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.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Monocular vision-based range estimation of on-road vehicles


    Contributors:


    Publication date :

    2014-07-01


    Size :

    595673 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Location and Relative Speed Estimation of Vehicles By Monocular Vision

    Marmoiton, F. / Collange, F. / Derutin, J. et al. | British Library Conference Proceedings | 2000


    Location and relative speed estimation of vehicles by monocular vision

    Marmoiton, F. / Collange, F. / Derutin, J.P. | IEEE | 2000



    Monocular depth estimation for vision-based vehicles based on a self-supervised learning method

    Tektonidis, Marco / Monnin, David | British Library Conference Proceedings | 2020