Autonomous and guide assisted vehicles make a heavy use of computer vision techniques to perceive the environment where they move. In this context, the European PROMETHEUS program is carrying on activities in order to develop autonomous vehicle monitoring that assists people to achieve safer driving. Car detection is one of the topics that are faced by the program. Our contribution proposes the development of this task in two stages: the localization of areas of interest and the formulation of object hypotheses. In particular, the present paper proposes a new approach that builds structural descriptions of objects from edge segmentations by using geometrical organization. This approach has been applied to the detection of cars in traffic scenes. We have analyzed images taken from a moving vehicle in order to formulate obstacle hypotheses: preliminary results confirm the efficiency of the method.


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    Title :

    Line grouping using perceptual saliency and structure prediction for car detection in traffic scenes


    Contributors:

    Conference:

    Intelligent Robots and Computer Vision XII: Algorithms and Techniques ; 1993 ; Boston,MA,United States


    Published in:

    Publication date :

    1993-08-20





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English





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