This paper presents a monocular vision-based range estimation of on-road vehicles approach. The proposed approach mainly combines non-drivable region from drivable region detection for detection region estimation instead of detecting the whole image, shadow detection for on-road object extraction, vehicle structure points estimation and adjusting for on-road vehicle classification, and motion vector and Kalman filter of on-road vehicles for collision avoiding. Extensive experimentation was performed to demonstrate that the proposed approach can correctly and dynamically estimate the relative distance of on-road vehicles in actual traffic conditions.


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    Titel :

    Monocular vision-based range estimation of on-road vehicles


    Beteiligte:
    Chih-Ming Hsu (Autor:in) / Fei-Hong Chao (Autor:in) / Feng-Li Lian (Autor:in)


    Erscheinungsdatum :

    01.07.2014


    Format / Umfang :

    595673 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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