This paper proposes a method to calculate the distance between vehicles from the perspective of the car, in which monocular vision information from the driving recorders of the host car is used to calculate the distance between the host car and the car ahead. The author first detects all the vehicles with their type in an image input, sifts out the front vehicle from them, and locates the license plate from the bounding box of the vehicle. Then the paper designs an algorithm to measure the length of the license plate in the bounding box of the license plate and utilizes the common characteristic of license plates in America and in other countries that all the plates of one type of vehicles in one country share to derive a novel method to convert the length of the plate in the image into distance between the driving recorder and the license plate, therefore obtaining car-to-car distance.


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    Titel :

    Measurement of distance between vehicles based on monocular vision


    Beteiligte:
    Mo, Qingyu (Autor:in)

    Kongress:

    International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2022) ; 2022 ; Wuhan,China


    Erschienen in:

    Proc. SPIE ; 12287


    Erscheinungsdatum :

    13.10.2022





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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