Stereo visual odometry is one of the most accurate dead-reckoning methods for estimating the motion of a moving vehicle but it strongly depends on a robust matching of the image features in the stereo frame. If a stereo camera is observing the environment from a critically small distance the two field of view can be subjected to poor or absent overlapping. That leads to failure of the computation pipeline because no stereo observations can be made. In this paper, we present a solution to this problem by taking advantage of monocular visual odometry techniques to propagate the pose estimations when the number of feature matches in the stereo frame is too low to produce accurate results. The proposed algorithm is tested on a challenging scenario for a stereo setup and a ground truth is given by mounting the stereo camera on a linear slide. Experimental results show that our algorithm is able to successfully recover failures of the stereo pipeline, obtaining a final position error of 1.2% of the total travelled path length in our dataset.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Stereo visual odometry failure recovery using monocular techniques


    Beteiligte:


    Erscheinungsdatum :

    01.06.2017


    Format / Umfang :

    576827 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Robust stereo visual odometry from monocular techniques

    Persson, Mikael / Piccini, Tommaso / Felsberg, Michael et al. | IEEE | 2015


    Ground Vehicle Monocular Visual Odometry

    Sabry, Mohamed / Al-Kaff, Abdulla / Hussein, Ahmed et al. | IEEE | 2019


    Monocular Outlier Detection for Visual Odometry

    Buczko, Martin / Willert, Volker | British Library Conference Proceedings | 2017


    Monocular Outlier Detection for Visual Odometry

    Buczko, Martin / Willert, Volker | IEEE | 2017


    Multimodal scale estimation for monocular visual odometry

    Fanani, Nolang / Sturck, Alina / Barnada, Marc et al. | IEEE | 2017