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Automatic real-time SLAM relocalization based on a hierarchical bipartite graph model

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Abstract

The need to increase the robustness of a real-time monocular SLAM system raises the important problem of relocalization; namely, how to automatically recover a SLAM system after tracking failures. We address this problem by proposing a real-time relocalization algorithm based on a hierarchical bipartite graph model. When the SLAM system is lost, we use the latter model to find sufficient correspondences between the detected image and stored map features, thus achieving efficient, real-time relocalization. The model accounts for both temporal and spatial constraints. Experimental results on both synthetic and real data support the effectiveness of the proposed algorithm.

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Authors and Affiliations

  1. National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China

    QiuLei Dong, ZhaoPeng Gu & ZhanYi Hu

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  1. QiuLei Dong
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  2. ZhaoPeng Gu
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  3. ZhanYi Hu
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Correspondence to QiuLei Dong.

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Dong, Q., Gu, Z. & Hu, Z. Automatic real-time SLAM relocalization based on a hierarchical bipartite graph model. Sci. China Inf. Sci. 55, 2841–2848 (2012). https://doi.org/10.1007/s11432-012-4669-5

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  • DOI: https://doi.org/10.1007/s11432-012-4669-5

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