In this paper, we present a method of detecting the rail track bends and flaws. Different from the traditional machine-vision based methods which analyze the images of the rail surface, we estimate the shake of the camera — which is caused by the flaw or bend of the rail track — from the video used for railway environment surveillance. We provide both theoretical analysis — based on the theory of optical flow and passive navigation — and the corresponding fast algorithms, i.e. the brightness-pattern-matching code (BPMC) and shaking-type code (STC). Our method uses the surveillance video of the railway environment directly, thus, we do not need extra expensive instruments.


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    Titel :

    Detect the rail track flaw by estimating the camera shaking


    Beteiligte:
    Wang, Liang (Autor:in) / Luo, Xiaoyue (Autor:in) / Horn, Berthold K. P. (Autor:in) / Wang, Shengchun (Autor:in) / Luo, Siwei (Autor:in)


    Erscheinungsdatum :

    01.10.2014


    Format / Umfang :

    1552086 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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