A statistical and computer vision approach using tracked moving vehicle shapes for auto-calibrating traffic surveillance cameras is presented. Vanishing point of the traffic direction is picked up from Linear Regression of all tracked vehicle points. Preliminary straightening model is then built to help collect statistics of the typical vehicle class traveling in each particular scene. Analysis on this class eventually helps to compute the complete calibration parameters. Results obtained from the validation step against traditional methods in different traffic locations demonstrate its desirable accuracy with much more flexibility and reliability.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Self-Calibration of Traffic Surveillance Camera using Motion Tracking


    Beteiligte:
    Thi, Tuan Hue (Autor:in) / Lu, Sijun (Autor:in) / Zhang, Jian (Autor:in)


    Erscheinungsdatum :

    01.10.2008


    Format / Umfang :

    515906 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Fully Automatic Roadside Camera Calibration for Traffic Surveillance

    Dubska, Marketa / Herout, Adam / Juranek, Roman et al. | IEEE | 2015



    A Novel Camera Calibration Technique for Visual Traffic Surveillance

    Yung, N.H.C. / ITS Congress Association | British Library Conference Proceedings | 2000


    On Automatic and Dynamic Camera Calibration Based on Traffic Visual Surveillance

    Li, Y. / zhu, f. / Ai, Y. et al. | British Library Conference Proceedings | 2007


    On Automatic and Dynamic Camera Calibration based on Traffic Visual Surveillance

    Li, Yuantao / Zhu, Fenghua / Ai, Yunfeng et al. | IEEE | 2007