Reliable vehicle ego motion estimation based on visual information is an important research goal because it has applications like accurate long term localization by fusion with other sensors, temporal fusion between frames, moving obstacles detection and tracking, path planning etc. This paper evaluates and significantly improves some steps of existing visual odometry methods. The main contribution is related to accuracy improvements in case of illumination changes by using the rank transform. Additionally we propose a new consistency check, based on image deformations, for subsets of features considered during the RANSAC iterations of the algorithm. Performance of GPU execution and results in various traffic scenarios are presented in order to show the advantages and the robustness of the method.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Stereo based visual odometry in difficult traffic scenes


    Beteiligte:


    Erscheinungsdatum :

    01.06.2012


    Format / Umfang :

    1011832 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Stereo Based Visual Odometry in Difficult Traffic Scenes

    Golban, C. / Szakats, I. / Nedevschi, S. et al. | British Library Conference Proceedings | 2012


    Uncertainty Estimation for Stereo Visual Odometry

    Ross, Derek / De Petrillo, Matteo / Strader, Jared et al. | British Library Conference Proceedings | 2021


    Robust stereo visual odometry from monocular techniques

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


    Large scale visual odometry using stereo vision

    Hernández-Gutiérrez, Andrés / Nieto, Juan I. / Vidal-Calleja, Teresa A. et al. | BASE | 2009

    Freier Zugriff