Driver support in inner-city road traffic based on machine vision still represents a considerable challenge. Model-based machine vision exploits a-priori knowledge, for example about the lane structure of roads and intersections, to select relevant image structures. Infrastructural objects, such as lamp posts or masts with attached traffic signs, often are located near road or intersection borders and can serve as additional cues for driving space boundaries. We report an approach to detect, localize, and track such objects in image sequences recorded from within a driving vehicle. This facilitates to estimate a vehicle position more robustly even in cases where road features cannot be extracted reliably.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Machine-vision-based detection and tracking of stationary infrastructural objects beside inner-city roads


    Contributors:
    Fleischer, K. (author) / Nagel, H.H. (author)


    Publication date :

    2001-01-01


    Size :

    929758 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Machine-Vision-Based Detection and Tracking of Stationary Infrastructural Objects Beside Innercity Roads

    Fleischer, K. / Nagel, H. / IEEE | British Library Conference Proceedings | 2001


    Elevated steel roads for inner-city traffic

    Wolf, W. | Engineering Index Backfile | 1962



    Stationary Vehicles Detection on Smart Highways and Roads using Spatio-temporal Tracking

    Khan, Wasiq / Kelly, Jessica / Al-Kafri, Ala et al. | IEEE | 2023


    Robot painter walks beside cars

    General Motors,US | Automotive engineering | 1981