (ICTCC 2016)
    Volume
    168
    DOI
    https://doi.org/10.1007/978-3-319-46909-6_3
    Subject
    Computer Vision
    Publication URI
    http://hdl.handle.net/10072/142098
    Collection
    • Conference outputs

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