This paper describes the implementation of a realtime architecture dedicated to obstacle detection in the automotive domain, and more particularly to pre-crash situations. The method, based on stereovision, is of high complexity and can not run in real-time on standard processors. Therefore, the application is accelerated with the use of special purpose hardware; in particular, a highly parallelized disparity engine is presented. A prototype board was built, which achieves a performance of 460 GOPS and computes the application at the rate of 22 frames per second, thus reaching road safety constraints.


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    Titel :

    Stereovision-based 3D obstacle detection for automotive safety driving assistance


    Beteiligte:


    Erscheinungsdatum :

    2009-10-01


    Format / Umfang :

    1623483 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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