Rear-end vehicle collisions are common in road traffic. Often acute neck injuries are the consequence. The severity of these and other injuries may be reduced by an onboard system that estimates the time of possible rear-end crashes and makes preparations (e.g. by moving the neck support in a better position or by tighten the seat belt). We are investigating the possibilities for time to collision estimation using a standard rear camera as a sensor. Two interesting techniques (the generation of a street texture and the usage of a particle filter) are presented and some preliminary results are shown. We are investigating the possibilities of a vision based time to collision sensor or more general a vision sensor that detects approaching vehicles in the rear camera while driving forward. The generation of a street texture seems to be a very interesting idea, but more work has to be done to make it robust against diverse weather and traffic situations. The particle filter provides the possibility to track multiple hypotheses simultaneously and is thus robust against clutter. But there is still need for a better vehicle classification and a post processing step for the position and velocity data.


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    Title :

    Towards time to collision estimation with a rear camera


    Contributors:


    Publication date :

    2007


    Size :

    16 Seiten, 11 Bilder, 24 Quellen



    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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