This paper deals with a pedestrian pre-crash sensor based on dense stereovision and motion analysis. The paper aim to provide means to deploy safety measures before a crash occurs. Depending on the concrete selected actuator, it could be interesting to know the type of object (e. g. vehicle, pedestrian, bicyclist, etc.) involved in the collision. Some actuators need the information about the collision partner type, because they have to be triggered only in specific situations, or in a situation dependent manner. The authors present a pedestrian detection system based on dense stereo and motion, acting as pre-crash sensor. In order to detect pedestrians, we use simple features such as object size, speed, and also more complex, motion based features. All these features are combined into a flexible, Bayesian framework.


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    Title :

    Multi-feature walking pedestrian detection using dense stereo and motion


    Additional title:

    Erkennung verschiedenartigen Fußgänger-Verhaltens mit Hilfe von Stereosehen und Bewegungsanalyse


    Contributors:


    Publication date :

    2001


    Size :

    6 Seiten, 6 Bilder, 19 Quellen


    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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