Lidar and cameras serve as essential sensors for automated vehicles and intelligent robots, and they are frequently fused in complicated tasks. Precise extrinsic calibration is the prerequisite of Lidar-camera fusion. Hand-eye calibration is almost the most commonly used targetless calibration approach. This article presents a particular degeneration problem of hand-eye calibration when sensor motions lack rotation. This context is common for ground vehicles, especially those traveling on urban roads, leading to a significant deterioration in translational calibration performance. To address this problem, we propose a novel targetless Lidar-camera calibration method based on cross-modality structure consistency. Our proposed method utilizes cross-modality structure consistency and ensures global convergence within a large search range. Moreover, it achieves highly accurate translation calibration even in challenging scenarios. Through extensive experimentation, we demonstrate that our approach outperforms three other state-of-the-art targetless calibration methods across various metrics. Furthermore, we conduct an ablation study to validate the effectiveness of each module within our framework.


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    Titel :

    Targetless Lidar-Camera Calibration via Cross-Modality Structure Consistency


    Beteiligte:
    Ou, Ni (Autor:in) / Cai, Hanyu (Autor:in) / Wang, Junzheng (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    01.01.2024


    Format / Umfang :

    5379809 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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