The integrated spatio-temporal approach to real-time machine vision, which has allowed outstanding performance with moderate computing power, is extended to obstacle recognition and relative spatial state estimation using monocular vision. A modular vision system architecture is discussed centering around features and objects. Experimental results with VaMoRs, a5-ton test vehicle are given. Stopping in front of obstacles of at least 0.5 m2 cross section has been demonstrated on unmarked two-lane roads at velocities up to 40 km/h.


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    Title :

    Relative 3D-state estimation for autonomous visual guidance of road vehicles


    Additional title:

    Relative 3D-Statusschätzung für eine autonome visuelle Führung von Straßenfahrzeugen


    Contributors:


    Publication date :

    1990


    Size :

    11 Seiten, 9 Bilder, 1 Tabelle, 12 Quellen



    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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