Vision-based driver assistance systems have great potential for preventing fatalities. This work addresses the problem of 3D monocular vehicle tracking and turn rate estimation in situations where vehicles need to be tracked along intersections and curves. To estimate the tracked vehicle's turn rate, an approach based on image feature correspondences and a simplified geometric vehicle model is used. The model is robustly and efficiently fitted to the matched image features using an improved RANSAC scheme that automatically enforces physically plausible vehicle motions and speeds up the overall system at the same time. Temporal integration of the computed turn rates is performed by an Extended Kalman Filter with the bicycle motion model. Experiments with real world data show the applicability and robustness of the proposed concepts.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Feature-based monocular vehicle turn rate estimation from a moving platform


    Beteiligte:
    Gabb, Michael (Autor:in) / Kaliuk, Artem (Autor:in) / Ruland, Thomas (Autor:in) / Lohlein, Otto (Autor:in) / Westenberger, Antje (Autor:in) / Dietmayer, Klaus (Autor:in)


    Erscheinungsdatum :

    2013-06-01


    Format / Umfang :

    1049131 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    FEATURE-BASED MONOCULAR VEHICLE TURN RATE ESTIMATION FROM A MOVING PLATFORM

    Gabb, M. / Kaliuk, A. / Ruland, T. et al. | British Library Conference Proceedings | 2013


    Moving Object Detection with Photometric Monocular SLAM on a Moving Ego-Platform

    Golla, Lokesh Chandra Sekhar / Molander, Soren / Nguyen, Duong-Van | IEEE | 2023


    Moving vehicle detection and tracking using monocular vision

    Miao,X. / Li,S. / Shen,H. et al. | Kraftfahrwesen | 2014


    Monocular-Vision-Based Moving Target Geolocation Using Unmanned Aerial Vehicle

    Tingwei Pan / Baosong Deng / Hongbin Dong et al. | DOAJ | 2023

    Freier Zugriff