Todays vehicles are more and more equipped with video cameras. These cameras are used e.g. for lane and parking assist systems. For the localization of the vehicle in the world the Global Positioning System is widely used. Unfortunately, GPS is very imprecise and insufficient for many driver assistance applications. To overcome this limitation, a more precise localization using a different approach has to be found. High quality localization sensors are already available on the market but still too expensive for mass integration in automobiles. The aim is to extract additional information from already established car equipment and to use it for precise localization. The approach combines map information with extracted image features using a model based algorithm. The introduced method is derived from a line style approach using landmarks. The main disadvantage of the line style approach is its reliance on clear visibility of the line landmarks, which cannot be guaranteed in real-world scenarios (if e.g. ground based lines like lane border marks are used as features, they are often occluded by parked cars and other obstacles). Therefore a major difference of the presented method is to utilize 3D models of buildings generated from outline data, and match them with borders of reference objects in the real world.


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    Title :

    Vehicle localization by utilization of map-based outline information and grayscale image feature extraction


    Additional title:

    Fahrzeuglokalisierung durch Nutzung kartenbasierter Konturinformation und Grauwert-Bilderkennung


    Contributors:


    Publication date :

    2010


    Size :

    8 Seiten, 12 Bilder, 11 Quellen



    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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